Acetylcholinesterase Inhibitory Potential of Plant-Based Phenolics in the Treatment of Alzheimer's Disease: An In Silico Approach

Acetylcholinesterase Inhibitory Potential of Plant-Based Phenolics in the Treatment of Alzheimer's Disease: An In Silico Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Acetylcholinesterase Inhibitory Potential of Plant-Based Phenolics in the Treatment of Alzheimer's Disease: An In Silico Approach Mojeed Ayoola Ashiru, Rasheed Adewale Adigun, Musa Oladayo Babalola, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6356281/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Alzheimer's disease is the most prevalent cause of dementia, accounting for more than seventy per cent of all the reported cases. Among the various treatment strategies, inhibiting the action of acetylcholinesterase that breaks down the neurotransmitter acetylcholine is the most common. In this report, thirty-eight phenolic compounds were retrieved from the PubChem database and screened in silico against acetylcholinesterase. Non-covalent molecular docking, molecular mechanics-generalized born surface area (MM-GBSA), and molecular dynamics (MD) were used to predict their binding mode, affinity, free energy, and the stability of the protein-ligand complex. These were followed by drug-likeness screening and a rigorous prediction of their absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters. Myricetin (-13.9 kcal/mol) was predicted to have the highest binding affinity among the phenolics, though lower than the bound donepezil (-16.3 kcal/mol). To increase the binding affinity of myricetin, it was modified via a Schiff base formation, which gave the hydrazine B-1 a binding affinity of -17.7 kcal/mol, higher than donepezil. The molecular dynamics simulation showed that the modified ligands have better stability than myricetin. The ADMET and drug-likeness studies showed that the top four phenolics and myricetin analogue derivatives could be further developed as potential drug candidates. Acetylcholinesterase ADMET Modeling Alzheimer’s disease Molecular Docking Molecular Dynamics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1.0 Introduction Dementia is an age-related condition that affects the cognitive brain processes of memory, language, perception, and cognition, making it challenging to sustain everyday tasks [ 1 ]. Alzheimer's disease (AD) is one of the most well-researched forms of dementia. In the USA, AD is the most prevalent form of dementia, accounting for 60–80 per cent of all cases [ 2 ]. Alzheimer's disease is projected to affect 12.7 million people aged 65 years and older by 2050 [ 3 , 4 ]. Protein misfolding and aggregation, oxidative stress, mitochondrial abnormalities, and neuroinflammatory processes are all hallmarks of Alzheimer's disease (AD) at the molecular level [ 5 ]. Unfortunately, no definite consensus on the causation of Alzheimer's disease exists, although various hypotheses have been proposed. The most prevalent of them is the cholinergic hypothesis, which postulates that a decrease in the amount of the neurotransmitter acetylcholine (ACh) is associated with cognitive decline. In another amyloid hypothesis, AD has been linked with the formation of β-amyloid (Aβ) plaques in the brain [ 6 , 7 ], which is a distinctive feature of AD. ACh levels in the brain are regulated by the enzyme acetylcholinesterase (AChE, EC number 3.1.1.7), which catalyzes the breakdown of the neurotransmitter ACh. Butyrylcholinesterase (BuChE) also degrades ACh more slowly and to a lesser level [ 6 , 7 ]. Interestingly, AChE has also been reported to bind specifically to Aβ and play a crucial role in Aβ plaque formation [ 8 ]. A single molecule of AChE breaks down over 20,000 molecules of ACh in one second. The enzyme uses three crucial amino acid residues (glutamine, histidine, and serine) known as the catalytic triad at its 20 Å deep gorge. The hydrophobic aromatic residues along the gorge propel ACh it into the reaction orientation where the oxygen atom on serine binds to the ACh ester's carbonyl carbon. The loosely-bonded hydrogen atom to the serine gets transferred to the AChE oxygen atom, breaking its intramolecular bond, and thereby releasing choline. Serine containing the remaining acetate gets protonated by a water molecule leading to the formation of a new bond between the acetate and the oxygen of the water molecule, releasing acetate in the process. The catalytic triad is restored to its original form, ready to break more Ach [ 9 ]. Therefore, by regulating the clearance of ACh, inhibition of AChE has always been an excellent therapeutic approach. The US Food and Drug Administration (US FDA) has approved three AChE inhibitors for Alzheimer's disease: donepezil, rivastigmine, and galantamine [ 10 ]. Tacrine was authorized by the FDA but has subsequently been withdrawn owing to hepatotoxicity concerns [ 11 ]. Despite the numerous treatment options for Alzheimer's disease, interest in plant-based herbal medicine is growing these days due to the lack of complete efficacy and side effects of the approved drugs [ 12 ]. Traditional medicine has been known for using plant-based extracts to treat various diseases, including skin infections, candidiasis, dyspepsia, neurodegenerative disease, cough, and fever [ 13 ]. However, as technology and drug discovery have advanced in the last century, this practice has begun to receive renewed attention [ 14 ]. The Food and Drug Administration has approved about 25% of new medications including phytochemicals [ 15 , 16 ]. Currently, more than USD 65 billion is made annually from the sale of pharmaceuticals derived from plants, with approximately 80% of antibacterial, cardiovascular, immunosuppressive, and anticancer medications being derived from plants [ 17 ]. Nevertheless, 6% and 15% of the estimated 450,000 plant species worldwide have undergone pharmacological and phytochemical screening, respectively [ 18 ]. Thus, many bioactive compounds may have strong physiological effects on several illnesses. For example, antioxidant-rich plants and foods may help reduce Alzheimer's disease by preventing or neutralizing the harmful effects of free radicals [ 19 ]. An extensive study on the therapeutic benefits of antioxidants in treating Alzheimer's disease has shown promising findings. Gallic acid (GA) and other polyphenols have been demonstrated to enhance cognitive functioning in elderly rats and prevent learning and memory losses following intracerebroventricular (ICV) infusion [ 20 ]. The computational screening approach has recently significantly improved the effectiveness of the present drug development process [ 21 ]. In the modern day, it is frequently employed to speed up the drawn-out and expensive processes involved in drug discovery and design, from identifying potential targets typically receptors or enzymes to creating and refining novel compounds with drug-like properties [ 22 ]. Therefore, every computational chemistry technique can influence and expedite a specific stage of the drug discovery process. These techniques range from quantitative structure-activity relationship (QSAR) to molecular docking, which simulates molecular interaction and generates potent inhibitory ability, or binding affinity [ 22 ]. The current study was designed to investigate some phenolic compounds of plant origin and evaluate their inhibitory potential against AChE using molecular docking and molecular dynamics techniques, which may be a possible remedy for neurodegenerative disease. 2.0 Materials and methods 2.1 In silico studies Thirty-eight phenolic compounds of plant origin were selected based on their therapeutic properties [ 23 , 24 ] and then retrieved from the PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ) (Table 1 ). Their 3D structures were prepared and docked against human acetylcholinesterase (hAChE) protein (PDB ID: 6O4W, resolution: 2.35 Å, wild type) in complex with donepezil to evaluate the phenolic compounds' complementarities and binding affinities,. Maestro molecular docking software from the Schrödinger suite (version 12.7) was used for the docking studies. Table 1 Phenolic cmpounds whose 3D structures were docked with acetylcholinesterase [ 23 , 24 ] S/N Name S/N Name S/N Name S/N Name 1 Coumarin 11 p -Hydroxybenzoic acid 21 Naringenin 31 Isorhamnetin 2 Catechin 12 Gallic acid 22 Glycitein 32 Myricetin 3 Gentisic acid 13 Caffeic acid 23 Naringenin chalcone 33 3- o -Caffeoylquinic acid 4 Protocatechuic acid 14 Ferulic acid 24 Genistein 34 Rosmarinio acid 5 p -Coumaric acid 15 Syringic acid 25 Kaempferol 35 Rutin 6 Epicatechin 16 Piperic acid 26 Luteolin 36 4- o -Methyl-epi-gallocatechin 7 Vanillic acid 17 Sinapinic acid 27 Capsaicin 37 Phenyl-6- o -Malonyl-beta-d-glucoside 8 o -Coumaric acid 18 Daidzein 28 Epigallocatechin 38 Epi-gallocatechin-3- o -gallate 9 Eugenol 19 Coumestrol 29 Ellagic acid 10 Isoeugenol 20 Apigenin 30 Quercetin 2.1.1 Protein preparation The hAChE (PDB ID: 6O4W) was downloaded from the Protein Data Bank ( https://www.rcsb.org ) and imported into the Maestro workspace. The highly solvated protein was prepared with the protein preparation wizard, keeping most default settings [ 25 , 26 ]. Considering the importance of water molecules during the acetylcholine hydrolysis [ 27 ], only the water molecules beyond 3 Å from the het groups were removed during the preprocessing stage, after which all the non-protein het groups were deleted, leaving only the bound donepezil ligand. The reliability of the binding affinity prediction has been reported to increase when these water molecules cannot form all possible H-bonds are removed [ 28 ]. The H-bond was optimized, and the orientations of the water molecules were sampled using PROPKA at pH 7.0 [ 29 ], followed by the application of restrained minimization using OPLS4 to freely minimize hydrogen atoms while giving room for heavy atom movement within a root mean square deviation (RMSD) of 0.3 Å to relax any strained geometry [ 30 ]. 2.1.2 Ligand preparation The structures of the standard inhibitor donepezil, and the 38 phenolic compounds were drawn with Maestro's 2D sketcher, converted to 3D structures upon saving and subsequently prepared using the LigPrep module from the Maestro software [ 31 ]. The possible ionization states of the compounds were generated using Epik as the p Ka predictor at pH 7.0 ± 2.0 [ 32 ]. No tautomers were generated from the compounds, and the specified chiralities from the 3D structures were retained. The ligands were subsequently minimized using the OPLS4 force field [ 33 ]. 2.1.3 Receptor grid generation The 20 Å deep gorge of the hAChE, which contained the bound donepezil crystal, was used to generate the receptor grid for the docking studies using the OPLS4 force field. The grid generation with the excluded cognate ligand (donepezil) allows a confined binding space within the active site for the various ligand poses. The default parameters were kept, like the van der Waals scaling factor of 1.0 and the partial charge cutoff of 0.25. An enclosing box of dimension 10 Å × 10 Å × 10 Å containing the centroid of the donepezil ligand was generated, and this defines the confined space for the docked ligands. No constraint was specified for the interactions of the ligands within the receptor; likewise, no volume was excluded. The catalytic triad at the bottom of the binding gorge consists of Ser200, the protonated glutamic acid Glu202, and His447. Other residues within the Peripheral Anionic Site (PAS) and the Catalytic Anionic Site (CAS) include Tyr72, Trp86, Tyr124, Trp286, and Phe338. 2.1.4 Non-covalent docking of the phenolic compounds and donepezil against hAChE The generated receptor grid was retrieved and loaded onto the ligand docking panel, and the prepared ligands were chosen from the project table. The extra precision (XP) scoring function was applied with the ligands docked in flexible states. At same time, keeping the protein at a "rigid" position. During the docking procedure, the ring conformations and nitrogen inversions were sampled while the Epik state penalty was applied to check if any ligand showed the highest binding affinity in an unfavourable protonation state. With the XP scoring function, the XP descriptor information was marked to allow the post-visualization of the docking interactions for further rational optimization. No torsional bias sampling was set for any predefined functional group, and nonplanar conformations were not penalized. Different poses per ligand were sampled, but only the best pose was reported for the output. In addition, post-docking minimisation was also engaged. 2.1.5 MM-GBSA re-docking of the ligands against hAChE The binding energies of the docked ligands were reassessed according to the combined Molecular Mechanics with Generalized Born and Surface Area (MM-GBSA) scoring function. The docked Post Viewer file from the previous receptor-ligands complex was loaded onto the Prime MM-GBSA panel. The variable-dielectric generalized Born continuum solvation model (VSBG), which uses water as the solvent, was chosen with OPLS4 as the force field. The flexibility of the protein residues within the binding site was changed to cover a distance of 5.0 Å from the ligands. The binding affinities of the ligands were ranked, compared, and analyzed for further rational optimization. 2.1.6 Molecular Dynamic simulations: finding the stability of the protein-ligand complex The non-covalent docking parameters assume a structural rigidity of the protein with a flexible ligand. On the contrary, the protein and the ligand continually change shape during their interactions. It is, therefore, necessary to check the stability of the protein-ligand complexes. This was done using Desmond's Molecular Dynamic Simulations of the Schrodinger suite. MM-GBSA docked donepezil, myricetin, and the modified myricetin ligands B-1 , A-2 , and C-3 in complex with hAChE enzyme were used, at the same time, stability was determined by monitoring the potential energy of the system and the root mean square deviation (RMSD) of each protein-ligand complex. The system for the molecular dynamic simulations was set up using the System Builder in Desmond. The solvation of the complex was achieved using the predefined TIP3P explicit water model within an orthorhombic box using the OPLS4 force field. The required number of sodium and chloride ions were added to neutralize the system, and no volume within the ligand's surroundings was excluded for the salt and ion placements. The built system was simulated for 20 ns while the trajectory was recorded at every 20 ps. The normal temperature and pressure (NPT) ensemble class was chosen at 300 K and 1.01325 bar, respectively, and the model was relaxed before the simulation to minimize the water molecules. The analyses of the various interactions were done using the Simulation Interaction Diagram (SID). 2.2 Analysis of ADME-Tox and drug-likeness Admetsar3 ( https://lmmd.ecust.edu.cn/admetsar3/ ) and Swissadme ( http://www.swissadme.ch/ ) were used to perform ligand-based investigations of the selected phytochemicals to identify the molecule that would qualify as potential hits to reduce viral pathogenesis. The pharmacokinetics and drug-likeness of these compounds were screened using a variety of metrics and guidelines [ 34 ]. The drug-likeness parameter was used to predict the route of administration of a drug candidate based on its bioavailability[ 35 ]. Toxicology risk prediction can show potential adverse effects of phenolic chemicals, facilitating rational medicine design. Predicting the hazardous effects of chemicals, including mutagenic, tumorigenic, irritating, and reproductive impacts, is crucial for drug development from laboratory to clinical application [ 35 ]. 3.0 Results and Discussion 3.1 Reliability of the non-covalent docking procedure The reliability of the non-covalent docking procedure applied during the in silico studies was validated by re-docking the donepezil ligand into the hAChE enzyme. The conformation with the protonated N -benzylpiperidine moiety with the lowest docking score was the most likely binding mode. The RMSD of the donepezil ligands was calculated and was found to be 0.54 Å which falls within 2.0 Å maximum allowed deviation, and therefore the docking procedure was considered valid [ 36 ]. Considering the superposition using the maximum common structure between the two ligands, the indanone moiety of the ligands perfectly aligned, deviation was found within the N -benzylpiperidine rings with the chair conformations of the piperidine rings clearly displaying more deviations (Fig. 1 ). As expected, the two bulky groups (the indanone and the phenyl) on the piperidine chair conformation occupied equatorial positions [ 37 ]. The only difference that caused the deviation was the directions of the indanone and the phenyl groups on the bridging carbons to the piperidine linker. 3.2 Non-covalent docking of the phenolic compounds and donepezil against hAChE The binding pose of the co-crystallized donepezil in the active gorge of hAChE enzyme showed the crystal near the catalytic triad, which could be important in preventing acetylcholine from getting in contact with the catalytic Ser203, thereby inhibiting the hydrolysis of acetylcholine [ 38 ]. Five notable interactions were observed when the 3D molecular interactions of donepezil within the binding pocket of the enzyme were analyzed. The protonated nitrogen of the piperidine ring simultaneously displayed two π-cation interactions with the benzene ring of Tyr337 (distance 4.19 Å) and the pyrrole ring of the CAS residue Trp86 (distance 5.28 Å). Additional two π-π stacking interactions could be observed between the benzene ring of the N -benzylpiperidine moiety of donepezil and the indole ring of the CAS Trp86 residue; one to the pyrrole ring of the indole backbone (distance 4.36 Å) and the other to the benzene ring (distance 3.72 Å). The carbonyl group of the indanone moiety of donepezil showed hydrophobically packed hydrogen bond interaction with the nitrogen atom of Phe295 backbone (distance 2.00 Å). This type of interaction is critical in maintaining ligand stability within the protein's binding pocket. In addition to being a hydrogen bond interaction, the hydrophobic location makes it very difficult to break, thereby maintaining stability during the protein movement. Lastly, the benzene ring of the indanone moiety also showed a π-π stacking interaction with the benzene ring of Trp286 PAS residue (distance 3.81 Å). Most of these interactions are in agreement with earlier reports [ 39 , 40 ]. Both the GlideScore (GScore) and the DockScore in kcal/mol for the docked ligands are shown in Table 2 . Table 2 GlideScore (GScore) and the DockScore in kcal/mol for the docked ligands S/N Ligand Compound CID XP GScore kcal/mol DockScore kcal/mol MMGBSA dG Bind (kcal/mol) 1 Donepezil (3152) -16.4 -16.4 -91.4 2 Myricetin (5281672) -14.0 -14.0 -75.8 3 Quercetin (5280343) -13.5 -13.4 -66.0 4 Epigallocatechin (72277) -12.0 -12.0 -55.0 5 Epicatechin (72276) -11.7 -11.7 -54.7 6 Catechin (9064) -11.7 -11.7 -54.7 7 Luteolin (5280445) -11.6 -11.5 -50.8 8 Isorhamnetin (5281654) -11.4 -11.4 -58.8 9 Rosmarinic acid (5281792) -11.2 -11.2 -54.6 10 Kaempferol (5280863) -11.2 -11.2 -56.1 11 Apigenin (5280443) -11.0 -11.0 -53.2 12 Naringenin chalcone (5280960) -11.4 -10.8 -28.3 13 Rutin (5280805) -10.8 -10.7 -64.5 14 Naringenin (439246) -10.7 -10.7 -45.3 15 4-o-Methyl epigallocatechin (163184613) -10.6 -10.6 -67.2 16 Genistein (5280961) -11.6 -9.7 -22.6 17 Daidzein (5281708) -9.4 -9.4 -51.6 18 Ellagic acid (5281855) -9.4 -9.4 -73.5 19 Glycitein (5317750) -9.3 -9.3 -61.5 20 Coumestrol (5281707) -8.9 -8.9 -53.5 21 3- o -Caffeoylquinic acid (1794427) -8.8 -8.8 -26.9 22 Capsaicin (1548943) -8.2 -8.2 -61.6 23 Epigallocatechin-3- o- Gallate (65064) -8.2 -8.1 -74.9 24 Caffeic acid (689043) -7.9 -7.9 -24.9 25 Coumarin (323) -7.5 -7.5 -39.1 26 Gallic Acid (370) -7.0 -7.0 -23.8 27 o -Coumaric Acid (637540) -6.9 -6.9 -24.0 28 Piperic acid (5370536) -6.7 -6.7 -40.7 29 Phenyl-6-O-malonyl-beta-D-glucoside (128708) -6.4 -6.4 -48.5 30 Eugenol (3314) -6.4 -6.4 -37.8 31 Sinapinic acid (637775) -6.2 -6.2 -24.7 32 Ferulic acid (445858) -6.2 -6.2 -23.9 33 Protocatechuic Acid (72) -5.9 -5.9 -27.1 34 Isoeugenol (853433) -5.8 -5.8 -44.6 35 p -Coumaric Acid (637542) -5.4 -5.4 -16.4 36 p -Hydroxybenzoic Acid (135) -5.4 -5.4 -11.0 37 Gentisic Acid (3469) -5.3 -5.3 -21.9 38 Syringic acid (10742) -5.2 -5.2 -17.9 39 Vanillic Acid (8468) -5.1 -5.1 -12.4 The docked ionization state with the lowest binding energy was taken as the most probable binding pose and, therefore, only reported in all the ligands. The observed differences between the GScore and the DockScore were due to Epik state penalties applied to a ligand that shows the lowest binding energy in an unfavourable ionization state. Donepezil showed the lowest binding energy at -16.4 kcal/mol and many of the docked phenolic ligands displayed comparable energies to donepezil (Table 2 ). Most binding energy contributions from all the ligands, including donepezil, generally come from their lipophilic interactions. The binding site contains a lot of lipophilic residues interacting with the lipophilic rings of the ligands. Myricetin, quercetin, epigallocatechin, epicatechin, and catechin showed binding energies of -14.0, -13.5, -12.0, -11.7, and − 11.7 kcal/mol, respectively. Interestingly, all of these ligands showed more hydrogen bond interactions than donepezil. This is aided by the presence of several hydroxyl groups on their molecules. Myricetin, for example, has an H-bond pair reward of -5.4 kcal/mol, while donepezil has − 1.3 kcal/mol. The 3D interactions of myricetin within the binding gorge revealed two π-π stacking interactions between the benzene ring of Trp286 and the benzene ring of the chromenone moiety (distance 3.99 Å) and the pyranone ring (distance 4.37 Å) (Fig. 2 ). The 7-OH group of the chromenone moiety displayed two water-bridged H-bond with NH of Tyr75 and the phenolic OH of Tyr72. The NH of Phe295 also showed hydrophobically packed H-bond interaction with 3-OH group of the chromenone moiety (distance 2.00 Å). As mentioned earlier, this type of H-bond interaction is essential in maintaining ligand stability within the binding pocket. Other interactions within the binding pocket involve H-bond interactions with two water molecules (Fig. 3). Due to their structural similarity, myricetin and quercetin had similar binding energies and interactions. The binding poses of (a) epigallocatechin (b) epicatechin (c) catechin and (d) luteolin showing non-covalent interactions within the binding site of hAChE enzyme are also shown in Fig. 4 . 3.3 MM-GBSA-based re-docking of the ligands against hAChE According to Hubbard and coworkers, better scoring and pose generation functions could be obtained from MM-GBSA than from a non-covalent docking mode [ 41 ]. This is because MM-GBSA gives more accurate results, and its efficiency has been proven in many studies [ 42 , 43 ]. As a result, the ligands were docked in MM-GBSA mode to evaluate their binding free energies and poses with the flexibility of the protein residues restricted within 5 Å from the ligand. The result is presented in Table 2 above. Analysis of the MM-GBSA results shows the preservation of some interactions initially identified by the non-covalent docking. Among these, the π-π stacking interactions between the benzene ring of PAS Trp286 and the benzene ring of the chromenone moiety of myricetin were fully preserved but at a closer distance of 3.71 Å, instead of the original 3.99 Å. Likewise, MM-GBSA indicated H-bond interaction between 3-OH of the pyranone ring and the NH of Phe295 at a distance of 1.96 Å. One partially preserved interaction is the water-bridged H-bond interaction between 7-OH of the chromenone ring and the OH group of Thr75 side chain instead of the original NH of its amino group. In addition to the preserved interactions, MM-GBSA identified new vital interactions of myricetin within the binding gorge of hAChE enzyme. The isolated benzene ring of myricetin showed two separate π-π stacking interactions with the benzene rings of Tyr337 and Tyr341 at 5.37 Å and 4.01 Å respectively. The 7-OH group of the chromenone moiety displayed a water-bridged H-bond interaction with the OH group of Asp74, and 5’-OH of the myricetin's isolated benzene ring showed an H-bond interaction with the phenolic OH of PAS Try124. Other H-bond interactions involved the 5-OH of the chromenone moiety and C = O of Ser293 in a water-bridged interaction, and the C = O of the pyranone moiety showed two H-bond interactions with NH of Arg296 (distance 2.54 Å) and NH of Phe295 (distance 2.58 Å). Figure 5 shows the superimposed structures of myricetin from the non-covalent docking (green) and the MM-GBSA (light grey) studies. The positions of the substructures were preserved, but MM-GBSA was able to move the ligand closer to the PAS residues. The high binding affinity shown by myricetin in this study agrees with several previous reports on myricetin's role in treating AD [ 44 – 47 ]. 3.4 Structural modification of myricetin for binding affinity optimisation Myricetin, the ligand with the highest binding affinity, was modified to increase its geometric and electronic complementarities. The chemical modification was done using the carbonyl oxygen of the pyranone ring to form Schiff bases with different amino group-containing compounds. The Custom R-Group Enumeration panel of the Schrödinger suite was used to generate 333 ligands using 38 aliphatic monocyclic rings and 73 aromatic monocyclic rings as R-substituents to give the hydrazides A , the hydrazines B , and the imines C as shown in Table 3 . The ligands were prepared as described previously, and the non-covalent docking was repeated with MM-GBSA analysis. DockScore filtering was applied to enrich the dataset with ligands having a minimum DockScore of -13.9 kcal/mol (using myricetin as the standard). A total of 30 ligands were obtained, and the top 5 ligands are shown in Table 3 . Table 3 The GScore, DockScore and MM-GBSA values for the top 5 modified myricetin As mentioned earlier, 30 ligands showed higher binding affinities than myricetin after the structural modifications, and from these, ligands B-1 , A-2 , C-3 , and C-4 displayed higher DockScores than donepezil. Using ligand B-1 containing an azetidine substituent as an example, the significant gains over the original myricetin come from lipophilic reward (32%), electrostatic reward (111%), and the electrostatic complementarity for having ligand atoms in a favourable electrostatic environment of the protein (300%). From the frequency of occurrence of the ligands, imine and hydrazine-containing compounds ( B and C , respectively) showed better binding affinities than the hydrazides A . This could be due to a reduced interaction from the highly polar hydrazides, as the binding site analysis of the AChE binding gorge showed a highly hydrophobic environment [ 48 , 49 ]. 3.5 Molecular Dynamic simulations: interaction stability of the protein-ligand complex The room-mean-square deviation (RMSD) for all the protein-ligand complexes was calculated for every frame in the trajectory. This was done to determine the average displacement of all the atoms for a specific frame compared to a reference frame. The RMSD for frame x is given by: $$\:RMSDₓ=\:\sqrt{\frac{1}{N}\sum\:_{i=1}^{N}\left({r}_{i}^{{\prime\:}}\left({t}_{x}\right)-{r}_{i}\:\left({t}_{ref}\right)\right)²}$$ Where N gives the number of atoms in the atom selection, t is the reference time and r' is the post-superimposed position of the selected atoms in frame x with respect to the reference frame, while frame x is recorded at time t x . The procedure is repeated for every frame in the simulation trajectory [ 30 ]. The RMSD of the protein-ligand complex for donepezil, myricetin, and modified myricetins B-1 , A-2 and C-3 are shown in Figs. 6 a, b, c, d, and e, respectively. In the donepezil complex, both the protein and the ligand showed equilibration at around 12 ns, and no apparent divergence was observed till the end of the 20 ns simulation time. The protein showed a lower RMSD value than the donepezil ligand, but the fluctuational changes in the two cases were in the order of ~ 1Å. Comparing myricetin and its derivatives, the most stable ligand is hydrazine B-1 followed by hydrazide A-2 and then imine C-3 , while myricetin showed some levels of divergence towards the end of the simulation. This result agrees with their dock scores and MM-GBSA values. Ligand B-1 achieved the equilibration point at approximately 5 ns, and this was maintained throughout the simulation time. In all the cases, including the donepezil complex, hAChE protein has RMSD values below 1.8 Å while ligands B-1 and A-2 have RMSD values below 3.0 Å and 2.4 Å, respectively, after they attained the equilibration. In contrast, both myricetin and C-3 showed RMSD values above 5 Å. Molecular dynamics studies show the significant binding interactions between donepezil, myricetin, and the myricetin derivatives with the highest MM-GBSA scores. The protein-ligand contacts are shown in Fig. 7 . As expected, the amino groups of the azetidine substituent on B-1 and A-2 and that of the piperazine substituent on C-3 displayed the most important interactions. Ligand B-1 formed a new water-bridged interaction between Gln71 and its protonated amino group of azetidine moiety. At the same time, there was no change in the frequency of interaction with Tyr72 except for the increase in the percentage of water-bridged interaction in B-1 with the accompanying decrease in H-bond interaction compared to myricetin. The interaction of myricetin with Tyr72 was coming from the 5’-OH group of the phenyl moiety at 41% of the simulation time. However, in ligand B-1 , the formation of the hydrazine group causes a change in the binding pose, resulting in a water-bridged interaction between Tyr72 and the protonated amino group of the azetidine group. The significant gain for ligands B-1 , A-2 , and C-3 came from different interactions with Asp74, with ligand B-1 having the highest interactions with this residue, as shown in the 2D interactions diagram in Fig. 8 (close attention should be paid to the scale of the y-axis). The interactions include different H-bonds, Pi-cation interactions, and water-bridged H-bond interactions. The interaction of the modified ligands with Thr83 disappeared in B-1 and was almost insignificant in C-3 but was maintained in A-2 . All the modified ligands showed an increased frequency of interactions with Trp86. The frequency of interaction with Asn87 only decreased in B-1 , saw an increase in A-2 , and was maintained in C-3 . Additional interactions in the modified myricetins, especially ligands B-1 and A-2 , involved Ser125, Glu202, Phe297, Phe338, Gly372, and His447 compared to myricetin. All these could explain the increased DockScore and the stability of the modified ligands. 3.6 ADME-Tox profiling and drug-likeness Before a medicine can be approved, it must be screened for pharmacokinetic properties and drug-likeness potential [ 50 ]. Several guidelines have been proposed to assess if a drug candidate would be orally bioavailable, depending on the pharmacological class. Lipinski's rule is a widely used standard for determining a compound's bioavailability in small-molecule inhibitors [ 51 ]. According to Lipinski and colleagues' careful analysis of orally active drugs, a potential drug candidate with an oral route of administration should not violate more than one of the following criteria: molecular weight less than 500 Da; the number of hydrogen bond donors ≤ 5; the number of hydrogen bond acceptors ≤ 10; and octanol-water partition co-efficient ≤ 5 [ 52 ]. Molecules with poor absorption and low permeability characteristics are considered poor inhibitors, especially if they violate more than one of these conditions [ 34 ]. The results of this investigation, as given in Table 4 , suggest that Quercetin and Epicatechin have the potential to be outstanding drug-like molecules since they do not violate any of Lipinski's principles. However, Myricetin its modified analogues (Table 6 ) and Epigallocatechin only violated one rule with more than the required number of hydrogen bond donors. As a result, there is a good possibility that any of these compounds may act as promising candidates for drug development. High-throughput screening tests of several pharmacokinetic parameters are undertaken early in drug development; computational-based ADME-Tox predictions are currently enhancing this labour-intensive and capital-intensive effort. In silico ADME-Tox prediction analyses drug candidates' probable distribution and pharmacokinetics within a single global model. This prediction shows if the candidate will be suitable for drug development in the future, avoiding late-stage attrition and clinical development costs. MetStabOn [ 53 ], admetSAR [ 54 ], ADMETlab [ 55 ], and CypReact[ 56 ] have all been shown to be highly effective in predicting drug candidates’ pharmacokinetic and toxicological endpoints. Early screening for pharmacokinetic and pharmacodynamic features is increasingly being used to prevent undesired qualities from delaying the advancement of a drug candidate into the clinic. To that end, the top four phenolic compounds and myricetin analogues were subjected to the admetSAR analysis to determine their future potential as drug candidates. Tables 5 and 7 present our results of pharmacokinetic predictions of Quercetin, Myricetin, Epigallocatechin, Epicatechin, the standard drug (donepezil) and myricetin analogues. For the prediction of absorption and distribution features of our drug candidates, we identified human intestinal absorption (HIA), P-glycoprotein substrate, and penetration through the blood-brain barrier (BBB) (Tables 5 & 7 ). The selected compounds' and myricetin analogues in Tables 5 & 7 depict positive HIA values, including the standard, may suggest that they are easily absorbed in the gut following ingestion. In the distribution section, Quercetin, Myricetin, Epicatechin, and Epigallocatechin exhibit negative BBB test results, indicating that they cannot cross the blood-brain barrier and thereby protect the central nervous system. However, the standard drug (donepezil) and myricetin analogues has strong correlation showing a positive score for BBB, indicating that it has a more significant dispersion and may have a neurological impact. Quercetin, Myricetin, Epicatechin, and Epigallocatechin were also predicted to be non-substrates of P-glycoprotein. This implies that these substances may have favourable distribution characteristics. However, the standard drug (donepezil) and the myricetin analogues may act as a P-glycoprotein inhibitors, limiting its distribution by P-glycoprotein efflux mediation [ 57 ]. The Cyp450 families have been recognized as a key pharmacological parameter in metabolism. Inhibition of these protein families, according to Lynch, may result in drug-drug interactions and bioaccumulation [ 58 ]. According to our results, Quercetin and Myricetin inhibit one or more of these metabolic enzymes, while Myricetin analogues exhibit minimal or no inhibition of metabolic enzymes. It is crucial to note that non-acceptable toxicological profiles are important reasons for drugs' failure to pass clinical trials; hence we have included Ames mutagenicity, acute oral toxicity, hERG inhibition, and carcinogenicity tests in this study (Tables 5 & 7 ). The carcinogenicity test results for all compounds including the myricetin analogues and the standard drug are negative, which clarifies why they are not carcinogenic. The hERG and Ames mutagenicity are important pharmacological indicators for determining if a drug-like substance is capable of causing cardiac arrhythmia[ 59 ] and mutating DNA. The standard drug (donepezil) and Myricetin excel in the Ames mutagenicity test. However, Quercetin, Epigallocatechin, Epicatechin, and Myricetin analogues show positive Ames test results, suggesting they may have the potential to modify DNA. The standard drug (donepezil), which has a positive hERG test result, may influence the heart's potassium channel rhythm (cardiac arrhythmia). In contrast, the other compounds including myricetin analogues have negative values for the hERG test. Table 4 Lipinski's character of donepezil and the top four ligands from the DockScore Ligand Molecular weight LogP nHBA nHBD nViolation Donepezil 379.21 3.245 4 0 0 Myricetin 318.04 1.115 8 6 1 Quercetin 302.04 1.448 7 5 0 Epigallocatechin 306.07 0.794 7 6 1 Epicatechin 290.08 1.094 6 5 0 Note: LogP: Octanol-water partition coefficient; nHBD: number of hydrogen bond donors; nHBA: number of hydrogen bond acceptors; nViolation: number of Violation. Table 5 Prediction of the toxicity profiles of donepezil and the top four compounds from the molecular docking Parameters/Ligands Donepezil Myricetin Quercetin Epigallocatechin Epicatechin Blood brain barrier (+/-) +(0.9250) − (0.7750) − (0.7750) − (0.6750) − (0.6750) Human intestinal absorption (+/-) +(0.9838) +(0.9071) +(0.9071) +(0.8922) +(0.8922) p-gp inhibitor (+/-) +(0.8860) − (0.9166) − (0.9191) − (0.9207) − (0.9411) LogS (+/-) − (2.425) − (2.999) − (2.999) − (3.101) − (3.101) Human oral Bioavailability (+/-) − (0.7857) − (0.5143) − (0.5429) − (0.7000) − (0.7857) Caco-2 +(0.6843) − (0.7367) − (0.6417) − (0.9372) − (0.9406) Carcinogenicity − (0.9600) − (1.0000) − (1.0000) − (0.9700) − (0.9700) Ames mutagenicity − (0.5800) − (0.5800) +(0.8410) +(0.6100) +(0.6000) Acute oral toxicity III (0.5250) II (0.7348) II (0.7348) IV (0.6433) IV (0.6433) Human either - a -go -go inhibition +(0.9520) − (0.7812) − (0.8410) − (0.4416) − (0.4678) Hepatotoxicity +(0.8677) +(0.6625) +(0.9025) +(0.6427) − (0.7375) CYP2C19 Inhibitor (+/-) − (0.8356) − (0.9025) − (0.5823) − (0.9041) − (0.9041) CYP1A2 Inhibitor (+/-) +(0.5072) +(0.9106) +(0.9106) − (0.9046) − (0.9046) CYP3A4 Inhibitor (+/-) − (0.7411) +(0.6951) +(0.6951) − (0.8309) − (0.8309) CYP2C9 Inhibitor (+/-) − (0.8189) − (0.5823) − (0.5823) − (0.9071) − (0.9071) CYP2D6 Inhibitor (+/-) +(0.8684) − (0.8553) − (0.9287) − (0.9231) − (0.9231) Table 6 Lipinski's character of the five modified analogues of Myricetin from the DockScore Ligand Molecular weight LogP nHBA nHBD nViolation B-1 371.11 -0.218 9.0 7.0 1 A-2 399.11 0.168 10 7.0 1 C-3 385.13 -0.333 9.0 7.0 1 C-4 384.13 0.327 8.0 6.0 1 B-5 385.13 -0.201 9.0 7.0 1 Note: LogP: Octanol-water partition coefficient; nHBD: number of hydrogen bond donors; nHBA: number of hydrogen bond acceptors; nViolation: number of Violation. Table 7 Prediction of the toxicity profiles of modified analogues of Myricetin from the molecular docking Parameters/Ligands B-1 A-2 C-3 C-4 B-5 Blood brain barrier (+/-) +(0.0020) +(0.0000) +(0.0000) +(0.0230) +(0.0020) Human intestinal absorption (+/-) +(0.0070) +(0.0180) +(0.0750) +(0.0000) +(0.0020) p-gp inhibitor (+/-) +(0.0000) +(0.0000) +(0.0070) +(0.0020) +(0.0060) LogS (+/-) − (2.5760) − (2.9420) − (2 .9720) − (2.6620) − (2.5480) Caco-2 − (6.1220) − (6.1430) − (6.1360) − (6.0800) − (6.1300) Carcinogenicity − (0.4860) − (0.4880) − (0.1740) − (0.1460) − (0.5860) Ames mutagenicity +(0.8070) +(0.8240) +(0.7540) +(0.7700) +(0.8250) Human either - a -go -go inhibition − (0.349) − (0.098) − (0.249) − (0.318) − (0.307) Hepatotoxicity +(0.8270) +(0.7360) +(0.9030) +(0.9030) +(0.8440) CYP2C19 Inhibitor (+/-) − (0.0000) − (0.0000) − (0.0000) − (0.0000) − (0.0000) CYP1A2 Inhibitor (+/-) +(0.0060) − (0.0290) − (0.6640) − (0.0680) − (0.0860) CYP3A4 Inhibitor (+/-) − (0.8230) − (0.9740) − (0.9580) +(0.9400) − (0.9920) CYP2C9 Inhibitor (+/-) − (0.0000) − (0.0070) − (0.0040) − (0.0000) − (0.0010) CYP2D6 Inhibitor (+/-) − (0.0000) − (0.0000) − (0.0010) − (0.0000) − (0.0000) 3.7 Limitation of the study The findings presented in this study are derived solely from computational (In silico) experiments. Additionally, in vivo and in vitro laboratory tests are required to validate the outcomes reported here. As this study is predictive, the results should be interpreted with appropriate caution. Also, While we recognize that longer simulations could provide more comprehensive insights, the current analysis provides valuable preliminary insights into the protein-ligand dynamics and interaction stability. Future studies can explore this system further with extended simulations when computational resources become available. 4.0 Conclusion In this study, thirty-eight plant-based phenolic compounds were retrieved from the PubChem database. These compounds, in addition to the cognate donepezil, were virtually screened against Acetylcholinesterase. The results of the virtual screening showed that myricetin, quercetin, epigallocatechin, and epicatechin displayed the highest binding affinities, though lower than donepezil. The molecular modification of myricetin was done by Schiff base formation using custom R group enumeration of the Schrödinger suite to give different hydrazides A , hydrazines B , and imines C , which were subsequently subjected to different virtual screenings. Four of these ligands from the three molecular classes showed better binding affinities than donepezil, in addition to the better stability of their protein-ligand complexes. The result of the molecular dynamics simulation agrees with the docking scores and the MM-GBSA values. From these, various molecular interactions were observed, which include hydrogen bondings, π- π stacking, π-cation, and more importantly, hydrophobically packed H-bonding, which is essential in maintaining ligand stability within a binding pocket. From the results of the molecular docking, the top four phenolics with the highest binding affinities (myricetin, quercetin, epigallocatechin, and epicatechin) including myricetin analogues derivatives were subjected to ADMET properties prediction and drug-likeness calculation using the Lipinski rule of five (Ro5). The favourable predicted results show these compounds could be further developed into potential drug candidates. However, highly powerful phenolic compounds also face hurdles such as poor bioavailability, labile structures, toxicity concerns, and lack of clinical data. Overcoming these challenges necessitates advanced drug delivery platforms, structural optimization, uniform formulation and robust clinical trials. The integration of nanotechnology, artificial intelligence, omics, sustainable production practices, and regulatory support will enable the effective promotion as well as clinical translation of phenolics. Declarations Acknowledgements The authors would like to thank the Centre for High Performance Computing (CHPC, Cape Town, South Africa) for access to the CHPC Lengau Cluster and Schrödinger molecular docking software. Ethical approval and consent to participate Not applicable. Consent for publication Not applicable. Competing Interest On behalf of all authors, the corresponding author states that there is no conflict of interest. Clinical trial number Not applicable. Authors' contributions M.A. Ashiru and R.A. Adigun: Conceptualization, investigation, methodology, validation, visualization, writing-original draft preparation, writing review, and editing. M.O. Babalola, S.O.Ogunyemi, I.O. Junaid, M.T. Bello-Hassan, M.A. Fategbe: Conceptualization, writing review and editing. M.G Baker, K.A Alabi, P.O. Emmanuel, M.O. Balogun: investigation, validation, visualization, writing-original draft preparation and writing review, and editing. Corresponding Author Mojeed Ayoola Ashiru ( [email protected] ) Funding No funding was received for this work. Availability of data and materials “Some of the datasets generated during and/or analysed during the current study are in the manuscript while the rest are available from the corresponding author on reasonable request.” References N.R. Jabir, M.T. Rehman, K. Alsolami, S. Shakil, T.A. Zughaibi, R.F. Alserihi, M.S. Khan, M.F. AlAjmi, S. Tabrez, Concatenation of molecular docking and molecular simulation of BACE-1, γ-secretase targeted ligands: in pursuit of Alzheimer’s treatment, Ann Med 53 (2021) 2332–2344. https://doi.org/10.1080/07853890.2021.2009124. Alzheimer’s disease facts and figures, Alzheimer’s and Dementia 20 (2024) 3708–3821. https://doi.org/10.1002/alz.13809. A. Association, 2022 Alzheimer’s disease facts and figures, Alzheimer’s & Dementia 18 (2022) 700–789. https://doi.org/10.1002/alz.12638. N.R. Jabir, S. Shakil, S. Tabrez, M.S. Khan, M.T. 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Temitope Isaac, Inhibitors of α-glucosidase and Angiotensin-converting Enzyme in the Treatment of Type 2 Diabetes and its Complications: A Review on in Silico Approach, Pharmaceutical and Biomedical Research 8 (2022) 237–258. https://doi.org/10.32598/PBR.8.4.1052.1. M.O. Babalola, M.A. Ashiru, I.D. Boyenle, E.O. Atanda, A.-Q.K. Oyedele, I.Y. Dimeji, O. Awodele, N.A. Imaga, In vitro Analysis and Molecular Docking of Gas Chromatography-Mass Spectroscopy Fingerprints of Polyherbal Mixture Reveals Significant Antidiabetic Miture, Nigerian Journal of Experimental and Clinical Biosciences 10 (2022) 105–115. https://doi.org/10.4103/njecp.njecp_15_22. Additional Declarations No competing interests reported. Supplementary Files floatimage1.jpeg Graphical abstract Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6356281","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449255893,"identity":"b03d6c0c-eadf-462b-a39f-144eba3ba47a","order_by":0,"name":"Mojeed Ayoola Ashiru","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAo0lEQVRIiWNgGAWjYHACNoYEBgY5GJt4LcY8bCRpAYLEHqK16LYff/bg4Z7D6fvlewwYPpQdJqzF7EyOuUHCs8O5PWw8BowzzhGj5UAOm0TCAYgWZt42YrScf/4MpCWdB6TlL1FabiSYgbQkgLUwEqflDUhLumHPsbSCgz3n0olxWPozyR8HrOXZmw9vfPCjzJqwFhRwgET1o2AUjIJRMApwAQDeyDkTfNgLXAAAAABJRU5ErkJggg==","orcid":"","institution":"Texas Tech University","correspondingAuthor":true,"prefix":"","firstName":"Mojeed","middleName":"Ayoola","lastName":"Ashiru","suffix":""},{"id":449255894,"identity":"feac3487-6b09-471e-a270-a72f89f42f17","order_by":1,"name":"Rasheed Adewale Adigun","email":"","orcid":"","institution":"Fountain University","correspondingAuthor":false,"prefix":"","firstName":"Rasheed","middleName":"Adewale","lastName":"Adigun","suffix":""},{"id":449255895,"identity":"286d3fde-31f5-4464-a9cf-d7d342310aab","order_by":2,"name":"Musa Oladayo Babalola","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Musa","middleName":"Oladayo","lastName":"Babalola","suffix":""},{"id":449255896,"identity":"185587c5-07cc-4839-a688-5bb637a7db7c","order_by":3,"name":"Sherif Olabisi Ogunyemi","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Sherif","middleName":"Olabisi","lastName":"Ogunyemi","suffix":""},{"id":449255897,"identity":"4545f93d-2f66-4cf7-b6e2-aa04898d6bb9","order_by":4,"name":"Idris Oladimeji Junaid","email":"","orcid":"","institution":"Stevens Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Idris","middleName":"Oladimeji","lastName":"Junaid","suffix":""},{"id":449255898,"identity":"d6c69edf-16c5-4721-be13-59a9fc97e62f","order_by":5,"name":"Maryam Titilayo Bello-Hassan","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"Titilayo","lastName":"Bello-Hassan","suffix":""},{"id":449255899,"identity":"4a370561-9445-4ba3-961a-208290c9896a","order_by":6,"name":"Mojisola Adebimpe Fategbe","email":"","orcid":"","institution":"Bowen University","correspondingAuthor":false,"prefix":"","firstName":"Mojisola","middleName":"Adebimpe","lastName":"Fategbe","suffix":""},{"id":449255900,"identity":"de3edcf1-f376-48fc-af2b-00264889b7c7","order_by":7,"name":"Myah Grace Baker","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Myah","middleName":"Grace","lastName":"Baker","suffix":""},{"id":449255901,"identity":"2ad11ed5-7acf-451d-98d8-a3d3ce4fec77","order_by":8,"name":"Kazeem Adelani Alabi","email":"","orcid":"","institution":"Fountain University","correspondingAuthor":false,"prefix":"","firstName":"Kazeem","middleName":"Adelani","lastName":"Alabi","suffix":""},{"id":449255902,"identity":"bb2ebf7a-820e-4b74-b3a9-aa838c41f5fc","order_by":9,"name":"Prince Ozioma Emmanuel","email":"","orcid":"","institution":"Texas Tech University","correspondingAuthor":false,"prefix":"","firstName":"Prince","middleName":"Ozioma","lastName":"Emmanuel","suffix":""},{"id":449255903,"identity":"9ad3e65a-5db8-4bf6-9e51-9910a74d46d4","order_by":10,"name":"Mohammed O. Balogun","email":"","orcid":"","institution":"Council for Scientific and Industrial Research","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"O.","lastName":"Balogun","suffix":""}],"badges":[],"createdAt":"2025-04-01 23:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6356281/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6356281/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82137452,"identity":"9cee8118-7b8c-42e7-ae04-dee3e54925f8","added_by":"auto","created_at":"2025-05-07 06:18:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31376,"visible":true,"origin":"","legend":"\u003cp\u003eThe superposition of re-docked donepezil (grey) and the cognate ligand of the enzyme (green)\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/e7fc275710647bb47fb770fe.jpg"},{"id":82137451,"identity":"a2cd6557-8e2c-4003-be31-0dfd4a9d918a","added_by":"auto","created_at":"2025-05-07 06:18:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":56222,"visible":true,"origin":"","legend":"\u003cp\u003eInteractions of myricetin within the binding pocket of hAChE enzyme (PDB ID: 6O4W)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/3e6fb5f4d3a25e133b2244b3.jpg"},{"id":82139177,"identity":"57359378-b4be-4358-bc9f-278525083c94","added_by":"auto","created_at":"2025-05-07 06:26:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":54332,"visible":true,"origin":"","legend":"\u003cp\u003eThe hydrophobically packed H-bond interaction of myricetin\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/aad61b565649e66b2edd8672.jpg"},{"id":82137455,"identity":"6860d0c5-b7f7-4570-9bb9-22d49bfcb46e","added_by":"auto","created_at":"2025-05-07 06:18:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":64836,"visible":true,"origin":"","legend":"\u003cp\u003eBinding poses of (a) epigallocatechin (b) epicatechin (c) catechin and (d) luteolin showing non-covalent interactions within the binding site of hAChE enzyme (PDB ID: 6O4W)\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/0c086b8b325ed22f2eb24eaa.jpg"},{"id":82139178,"identity":"d95dd4c3-f5d7-455d-afc3-ef7d959ae48e","added_by":"auto","created_at":"2025-05-07 06:26:07","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":87484,"visible":true,"origin":"","legend":"\u003cp\u003eMyricetin (\u003cstrong\u003ea\u003c/strong\u003e) re-docked with the MM-GBSA method and the superimposed structures of myricetin (\u003cstrong\u003eb\u003c/strong\u003e) from non-covalent docking (green) and MM-GBSA (light grey) within the binding gorge of hAChE (PBD ID: 6O4W)\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/4770ab714fed587e116d222b.jpg"},{"id":82137465,"identity":"654e5c70-6639-47d4-a54a-2996f22f01c4","added_by":"auto","created_at":"2025-05-07 06:18:07","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":300811,"visible":true,"origin":"","legend":"\u003cp\u003eRMSD of ligand (red) and protein Cα (blue) for (a) donepezil-AChE (b) myricetin-AChE (c) \u003cstrong\u003eB-1\u003c/strong\u003e-AChE (d), \u003cstrong\u003eA-2\u003c/strong\u003e-BuChE (e) \u003cstrong\u003eC-3\u003c/strong\u003e-AChE over 20 ns MD simulation time.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/dd7657383f419d31fde3d35d.jpg"},{"id":82141353,"identity":"f4817138-05b6-40d2-b63a-82bf9b04ff59","added_by":"auto","created_at":"2025-05-07 06:34:07","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":172582,"visible":true,"origin":"","legend":"\u003cp\u003eProtein-ligand contacts monitored during a 20 ns MD simulation at 300 K for the (a) hAChE-myricetin complex, (b) AChE-\u003cstrong\u003eB-1\u003c/strong\u003e complex, (c) AChE-\u003cstrong\u003eA-2\u003c/strong\u003e complex and (d) AChE-\u003cstrong\u003eC-3\u003c/strong\u003e complex. The stacked bar charts of the contacts are normalized to fractions, with values over 1.0 representing protein residues that make multiple contacts with the ligand.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/c807470ff4d8fd17469dc2e2.jpg"},{"id":82141356,"identity":"52efdb8b-0d8f-4e1c-9bb8-a58623f0c015","added_by":"auto","created_at":"2025-05-07 06:34:07","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":135981,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation showing the interactions of ligands (a) myricetin (b) \u003cstrong\u003eB-1\u003c/strong\u003eand (c) \u003cstrong\u003eA-2 \u003c/strong\u003eand (d) \u003cstrong\u003eC-3\u003c/strong\u003e with the surrounding residues of hAChE during a 20 ns MD simulation at 300 K.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/f2ce2de6bfbd7f175fb8c550.jpg"},{"id":83242712,"identity":"1878d99f-3962-44b2-9af3-547ab98be505","added_by":"auto","created_at":"2025-05-21 16:16:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2575855,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/b19fee01-fffb-4af6-9df4-e6e428ee50cf.pdf"},{"id":82141354,"identity":"50ef6b4f-0831-4f59-a4d0-2823ea9d9214","added_by":"auto","created_at":"2025-05-07 06:34:07","extension":"jpeg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":311661,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical abstract\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6356281/v1/b96945b5268154af0894427a.jpeg"}],"financialInterests":"No competing interests reported.","formattedTitle":"Acetylcholinesterase Inhibitory Potential of Plant-Based Phenolics in the Treatment of Alzheimer's Disease: An In Silico Approach","fulltext":[{"header":"1.0 Introduction","content":"\u003cp\u003eDementia is an age-related condition that affects the cognitive brain processes of memory, language, perception, and cognition, making it challenging to sustain everyday tasks [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Alzheimer's disease (AD) is one of the most well-researched forms of dementia. In the USA, AD is the most prevalent form of dementia, accounting for 60\u0026ndash;80 per cent of all cases [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Alzheimer's disease is projected to affect 12.7\u0026nbsp;million people aged 65 years and older by 2050 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Protein misfolding and aggregation, oxidative stress, mitochondrial abnormalities, and neuroinflammatory processes are all hallmarks of Alzheimer's disease (AD) at the molecular level [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Unfortunately, no definite consensus on the causation of Alzheimer's disease exists, although various hypotheses have been proposed. The most prevalent of them is the cholinergic hypothesis, which postulates that a decrease in the amount of the neurotransmitter acetylcholine (ACh) is associated with cognitive decline. In another amyloid hypothesis, AD has been linked with the formation of β-amyloid (Aβ) plaques in the brain [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], which is a distinctive feature of AD. ACh levels in the brain are regulated by the enzyme acetylcholinesterase (AChE, EC number 3.1.1.7), which catalyzes the breakdown of the neurotransmitter ACh. Butyrylcholinesterase (BuChE) also degrades ACh more slowly and to a lesser level [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Interestingly, AChE has also been reported to bind specifically to Aβ and play a crucial role in Aβ plaque formation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA single molecule of AChE breaks down over 20,000 molecules of ACh in one second. The enzyme uses three crucial amino acid residues (glutamine, histidine, and serine) known as the catalytic triad at its 20 \u0026Aring; deep gorge. The hydrophobic aromatic residues along the gorge propel ACh it into the reaction orientation where the oxygen atom on serine binds to the ACh ester's carbonyl carbon. The loosely-bonded hydrogen atom to the serine gets transferred to the AChE oxygen atom, breaking its intramolecular bond, and thereby releasing choline. Serine containing the remaining acetate gets protonated by a water molecule leading to the formation of a new bond between the acetate and the oxygen of the water molecule, releasing acetate in the process. The catalytic triad is restored to its original form, ready to break more Ach [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, by regulating the clearance of ACh, inhibition of AChE has always been an excellent therapeutic approach. The US Food and Drug Administration (US FDA) has approved three AChE inhibitors for Alzheimer's disease: donepezil, rivastigmine, and galantamine [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Tacrine was authorized by the FDA but has subsequently been withdrawn owing to hepatotoxicity concerns [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Despite the numerous treatment options for Alzheimer's disease, interest in plant-based herbal medicine is growing these days due to the lack of complete efficacy and side effects of the approved drugs [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTraditional medicine has been known for using plant-based extracts to treat various diseases, including skin infections, candidiasis, dyspepsia, neurodegenerative disease, cough, and fever [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, as technology and drug discovery have advanced in the last century, this practice has begun to receive renewed attention [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The Food and Drug Administration has approved about 25% of new medications including phytochemicals [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Currently, more than USD 65\u0026nbsp;billion is made annually from the sale of pharmaceuticals derived from plants, with approximately 80% of antibacterial, cardiovascular, immunosuppressive, and anticancer medications being derived from plants [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Nevertheless, 6% and 15% of the estimated 450,000 plant species worldwide have undergone pharmacological and phytochemical screening, respectively [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Thus, many bioactive compounds may have strong physiological effects on several illnesses. For example, antioxidant-rich plants and foods may help reduce Alzheimer's disease by preventing or neutralizing the harmful effects of free radicals [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. An extensive study on the therapeutic benefits of antioxidants in treating Alzheimer's disease has shown promising findings. Gallic acid (GA) and other polyphenols have been demonstrated to enhance cognitive functioning in elderly rats and prevent learning and memory losses following intracerebroventricular (ICV) infusion [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe computational screening approach has recently significantly improved the effectiveness of the present drug development process [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In the modern day, it is frequently employed to speed up the drawn-out and expensive processes involved in drug discovery and design, from identifying potential targets typically receptors or enzymes to creating and refining novel compounds with drug-like properties [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Therefore, every computational chemistry technique can influence and expedite a specific stage of the drug discovery process. These techniques range from quantitative structure-activity relationship (QSAR) to molecular docking, which simulates molecular interaction and generates potent inhibitory ability, or binding affinity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The current study was designed to investigate some phenolic compounds of plant origin and evaluate their inhibitory potential against AChE using molecular docking and molecular dynamics techniques, which may be a possible remedy for neurodegenerative disease.\u003c/p\u003e"},{"header":"2.0 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 In silico studies\u003c/h2\u003e \u003cp\u003eThirty-eight phenolic compounds of plant origin were selected based on their therapeutic properties [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and then retrieved from the PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Their 3D structures were prepared and docked against human acetylcholinesterase (hAChE) protein (PDB ID: 6O4W, resolution: 2.35 \u0026Aring;, wild type) in complex with donepezil to evaluate the phenolic compounds' complementarities and binding affinities,. Maestro molecular docking software from the Schr\u0026ouml;dinger suite (version 12.7) was used for the docking studies.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhenolic cmpounds whose 3D structures were docked with acetylcholinesterase [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoumarin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Hydroxybenzoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNaringenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eIsorhamnetin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGallic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlycitein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMyricetin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentisic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCaffeic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNaringenin chalcone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3-\u003cem\u003eo\u003c/em\u003e-Caffeoylquinic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtocatechuic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFerulic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGenistein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRosmarinio acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Coumaric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSyringic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRutin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEpicatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePiperic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLuteolin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4-\u003cem\u003eo\u003c/em\u003e-Methyl-epi-gallocatechin\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVanillic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSinapinic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCapsaicin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePhenyl-6-\u003cem\u003eo\u003c/em\u003e-Malonyl-beta-d-glucoside\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eo\u003c/em\u003e-Coumaric acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDaidzein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpigallocatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEpi-gallocatechin-3-\u003cem\u003eo\u003c/em\u003e-gallate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEugenol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCoumestrol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEllagic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsoeugenol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eApigenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Protein preparation\u003c/h2\u003e \u003cp\u003eThe hAChE (PDB ID: 6O4W) was downloaded from the Protein Data Bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and imported into the Maestro workspace. The highly solvated protein was prepared with the protein preparation wizard, keeping most default settings [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Considering the importance of water molecules during the acetylcholine hydrolysis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], only the water molecules beyond 3 \u0026Aring; from the het groups were removed during the preprocessing stage, after which all the non-protein het groups were deleted, leaving only the bound donepezil ligand. The reliability of the binding affinity prediction has been reported to increase when these water molecules cannot form all possible H-bonds are removed [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The H-bond was optimized, and the orientations of the water molecules were sampled using PROPKA at pH 7.0 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], followed by the application of restrained minimization using OPLS4 to freely minimize hydrogen atoms while giving room for heavy atom movement within a root mean square deviation (RMSD) of 0.3 \u0026Aring; to relax any strained geometry [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Ligand preparation\u003c/h2\u003e \u003cp\u003eThe structures of the standard inhibitor donepezil, and the 38 phenolic compounds were drawn with Maestro's 2D sketcher, converted to 3D structures upon saving and subsequently prepared using the LigPrep module from the Maestro software [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The possible ionization states of the compounds were generated using Epik as the p\u003cem\u003eKa\u003c/em\u003e predictor at pH 7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. No tautomers were generated from the compounds, and the specified chiralities from the 3D structures were retained. The ligands were subsequently minimized using the OPLS4 force field [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Receptor grid generation\u003c/h2\u003e \u003cp\u003eThe 20 \u0026Aring; deep gorge of the hAChE, which contained the bound donepezil crystal, was used to generate the receptor grid for the docking studies using the OPLS4 force field. The grid generation with the excluded cognate ligand (donepezil) allows a confined binding space within the active site for the various ligand poses. The default parameters were kept, like the van der Waals scaling factor of 1.0 and the partial charge cutoff of 0.25. An enclosing box of dimension 10 \u0026Aring; \u0026times; 10 \u0026Aring; \u0026times; 10 \u0026Aring; containing the centroid of the donepezil ligand was generated, and this defines the confined space for the docked ligands. No constraint was specified for the interactions of the ligands within the receptor; likewise, no volume was excluded. The catalytic triad at the bottom of the binding gorge consists of Ser200, the protonated glutamic acid Glu202, and His447. Other residues within the Peripheral Anionic Site (PAS) and the Catalytic Anionic Site (CAS) include Tyr72, Trp86, Tyr124, Trp286, and Phe338.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.4 Non-covalent docking of the phenolic compounds and donepezil against hAChE\u003c/h2\u003e \u003cp\u003eThe generated receptor grid was retrieved and loaded onto the ligand docking panel, and the prepared ligands were chosen from the project table. The extra precision (XP) scoring function was applied with the ligands docked in flexible states. At same time, keeping the protein at a \"rigid\" position. During the docking procedure, the ring conformations and nitrogen inversions were sampled while the Epik state penalty was applied to check if any ligand showed the highest binding affinity in an unfavourable protonation state. With the XP scoring function, the XP descriptor information was marked to allow the post-visualization of the docking interactions for further rational optimization. No torsional bias sampling was set for any predefined functional group, and nonplanar conformations were not penalized. Different poses per ligand were sampled, but only the best pose was reported for the output. In addition, post-docking minimisation was also engaged.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.1.5 MM-GBSA re-docking of the ligands against hAChE\u003c/h2\u003e \u003cp\u003eThe binding energies of the docked ligands were reassessed according to the combined Molecular Mechanics with Generalized Born and Surface Area (MM-GBSA) scoring function. The docked Post Viewer file from the previous receptor-ligands complex was loaded onto the Prime MM-GBSA panel. The variable-dielectric generalized Born continuum solvation model (VSBG), which uses water as the solvent, was chosen with OPLS4 as the force field. The flexibility of the protein residues within the binding site was changed to cover a distance of 5.0 \u0026Aring; from the ligands. The binding affinities of the ligands were ranked, compared, and analyzed for further rational optimization.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.1.6 Molecular Dynamic simulations: finding the stability of the protein-ligand complex\u003c/h2\u003e \u003cp\u003eThe non-covalent docking parameters assume a structural rigidity of the protein with a flexible ligand. On the contrary, the protein and the ligand continually change shape during their interactions. It is, therefore, necessary to check the stability of the protein-ligand complexes. This was done using Desmond's Molecular Dynamic Simulations of the Schrodinger suite. MM-GBSA docked donepezil, myricetin, and the modified myricetin ligands \u003cb\u003eB-1\u003c/b\u003e, \u003cb\u003eA-2\u003c/b\u003e, and \u003cb\u003eC-3\u003c/b\u003e in complex with hAChE enzyme were used, at the same time, stability was determined by monitoring the potential energy of the system and the root mean square deviation (RMSD) of each protein-ligand complex. The system for the molecular dynamic simulations was set up using the System Builder in Desmond. The solvation of the complex was achieved using the predefined TIP3P explicit water model within an orthorhombic box using the OPLS4 force field. The required number of sodium and chloride ions were added to neutralize the system, and no volume within the ligand's surroundings was excluded for the salt and ion placements. The built system was simulated for 20 ns while the trajectory was recorded at every 20 ps. The normal temperature and pressure (NPT) ensemble class was chosen at 300 K and 1.01325 bar, respectively, and the model was relaxed before the simulation to minimize the water molecules. The analyses of the various interactions were done using the Simulation Interaction Diagram (SID).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Analysis of ADME-Tox and drug-likeness\u003c/h2\u003e \u003cp\u003eAdmetsar3 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://lmmd.ecust.edu.cn/admetsar3/\u003c/span\u003e\u003cspan address=\"https://lmmd.ecust.edu.cn/admetsar3/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Swissadme (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used to perform ligand-based investigations of the selected phytochemicals to identify the molecule that would qualify as potential hits to reduce viral pathogenesis. The pharmacokinetics and drug-likeness of these compounds were screened using a variety of metrics and guidelines [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The drug-likeness parameter was used to predict the route of administration of a drug candidate based on its bioavailability[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Toxicology risk prediction can show potential adverse effects of phenolic chemicals, facilitating rational medicine design. Predicting the hazardous effects of chemicals, including mutagenic, tumorigenic, irritating, and reproductive impacts, is crucial for drug development from laboratory to clinical application [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"3.0 Results and Discussion","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Reliability of the non-covalent docking procedure\u003c/h2\u003e \u003cp\u003eThe reliability of the non-covalent docking procedure applied during the \u003cem\u003ein silico\u003c/em\u003e studies was validated by re-docking the donepezil ligand into the hAChE enzyme. The conformation with the protonated \u003cem\u003eN\u003c/em\u003e-benzylpiperidine moiety with the lowest docking score was the most likely binding mode. The RMSD of the donepezil ligands was calculated and was found to be 0.54 \u0026Aring; which falls within 2.0 \u0026Aring; maximum allowed deviation, and therefore the docking procedure was considered valid [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConsidering the superposition using the maximum common structure between the two ligands, the indanone moiety of the ligands perfectly aligned, deviation was found within the \u003cem\u003eN\u003c/em\u003e-benzylpiperidine rings with the chair conformations of the piperidine rings clearly displaying more deviations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As expected, the two bulky groups (the indanone and the phenyl) on the piperidine chair conformation occupied equatorial positions [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The only difference that caused the deviation was the directions of the indanone and the phenyl groups on the bridging carbons to the piperidine linker.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Non-covalent docking of the phenolic compounds and donepezil against hAChE\u003c/h2\u003e \u003cp\u003eThe binding pose of the co-crystallized donepezil in the active gorge of hAChE enzyme showed the crystal near the catalytic triad, which could be important in preventing acetylcholine from getting in contact with the catalytic Ser203, thereby inhibiting the hydrolysis of acetylcholine [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFive notable interactions were observed when the 3D molecular interactions of donepezil within the binding pocket of the enzyme were analyzed. The protonated nitrogen of the piperidine ring simultaneously displayed two π-cation interactions with the benzene ring of Tyr337 (distance 4.19 \u0026Aring;) and the pyrrole ring of the CAS residue Trp86 (distance 5.28 \u0026Aring;). Additional two π-π stacking interactions could be observed between the benzene ring of the \u003cem\u003eN\u003c/em\u003e-benzylpiperidine moiety of donepezil and the indole ring of the CAS Trp86 residue; one to the pyrrole ring of the indole backbone (distance 4.36 \u0026Aring;) and the other to the benzene ring (distance 3.72 \u0026Aring;). The carbonyl group of the indanone moiety of donepezil showed hydrophobically packed hydrogen bond interaction with the nitrogen atom of Phe295 backbone (distance 2.00 \u0026Aring;). This type of interaction is critical in maintaining ligand stability within the protein's binding pocket. In addition to being a hydrogen bond interaction, the hydrophobic location makes it very difficult to break, thereby maintaining stability during the protein movement. Lastly, the benzene ring of the indanone moiety also showed a π-π stacking interaction with the benzene ring of Trp286 PAS residue (distance 3.81 \u0026Aring;). Most of these interactions are in agreement with earlier reports [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBoth the GlideScore (GScore) and the DockScore in kcal/mol for the docked ligands are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGlideScore (GScore) and the DockScore in kcal/mol for the docked ligands\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLigand Compound CID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eXP GScore kcal/mol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDockScore kcal/mol\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMMGBSA dG Bind (kcal/mol)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDonepezil (3152)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-16.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-91.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMyricetin (5281672)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-75.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuercetin (5280343)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-13.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-66.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEpigallocatechin (72277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-55.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEpicatechin (72276)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-54.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatechin (9064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-54.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuteolin (5280445)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-50.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsorhamnetin (5281654)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-58.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRosmarinic acid (5281792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-54.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKaempferol (5280863)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-56.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApigenin (5280443)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-53.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaringenin chalcone (5280960)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-28.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRutin (5280805)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-64.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNaringenin (439246)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-45.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4-o-Methyl epigallocatechin\u003c/p\u003e \u003cp\u003e(163184613)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-67.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenistein (5280961)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-22.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDaidzein (5281708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-51.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEllagic acid (5281855)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-73.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlycitein (5317750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-61.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoumestrol (5281707)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-53.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-\u003cem\u003eo\u003c/em\u003e-Caffeoylquinic acid (1794427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-26.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCapsaicin (1548943)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-61.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEpigallocatechin-3-\u003cem\u003eo-\u003c/em\u003eGallate (65064)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-8.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-74.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCaffeic acid (689043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoumarin (323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-39.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGallic Acid (370)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eo\u003c/em\u003e-Coumaric Acid (637540)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-24.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePiperic acid (5370536)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-40.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhenyl-6-O-malonyl-beta-D-glucoside (128708)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-48.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEugenol (3314)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-37.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSinapinic acid (637775)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-24.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFerulic acid (445858)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-23.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtocatechuic Acid (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-27.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsoeugenol (853433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Coumaric Acid (637542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-16.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Hydroxybenzoic Acid (135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-11.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGentisic Acid (3469)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSyringic acid (10742)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-17.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVanillic Acid (8468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-12.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe docked ionization state with the lowest binding energy was taken as the most probable binding pose and, therefore, only reported in all the ligands. The observed differences between the GScore and the DockScore were due to Epik state penalties applied to a ligand that shows the lowest binding energy in an unfavourable ionization state. Donepezil showed the lowest binding energy at -16.4 kcal/mol and many of the docked phenolic ligands displayed comparable energies to donepezil (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Most binding energy contributions from all the ligands, including donepezil, generally come from their lipophilic interactions. The binding site contains a lot of lipophilic residues interacting with the lipophilic rings of the ligands. Myricetin, quercetin, epigallocatechin, epicatechin, and catechin showed binding energies of -14.0, -13.5, -12.0, -11.7, and \u0026minus;\u0026thinsp;11.7 kcal/mol, respectively. Interestingly, all of these ligands showed more hydrogen bond interactions than donepezil. This is aided by the presence of several hydroxyl groups on their molecules. Myricetin, for example, has an H-bond pair reward of -5.4 kcal/mol, while donepezil has \u0026minus;\u0026thinsp;1.3 kcal/mol. The 3D interactions of myricetin within the binding gorge revealed two π-π stacking interactions between the benzene ring of Trp286 and the benzene ring of the chromenone moiety (distance 3.99 \u0026Aring;) and the pyranone ring (distance 4.37 \u0026Aring;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe 7-OH group of the chromenone moiety displayed two water-bridged H-bond with NH of Tyr75 and the phenolic OH of Tyr72. The NH of Phe295 also showed hydrophobically packed H-bond interaction with 3-OH group of the chromenone moiety (distance 2.00 \u0026Aring;). As mentioned earlier, this type of H-bond interaction is essential in maintaining ligand stability within the binding pocket. Other interactions within the binding pocket involve H-bond interactions with two water molecules (Fig.\u0026nbsp;3). Due to their structural similarity, myricetin and quercetin had similar binding energies and interactions.\u003c/p\u003e \u003cp\u003eThe binding poses of (a) epigallocatechin (b) epicatechin (c) catechin and (d) luteolin showing non-covalent interactions within the binding site of hAChE enzyme are also shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 MM-GBSA-based re-docking of the ligands against hAChE\u003c/h2\u003e \u003cp\u003eAccording to Hubbard and coworkers, better scoring and pose generation functions could be obtained from MM-GBSA than from a non-covalent docking mode [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This is because MM-GBSA gives more accurate results, and its efficiency has been proven in many studies [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. As a result, the ligands were docked in MM-GBSA mode to evaluate their binding free energies and poses with the flexibility of the protein residues restricted within 5 \u0026Aring; from the ligand. The result is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e above.\u003c/p\u003e \u003cp\u003eAnalysis of the MM-GBSA results shows the preservation of some interactions initially identified by the non-covalent docking. Among these, the π-π stacking interactions between the benzene ring of PAS Trp286 and the benzene ring of the chromenone moiety of myricetin were fully preserved but at a closer distance of 3.71 \u0026Aring;, instead of the original 3.99 \u0026Aring;. Likewise, MM-GBSA indicated H-bond interaction between 3-OH of the pyranone ring and the NH of Phe295 at a distance of 1.96 \u0026Aring;.\u003c/p\u003e \u003cp\u003eOne partially preserved interaction is the water-bridged H-bond interaction between 7-OH of the chromenone ring and the OH group of Thr75 side chain instead of the original NH of its amino group.\u003c/p\u003e \u003cp\u003eIn addition to the preserved interactions, MM-GBSA identified new vital interactions of myricetin within the binding gorge of hAChE enzyme. The isolated benzene ring of myricetin showed two separate π-π stacking interactions with the benzene rings of Tyr337 and Tyr341 at 5.37 \u0026Aring; and 4.01 \u0026Aring; respectively. The 7-OH group of the chromenone moiety displayed a water-bridged H-bond interaction with the OH group of Asp74, and 5\u0026rsquo;-OH of the myricetin's isolated benzene ring showed an H-bond interaction with the phenolic OH of PAS Try124. Other H-bond interactions involved the 5-OH of the chromenone moiety and C\u0026thinsp;=\u0026thinsp;O of Ser293 in a water-bridged interaction, and the C\u0026thinsp;=\u0026thinsp;O of the pyranone moiety showed two H-bond interactions with NH of Arg296 (distance 2.54 \u0026Aring;) and NH of Phe295 (distance 2.58 \u0026Aring;).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the superimposed structures of myricetin from the non-covalent docking (green) and the MM-GBSA (light grey) studies. The positions of the substructures were preserved, but MM-GBSA was able to move the ligand closer to the PAS residues. The high binding affinity shown by myricetin in this study agrees with several previous reports on myricetin's role in treating AD [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Structural modification of myricetin for binding affinity optimisation\u003c/h2\u003e \u003cp\u003eMyricetin, the ligand with the highest binding affinity, was modified to increase its geometric and electronic complementarities. The chemical modification was done using the carbonyl oxygen of the pyranone ring to form Schiff bases with different amino group-containing compounds. The Custom R-Group Enumeration panel of the Schr\u0026ouml;dinger suite was used to generate 333 ligands using 38 aliphatic monocyclic rings and 73 aromatic monocyclic rings as R-substituents to give the hydrazides \u003cb\u003eA\u003c/b\u003e, the hydrazines \u003cb\u003eB\u003c/b\u003e, and the imines \u003cb\u003eC\u003c/b\u003e as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The ligands were prepared as described previously, and the non-covalent docking was repeated with MM-GBSA analysis. DockScore filtering was applied to enrich the dataset with ligands having a minimum DockScore of -13.9 kcal/mol (using myricetin as the standard). A total of 30 ligands were obtained, and the top 5 ligands are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e The GScore, DockScore and MM-GBSA values for the top 5 modified myricetin\u003c/p\u003e\n\u003cp\u003e\u003cimg 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6tWrbck+SkP88MMPg3PPPdeWoBQEsCXQcK7r16+3S9Vx8803myE0RZ+l2BCzAACUkxo2KmhU7zivv/56MGbMGPvMXr169TL9JqsRkwJIncdUS5om1a6qlvWTTz4xwbNG0vT16NHD9Apwww03mEBaNbRpfwYXnCuIViqA+nN11AesPpMGZgnfxUUyBLAlqJXGGu4z0HAEaDw6EaomJzy8rqjHFD0X7jnFlQNpUn6palzVM4+CwxkzZpiW/qKUAQWr/nlKjagUXOoWunrvSKNHEdWm6u+odlW1rKptdZ8hysCBA03NrGpoFXSn0ShagasLikVpAArYFayqP1g1zFIfsPqc6tkIbUMACwAZoiD0mmuuMSdCNSi96KKLTGNSP5BV7yhq3BnuJcWVA2nw81ynT59uAkeXt+mCOaUMKKANN5rS8pQpU0yA9+qrr5pAtpQ7m36eq2pVFUCrljUu1YYqmFaNban5sQrOb7vtNhOYqnbZH5RA3Wzq2HS1sWrcFW63osA2asAClSsdA9EIYAEgQ6666ioTiOpEqAalOjn+0z/9k2k0ElUbC6RNAVs4z9X1h66AUqkBLphTgKrUgXw6d+5scmNVY6pAVOlwcdt0hPNcVataCtXUlpofq1Q+Bb6i9aDa5SiuYVa4T1hRKoGeC1O539MRWiKABYCM0O1YnWRVy+SfCDWwiWqg/uVf/sWWAOVRKM9VwZxqUpUaUCiYi9KnTx/zfuo6Su+hGs186XHF8lxLlSQ/VrXF+pzPPPOM+dz6vJUYHAH7EMACQAp0m1S1SeX02muvmRNrVC3OyJEjg9mzZ9ulvVQrpZxXN2kZKEWhPFc/mFONq1IDSg3mhg0b1ryfKkh1jZUlaZ5rqQrlx6p2WLXECm7195cuXVr24x7RCGBREt2q1AlRDUnCXOOSMJVzixNp+Prrr4MvvvjCLlWHaqD8z6ATb7lrYKLy5JyoEX8eeOABkyfrJi0DSagGUqkAUXmu5QrmdBypRlM1mwqKTz311OCKK64oOc+1VOH82J///OcmUFctsT6bao1RPQSwSEQBqFpTquGITohqSKJEc7+1s/LyohqKqFxX5kCpXO6d9iV1TVOObnjiWLRokTlhb9q0yTRiqVQ/zAcccIB9FI9qjrSu3JRGS2s0Fg0AsG3bthZ5rq7RUrmDOQXDCor13v/2b//WpjzXUrn8WAXOql3WZ9DFKqqPABaxKUhVQxH9mCiQ1QlRDUm6detmbuuEu+wB0uTn3mkM8a1btzZ3w6OAshKUg6rPoMBVt00///xz04hFt1YVWOfL2UuLAgiN4BNFHaar43QgTQcddFBwzDHH2KW9x6FrtFTOYM4f6EANnFQLW2m6MHXHtGp8df4jz7V2EMAitnnz5pkTpN9/nXLxdFtp3bp1wcsvv2xLgfTky73TicR1w6OAUoFluYap9LsEUotpjSrkbpWqEYtqoBRY6zPoBF8uGrlHI/j4HaOLLh7VRc/o0aNtCVAeOhYq0WhJKQuVHHY2ij9gEGoPAWwdUI2oTurlpuAh6mpbQaw6ag6fVP3GI5r8K2qgGNV+FOpj0u1PCiTLNUxl3C6BFFDrGNQxokBbAbcC7zSoBkifQe+nbnWUE6jbtgsWLDDHlY67k08+2RyD6o0AKCflhdJoCbWAALYEygdSPk41KR9Jt1FFV8GVSCZXLWs+Ciy++eYbu7SX33hEk068QBxx+pgM576mPUyl0hKUnpCkSyAdBwq0FXAr8G5rfqzrY1KfwQXOgwYNCnbs2GGCdB1XCmDV+4B/Z2T//fc3gbzmPlcOAFlHAJuAy3/TCUWJ7ZVsvOG47koOPPBA83mSdPpcaX7jEU1KggcKcf07RvUxqeEm/YAyX+fo4WEqk+bH+nmupXYJpIBbn6HU/NhwH5Phxo+qiVXAquNKv0UKan3q/FzPhTtBd+UAkHUEsDEoQPTz33SSVQ2sf3IqN3c71XVX8tJLLwVvvfVWrE6f0zJq1Ki8t2ZVU8QQlShVuH/HqD4mNdxk3ICylPxY7dv58lxLlTQ/Vse5am7pYxIACiOALUABoesqJCr/zT85qdaolDGUi9Fn8G+n6u/56QJ+p8/lbkCi/Drdqgz35ao8PKUXXHrppbYEiEe3+BWsKXAM9++oYM7vY1JBZdJgLk5+bNw811LFyY/1j/Ozzjqr1XEOAGiJADYPl3smChD9/DfdknS5de7kpFqjpGMoF+N3G6QTmn871afaJgXa5WhAoqBcAby+r26LqqGIuhJR3p0CVzUkUc2rbnUyZjOSyDeOuQvmtN+l1cdkvvzYUvJcS5UvPzZ8nGtELQBAYQSwIeHcM7+rEH/8ZXd700kyhnIx+boNKibNBiT+LV3VXrm/r7w7jQakAFYNSFSbpWU/B+/www836yBM5aQZQJTDGTWOuR/MlaOPST8/VoNw6HiPm5aQFj8/Vn0o/8//+T8THecAgJwmGDt37mzKnSyb+vTp05QLXG3pXrkTadPAgQPNpMdxzJkzpykXUJp5XLt3724aM2ZMU69evZpyJ1VbWrqFCxc25QLrptyJselPf/qTLS1MnyF3Mjf/L3dStaVAusI/PbmArikX2DXlAsym7du329Ly0vFZqb+Vj75zGsc6UC6PPPJI08iRI+1S5fjHRrU+g/6m/rbos+gzoXY0fA2sn+cavl2pGtR8+XnFhMdQLpYf626nhrsNaoukDUj826n+LV2gnNS4Kqqv17SptjVpjwRp0x0L/d4AANqmoQPYcJ6rf7syX35eErodqMYnhfJj/bQEBa758lxLpc9QrAFJVLdBQKXoYi2ti7ZCdOy98cYbdqk6FMCqNwUAQNs0ZABbKM/VBXNR+XmlisqPVRdYLsdUAa4C3XLmv0Xlx+oz6POk2W0QAACoPxqy2o2sGUXlO3futEv7qFz/N20NF8Cq/1QFbQoY/T4Ww31AliOgVC2uanN//OMfm65ykqYlpMHVdqnHgDPPPLMs3QYBAID6oR6HNJKfGm+rYq9du3atho9XI+2ogVJUvmXLFruUnoYLYH/0ox+ZgNHPcy1nH5BRVAN6yCGHVDXHVMG6gvdydhsEAACyTcHruHHjTBCqAHXt2rWm9yG1GwoHsZXU8I24lOtaiT4glaZQzkEG4tB31XCcAACUIq0+xpENuvWv4FWVe35f76ecckowf/580zd8tTR8AKvAshJ9QCqnttR+YdOivx8ehQgAgLjUGFjtRIoNzdxWSrGrdmqb7sqWu3FprVNNq0Sth4svvjj48MMPW4zOqRjD5cm6qVwaPoAFAADR1A3jV199ZZeC5mGd8w3NnBbdEXXtUPQZvvjiC/O4khS0uW79/vKXvwRff/21eVxNzz33nH1UGe+++6591JoGpJE9e/aYuahxvPJk/alcCGABAEArSjvTsM7qfs4fXTLf0MzloL6bFTSrm8fLL7+85NEl20Lpf9ddd13wzTfflDVoL0Rdbqr9zuTJkyO75CwXpVgmoZpz5cn6U7kQwAIAgGZ+/+TqOecPf/iD6RNdqQMKah1/aGZ1TZnmQCF+/+Tq+vLzzz83jYb0d5T6p0GIys0f1v1//+//Hfz+97+vSNDu84d1VyCtGlG/S85yf4bTTjvNzKO6x3JpJMcdd5yZVxoBLAAAaBEshfsnzze6pNqPqB2JamQVbCrAVMBZqnCXln7/5BpsSAG16DNoMKJyUC2v+kqPGiGwnEG7T4FpvpFAXZecURcVaVPDrb59+wb33nuvLdln3rx5wahRo4L27dvbksoigAUAoIEVCpZ8CmYV1EaNLqkgU8Gmntd7Jb3dr88Qp0tLBcyqgdUgRMq3bGvA7FOtrlImVOtaaFj3cNCedqM2BaR6z6iRQP1h6ZMOWZ+EAnPXa9HDDz8czJ49O7jmmmtMoyx9VzXg+vLLL8saPBdDAAsAqIolS5aYE6Gmu+66q9VtSvUxqefCVK7XNxJ936jvrLJwX5zq+kjlbt1qPecbCalQsJSPgtvw6JLuVrb6WFdwmeR2vwIlvTZJl5YKmDUYUbGAudg+5uj2vNaDGozp88cZ1t0F7a5RW1tzdP3UDa2H8EigWo/Lly9vEbQXuqgohd5X60GBudsOqoVVQy2Vq1GWal61PrUP+LWv2hcOP/xwu7SPyjUIQuqaGkzuiqkpd0Vllypn5MiRTbmd3Dzevn17U9euXc3jSpo+fbqZpFqfAZBq/PTo+NNx6Gj/13FQSeHfHz1WWaPJnQyb+vbtayZ9/w0bNjRNmjTJ7Bdbtmyxr2pqmj9/fuS+ovLcSdEuNQZ936jvrDKtD0frT+ts1KhRZr1q/eo1Wtda704u+GjKBaJNuSCpaffu3ba0NLkAyhxPmvv+9Kc/mXOO/o4eh+UCxaZcwGuOy1xgaUtLkwtmzWdw57i4+1guUDTHYS5Ya/Pvgf8Zor5vPrkLh6bchYOZ9LgYt96GDRvWar2Vul31Pno/va/WSRZQAwsAqCjV4IhqcHSLVp2i33PPPaZj9Go1CKkXyklU5/IPPfSQWa9av2oJfvDBBzfX6LmavHCea6ny3cp2t/v1nN/XumopVVupmlP9fdVgujzXUrn8WP0dvX/cfUy1lrmAs0Wea6mS5ujGTd0IK1TLnTQ/Vv9P/1/vo/fT+2ZlaHkCWABVpXwq/xZkuegk3dYTdVvVwmeoBdOmTTPdAYUbfyj3UdLMJ2wk6lB+3bp1wS9/+Utbss/48eNNLqNSCRTkKWiMEyzFpf06361sF7xGBUsKxtKiv6PcVAXDcfcxrQcFuGnRZ9B31HcrlKNbSupGWKGAOd9FhU+v13Oi99H7ZQkBLICq0smjEq1plc+lE2w1qWZDJ/hG5kbtOeyww8zcp2BDtVHhztNdDqObFCA1Iu074XXh709vvvmmmbsO5n0uSNN49uWkoFg1ieH82EoGS6XsY2nLl6NbLM81qUIBc76LCj2v1+n1+n/6/+4iI0sIYNGQ4jRy0POawlQWbjSB+FTz8Vd/9Vem0YQTp7YgTfoBV9+WTzzxhC2pPJ1I1M9kOTv6LkZdFp188snmBOZuQZabP2pPXKpN8yfV3jWivn37tloXKnPUAKlW+Ley1QhI+3mlgqVS9rFy8W/3d+vWLbjjjjtMQKnAMs27MYUatfkXFf/5P//n4KqrrjKv0+vbmrpRTQSwaDi6OleLyG3btpkTgG6t6cdVV6d+EKsxoN040D6VffbZZ3YJcfn9O+rHVJ2Dq7saBXESri3Qa9Me8cbPvXvyySfNdlTNbyVvWft5b8pT/NGPflSRoN2nz+C6LNIx8Oc//9msB/+iolyK5bhu3ry51eg/yl/0p7bmKmaV8ljD60JlTs+ePe2j1lzr+7K0Bi9AF6e6WNTxVqlgqZR9rNxU46xBARTAppm6EVYsP3bQoEHB1KlTU03dqBYCWDScOI0ckB4/WHL9O5577rkmUFXjCXUWrk7Dw7UFaY54E5V7d+GFF7boAqccAXNYOO/tkksuibzFV07q31HrwXVZpM8wY8aMyIuKctAtXNUarl692pbsoz4mP/zwQ7N/ILnevXubedQFmX7junfvbmpD610W9jH91uhCtlz8/Fj9xtajhg9gtQP5J89yUafI1a410N/PSuvCconbyAHpCAdL4f4ddfGgch0fCpzUibirLdBr9Zz+r97DdaqdVLHcu0qM614s7y1f3mCaFNQoeFb/jvq+auzi38rV70O+i4q0uAsEBfKq+fVTcVRDqPWii8uoHE4Up8BNrex1LLk8UFHQNm7cONMZfaOo9X1Mx0I5LxTF5ccqVaAu2e60Gob6g8udNO3SXgsXLjT9ps0J9WFXLrXQB2uj9gP7+OOPF+yDVM+pv0DJBRJmWXN/Upnf72JW7dixo/m7+lTu95PoU7n+j15TiI6zXGDYNGbMmNj9O6rPwlxQZY7FXDBnS/fSe6ivyD59+pg+EOPQ6/T6XMAa+zOo78YZM2aYz6DfhXzcusu3npxcwJyof0dHv0U6PtP4TdKxrj4u9buXC55t6T76nlrv4T4j3e+i1keSPi2jaP1rO2h7uPfSPtK9e3fTT6c7ru68807znKPjLOp4Vbn+TyNxvz9hKgv/Hrn1pue0fvX4mWeesc82jjj7WCXpGNRnkqhYpBL8PumzrqECWP2InnvuuU25qxLT4bBPP965K7PIk2ea9Heuvfbapv/0n/5TxQLmMPddtR7SODmVwgUKf/d3fxd58iyXfCdER8/5Aax++LTsTyoLnzCyKN+6UHn4RKlATd9bJwN3ItDc7xhdigVLceg98gV9flCab5/xg6W4wW6Y3kPBt4Jwd8IRfV91EO++v9aHpnAgm8bviXuP8GeIS//fXRCsWLHClrZWKGiP+x75+O8d/s113HEV3peklIuseqXvG/WdVRZ1Qan16dZtoyu0j1USAWy6GiKA1Y+oRsZQjYZ+RAud4EqtMYnDr1VJ4wRXCn1//U2dVHbt2tWmk1Op9Lf0N/W39RmKneDSpB+NfAGsTgJ6zp0kFKCEAzlRWSMFsPrR1+s0io2jMi0rqHUnBe3Xae5LOi70fjpOdLz4tK+Eg7rwcZ4GBeE6ybjATuvF/87iavXdfqPPlVbtqbjPoAsDBfdxlFJ7mi9ol1IuTPzjPLz9gEZEAJuuug9gdSLTyUQntvAPuavNiRrGrtDJMyntqPneywXMSU5OpSh0O9WdnMoRtPsKfddCFxVpcsFY+AQtCtxUm+YQwO6lW24K2sLcunS3JrVN4wZLSfgXfvkUOs7ToPfUPqPv6wevjtaXC/B1jJcjYIsTEOozJk3dCCsUMMd5/1ICbqAREMCmq24D2EIBW5g2Zr7aCnfyDN9ai8MFhtpJiwWG5aqtSBIYphm0+/RecWubk2y3JPQZ3N92gZt/O063l/xgTBolgHW319ykQMz/3oVSJvRa3VIvt3z7ULn2lygK5KP2B9F+o3VZbvp9cncs/N8k/7cmbg1pMYV+k6JqeLX+89XgAiCATVvVAlgFD34A4agsKp9H3Ak2qgbESRKw+fQDrR9q/SiHb4HquSQ/zIXeq5B8J6ewOOtB71Xq7dQ4NV5xFXsvHcBRAXOaNWruM/jrwQVvCkgUoIWDV9FzUQGLyuopgHXf000uz9XRa/J9X5X7ry03V4uvXPaLL7448XHeFm79RNHxWIkA1vGDxZ/97GeJf2viKvSb5P/OXXXVVUV/t4BGRwCbrqoFsPlOBioLnyy1oXVyUKCh5/U43JKwLQGbr1BNhrs1pgA5X1AVVTORVL6ajDjrQdII/nRyiltrGiVJbW6+ILet27TYZ9AFgLsYiFLKRVaWuAA2LByU6jW1EsA6CxYsaJo5c6ZdqgzVNOf7rpUOYJ25c+c2denSpeTjPK5CtasvvfRSU/v27Yse50CjI4BNV80HsO7E4NeOKXhQEOdyzvTjrR/WNGrrHO1cek/9aOvH26fAKPx3Cr2+VC5gVlAdZz2Ids40b6e6Gq+4+bFJX+8UCpj1XfSdoi4qoriLkKSfodHEDWAVuPn7mE/7XzW7pakkNdbyc6R9+fKEyy18EkwrfSAf95uk48sFrDredJEJoDAdOwSw6an5ADbfCdIFdOWuCStWo1qO3LMo1V4PxWozCwWgSRQKgItdJOgzlJK60ajiBrBa73pduDba7XtRtdT1SMeYvm841cQ1ZlOAW2nhk6ACSf0mlZuOL/d3CGCBeAhg01XVkbi+/PJLM0KIP6nM0YhIGjVpwIABtmQfDQHavXv34KWXXrIl5ZELlsywk999912LscKjhsfMBVfmubTVwnrIBZRmFCMNgan1oFFOnPDwmHptqXLBZ94RiXIHe95Rm4qN+ITSab1PmjTJjC+uUW10nC5YsMAMW5kL5hpiaErRyD36vhqKVt9f60Hr4+STTzbrZ/jw4faV9U/HVy5otUsAUHlVDWAVlN15550tJpU5W7ZssY+inXDCCSawLLeOHTu2GCtcAdRpp51WsWCpVtaDTJgwwXxnDYl52GGHmZNYvuEx26JQwOxfVCjgPeqoo/IOj4n8Dj/8cHOREKZyN6a6c8899wQbNmwwAZuOUw2DqOVBgwbZVzQGfd8dO3aY76/1oPWh4Tm1fgAAlVPVAFYnz6effrrF5J9Q999/f/uoNihYW7FiRTB16tTgxRdfrFiwVGvrQQH9nDlzgv/yX/5LcP7555vHKisHP2DWWPIaU17cRYVqwM8444xg4cKFQefOnc1ziEfBmI65MJVrHw9Tbf9DDz1k/o8CNi03ItXE6vtrPWh9NFoQDwC1oKoBbDHu1uTnn39u5j7dVlcw2bNnT1tSOZdddpmpGayUWl0Pqvns0qWLeaxb+cuWLTOP0+YCZn3PuXPnmosclzpwyCGHmBQKAADQOGo6gBXdplNthwI1n27li/LzGkGtr4ddu3aZnOBycvmxqnklTQAAkFWqmCnXnUuf2u1cffXVdqm+1HwAO378eDPXreJXXnnFNJyYPHlyMG7cuKK5ofWE9bCPAlkAALJKjb51V7FcNm7caBo7q5Jr+vTptrS+VC2AVSORcEMRUZkakTjt27cP1q5da4K1efPmmZrITp06mYYUjdL6WVgPAABk19dff22CVpcCVw66Gzp27FhT66rAVX/P9Rii515++eXgsccea+7dJ8uqFsCqkUhUQxGVRTWKcA1ONOk1akjRiFgPAABkz29/+9vgb//2b1t0yZkWBcXqWlK1ruopSY2fXWqh/9wtt9xi4ohw7z5ZVPMpBAAAAFnnes9xXXIqoNSt/rZSMKyAVF1LqotJdTXphJ/7xS9+kbd3n6whgAUAAKgQ1yWnbvHrVr9u+ev2flJ+nqtr4OwahhV6TvTY791H7Wvef/99+2w2EMACAABUWKHRJQspluea77kohUa/DFMvSGpArimKynfu3GmX9lF5uAelNBDAAgAAVEm+IeujKG9VwW6hPNfwc3EUGv1SNHy2BlVSA3KlILRr186MROhTI3y1zwlTeTl6SyKABQAAqKI4+bEKUtUHerE8V/+5pPz82NNPP92UKXh1XXYqQFWPSBpKfPDgwa2C2EoigAUAJPLxxx/HutUJIJlC+bEKXhWcxs1zLZXLj12zZo259a/gVY/9Ljs1lPj8+fODSZMm2ZLKI4AFgDqhE1jnzp3tUvqUG6ccOTX4KKXRCYB4CuXHJs1zLZUCZtW0SlQ6wsUXXxx8+OGHwQcffGBL9l7cujxZN5ULASwAZJjfOGLYsGFlG2ZZOXG6TakcOeXKuRPmn//85+BPf/qTeQwgXeH82BEjRpSc51qKd9991z5qzfVDv2fPHjOXZ555xuTJ+lO5EMACQEYdddRRplZGrYdV81EO6iNSfUUqJ04nTOXIOcq9+6//9b8Gf/VXf5XJbniALHD5scpFVQ5qW/Nck+jQoYN9FI96M3CDLbmpXAhgASCjVBv6f/7P/zG1Mgogb7755tSGiFQwqvdUH5G6RamcuKjcuxdeeCH47LPPYnXDA6B0Rx99dHDQQQelkuca12mnnWbmUd1jvfLKK2Z+3HHHmXmlEcAiU1TbtHjxYrsEQIYMGWJqR1VbopbDixYtss8k5/JcFYwqKFXjEPUVKYVy74p1wwMge9Rwq2/fvsG9995rS/aZN29eMGrUqKB9+/a2pLIIYJEK13KynHS7Urcyqd0BWlPu65QpU0xr4U2bNpkg0tWQxBXOc1VQKrpwjNvHZL0MUwlgr4cffjiYPXt2cM0115hGWfpdUQOuL7/8sqoXqgSwKJlqYz766CO7FAS9evWyj9Ll365U7o+fg7d58+Zg/fr1dgmAeiFYuHBh8MgjjwS33357rPzYYnmuCmqT9DHpuuHRRW2hYSqXLFliToSa7rrrrla3KdXHpJ4LU7leD6D8VAurhlr6HVCjLNW86rjU3Rm/9lW/NYcffrhd2kflGgQhdU1AidauXdt07rnnNg0cOLDpvffes6XpyZ3MmnIny6ZcYNy0Zs0aW7qXnhsyZEhTnz59mvr169d09tlnN+VOvPZZAE4uiGzq0aNH05QpU5p2795tS/eZPn165DGs40nHlY6z7du329LS5E505jPkAuOmP/3pT025k2FT3759zaRje8OGDU2TJk1q0ilpy5Yt9n81Nc2fP9+Uhak8d1K0S0Bj0HHYtWtXuwQCWLSZf3KKOkGWYs6cOeY9Fy5caEv20slPJ1wdxDoxOzoJKtBVwKvgFsA+Om5mzJgReUyFFbpwbCsd1wqU77zzThO8KpD1hQNWAlhgHwLYlkghQJv5jTfa2oDEv5UZvl25bNky85zo76nhiqN8PN36jOr0GWh0cfJjk+S5lkqpCbkgOpg2bVowefLkVo0/1JuCJM3dBdB4CGCRGp2cCp0gCynUZY9yXBUYq4NkBbW33XZb3s7aFfDqNa7TZ+XvAdgrX35smmOpF+NG7TnssMPM3KeAVp8p3Hm6y5N1k34nADS2dqqGtY+B1KjhlbricY05XFc7YepRYNasWabmVR01u1bPokZieg+dYPUeffr0sc/Eo//n+qTU//cbmWn0IiWiu2HydFJUja5fI+QaiUydOtXMHZWfcMIJwaBBg2wJkE0KXIcPHx6cfPLJwWOPPVaW4SjD1Iq5d+/e5tjTeOphOhbPPffc4Prrrzcdt2scdnecOrobs3Xr1rJ2kg7UGp3TdIdk+/bttqSxUQOLslCwqNrYYh2sqz9J9V2pWp9wlz2qdR08eLB5LmnwKjoZqzZX/VXq7yiYFdUAqUXktm3bzK3M8ePHmxOhPqc/LKdOmuETp6hMHbcDWaeLtlNPPTX4H//jf1QkeJVinZ6rZ5Hw6D8KdP2pUp8VQO0igEVZ6QSpXLp8HawrwFRunksJ8G9lKs9VY7u3lcuPPeuss8yyOl6eNGlS8NBDD5mToZ5XAHvwwQe36D4IQPp0l0Mdo69evdqW7KPa2Q8//NDUwAJAIQSwKLs4DUj8vl7Vt5zSCfLluZZKwbRqX9etWxf88pe/tKX7qCZWHTb7tbAA0qfOz3X3Q/25OuoDVheQurg89NBDbSkARyl5fipcoyOARcVENSB566238g5NWQ5vvvmmmUedIF2L6y1btpi56PP4jUc0qQxA6XTnQxe0Clb79etnjqsuXbqYNJ577rnHvgqAows85X2rzUgU3b3Qa8JUXq+VMgSwqDg/P1a3EsvVZU8UpSYkoc+nmiJ/UhmAttHxrjsirjZWI/2EG0wqsI3KQ1e58uSBeqfgU0O46gJPo2BddNFFZmQs15uHo4aRUY0aVe5XytQTAlhUjW7p/+Uvfylrlz1hPXv2tI9ac1ev/pB3yov1G49oUhmAdLjjKtwnrOhOiZ4LU7lO4kC9u+qqq0wAqgs8BagKXP/pn/7JNIYMB7GNhgAWDUVXoxLVR61+HLp3786JEQBQdTpPKWVN7UL8Czx1facUvH/5l3+xJY2JABYNRT8C8+fPNw3G/KtX5Qmpv8nZs2fbEgAAque1114zgWrU3YmRI0e2Ol+pn1idy/ypnhHAouGog3QFsboFo1w6NSJRzaxG+mJwAgBALYjK/3aiRrLTOUx5sv5UzxiJC1XVrl27oFq7oJLjXXJ7VJ6dq6ENpxSoXHmydPWDeqC7EeoBpBKNKAHEp8Zb33zzTWTjLNWuquLFnT91LlXFjCpofCpXIBx1jss6amDRsHRbxjUgiaLANSofVmUErwCActJFpUami6KBQBq9RxwCWAAAgBqjEek0Mp0/4Ifo7qG6nhs9erQtaUwEsADQwDTqXZ8+fewSgFqhO33Kax08eHCwYMECkzagYPbkk082g4CoN4JGRgALAA1oyZIlphHj3XffHdx7772tRvHRiVLPh6n8rrvusksAykkNi3fs2GF6GFCjLB1/6n0gPGKdeis4/PDD7dI+Kvf7Nq8nNOJCVVWzERfQiHT7UUO2yq9+9Stzclu2bJk5KapRo8v7Vo2PupYLH58qf+mllyIblgBApVADCwANZN68eWauztHVSESNGFWb47qWA4AsIIAFgAaixh+TJ09u1Tn6iBEjzDxqlDoAqDUEsKiq7du320cAys31bRzVCboCWuXLvfvuu7ZkL+XB+tPcuXPtMwBQPQSwqDjl4KkRiE6Gv/zlL01jEpX59Fy46xBRuT8ELID49uzZYx/Fpxpbf1KLaACoNgJYVJQbxWrbtm3mZDh+/HjTGESNSvwgdsWKFcFnn31ml/ZReSknYQBB0RxXdZreoUMHu7SXG+zDTV27drXPAED1EMCiokaNGmX6r3vooYfMyVCNSBTAHnzwwcGECRPsqwCUg9IENHqPRvEJUx+T6jRdnacDQK0jgEXFqPZ13bp1Jm0gTDWxDz/8cKtUAgDpuu+++8zdDz9FR33A6gJSF5cMkwwgCwhgUTFvvvmmmUedIFUTK+qH0lFjEddwxE0A2kZ3PtasWWOC1X79+pnjqkuXLiaNJ9w5OgDUKgYyQMXk6xjd0aAGGzZsMCdYPdYJdtiwYfbZvXr37t38GgBto7QBUW5suFst1cpqBKDwsaZy5aG7AQ8AoBqogUXF9OzZ0z5qzQ1j6Q95p8YiOnn6E4D0uOMqHLyK7pREHXMqJ3gFUG0EsKgY1Z5KVEfpasjVvXt3TowAAKAoAlhUjGp5NFxl//79W/TlqtuYSi3QWOwAAADFEMCioq6//vrmMdfVeESNSFQz+8wzzwSDBg2yrwIAAMiPRlyoCnWX5XociMqzU62sWkaHeyxQeVSDEwAA0DgIYAEAAJAppBAAAAAgUwhgAQAAkCkEsAAAAMgUAlgAAABkCo24MuKuu+4yQ6iqy6mpU6faUgDVoH6Mp0yZYpf20fE5fvx4eskAaph6wVm5cqUZQEe6detmhi1ntMdsIYDNAB1s/hCrGoecEyRQPerOTcHqpEmTzIlPdFxqkI6+ffsGa9euNWUAaovOpxdccIF5/Ktf/cqcW5ctW2YG0lEf5eqrHNlACkEGvPzyy2auE6O4ZQDV1bVrV1Nro+nss88Ohg4dGqxbt84EuABqz+23326O0SeffNIcszp277nnHnOHs0+fPvZVyAIC2Ax49tlnzfzhhx82c7cMoLZ8+eWXZq7BNgDUHtW06kIzPEiOuxBFdhDA1jjd7lDgqtrXY4891sy1rHIA1TV37lwzJLImHZ+q2Xn88cdJ8QFqkHLXUT8IYGucSxcYPXq0mbt8O9IIgOobPHhwMG3aNDM9+OCD5gLzyiuvDF555RX7CgC1QnnqqB8EsDXOpQuce+65Zn7eeeeZOWkEQPWFc2AnT55syt99910zB1A7SO2pLwSwNcylD4haRuo2peu6hzQCoPYcdthh9hGAWqPUnu7duwebN2+2JcgyAtga5tIE1FWPu02padSoUaacNAKgtqxfv97Me/bsaeYAaotSfT788MNgyZIltmRvZZEqiNwdFGQDAWwNc2kCv/jFL5pvU2oaPny4KSeNAKguvxFXv379gnHjxpkLTqUTAKg9OjafeeYZk6uuY1bHrutnXedaZAcDGdQw15ekgtawQs8BKC/V2GzZssUu7dOlS5dW3fMAqE3uPMpxm00EsAAAAMgUUggAAACQKQSwAAAAyBQCWAAAAGQKASwAAAAyhQAWAAAAmUIACwAAgEwhgAUAAECmEMACAAAgUwhgAQAAkCkEsAAAAMgUAlgAAABkCgEsAAAAMoUAFgAAAJlCAAsAAIBMIYAFAABAphDAAgAAIFMIYAEAAJApBLAAAADIFAJYAAAAZAoBLAAAADKFABYAAACZQgALAACATCGABQAAQKYQwAIAACBTCGABAACQKQSwAAAAyBQCWAAAAGQKASwAAAAyhQAWAAAAmUIACwAAgEwhgAUAAECmEMACAAAgUwhgAQAAkCkEsAAAAMgUAlgAAABkCgEsAAAAMoUAFgAAAJlCAAsAAIBMIYAFAABAphDAAgAAIFMIYAEAAJApBLAAAADIFAJYAAAAZAoBLAAAADKFABYAAACZ0q4pxz4uq3bt2tlHAAAArVUoJEEdqGgA2wg7ZqN8T0Rj+yMN7EfpYn1mA9sJSZBCAAAAgEwhgAUAAECmEMACAAAgUwhgAQAAkCkEsAAAAMgUAlgAAEq0bt0603pe0wEHHBBs27bNPrPPqaee2vyaZcuWmbJS/5/z3HPPBQMHDmzxHsOGDQs2bdpknv/666+bn3PTMcccE9x9993meUfv4/6O3mPatGn2mX38zxr+/0C1EMACAFCi1157zT4Kgt27dwcPP/ywXdpLgeeGDRvsUhB8+umnZl7q/5PrrrsuuPDCC4PVq1fbkr3vsXz58uCmm24yy++9956Z+7Zu3Wqe94NovY/7O3qPu+66y5T75s+fb+adOnUKZs6caR4D1UYACwBAGym4EwWRvpUrV5r5ZZddZuZhSf+fakwXLlxoHs+aNSv46quvTN+pCk613LFjR/OcT8/rde69wkH02LFjm98j/PdUk6vPpnLV8CrI1WcAqo0AFgCANjrttNOC3r17myDQ1WAqLUDBX7du3YKTTz7ZlIUl/X+PPfaYmStYvfHGG4MDDzzQLB999NFmOZxqEOWII44w8w4dOpi5/o/+tt5Dj/v27WvK5cUXXzTzIUOGBGeeeaZ5/Otf/9rMgWoigAUAIAXXXHONmT/xxBNm7oK/yZMnm3k+Sf7fCy+8YOZnnHGGmSsn1eWnalItaZjKDzroIBMUDxgwoPk1l156qQmeVavar18/kyMbrl11NcEKtM877zzzOE6QDJQbASwAACkIB3j33HOPmbvyfJL8PwWbhXz77bf2UTTlzbqGWqq9XbVqlanNVW2vaoGVE/vAAw+Y5136gIJc1c7q9Uol0GcgiEW1EcACAJACBXkuwFPNqMspVXkhSf6falDF5a8qbUD5qwpC89HzmtauXWuW1VDLUVCq9/joo49MLqysWLHCzJ966ikzVyMvV8OrgFZczSxQLQSwAACkRLmi4noDcMvFxP1/Q4cONXO9TjWlqiWV7777zsyTUCqB/x4nnniimTsPPfSQfdSaAln3/4BqIIAFACAluu3vehbQPConNUrc/zd69GhzS1/GjBljcltVM+rXqoa52lPluYqrxVW6gf8eeiwKktWQTDWvSi1wNbhucn/f5eoC1UAACwDISzV0Cm5cXiRaci35XfdVuiXvgs+oINS9vtT/J2+99VawdOnS5kBSFPQq7eCWW24xy8cff7yZ+xSMKtXgX//1X82yHuv/OHo/va+CZBecXnvttWbuc43OFi9ebOZANbTLXU012cdlpR/ACv2pqmqU74lobH+kIe5+pBGU/M7uRQHJVVddFfzDP/yDLWkb5WTqdrXrtilMIz/NmDGjOTdSf3/BggUmIKsVHJfZwHZCEtTAAkBGhYNXUSDptyQvJ+VA9u/fvzl4FT0OjyoFAGkjgAWAjFPrctVcqfW6a0mufMao8fXTpOFK1XJet5410pOmQq3hASAtBLAAUCfU7dL999/fqpGNako1fv4BBxxgbtNqrr5A/Vbk6sBeKQl6Xh3a5+vnU++j1yhPc//99zdlqglWl0uuSyY/1aDQ+yo9QWV6zr2nH3SrbODAgeaz6rGrVdbc/b+o7wKgAeSu2iuign+qqhrleyIa2x9piLsf6XWa1q5da0v2mjVrlinXXHIBbfNr/Wns2LHm+Y0bN0Y+L/57LV261DzW+3311Vfmeb2He32nTp2a/6YUet+pU6dGPtetWzfzvISf8z9DeNL75aPnUfvYTkiCGlgAqGOqAXXdISnFIPe7H/zmN78xzy1cuNDMn3zySTNXAyylAeh1rqsl53e/+11w+eWXm9pdjd7kGmmpxte1iFc6gRp8uVb0+d5XtaWu2yc//UEt6TXXuPw+fV69ZtSoUcE///M/tyjLBclm2X0XAI2BABYA6sz/+l//y8yPOOKIYPPmzeaxukNyIzuFeyh4++23zXzcuHEmMNXrFKT6FFiKgtQwBayuaydxjbryva9yZ0XBbN++fc1jPafx9qO4z6v3cA3X1FBNKQS9evUyywAaCwEsAOQo11IBUZZzKZU/qhxVF+QpIFQQKw8++GBzfqnLQ3Ud57vAdv78+eb763XKW/X97Gc/MzWpCmTvvfdeU6YcVuWfuvcN9z2a7327dOliyjUuv6ttVXdcb775pnnscmujqCZZXA2sm7755htTDqBB5A78iqjgnyobl+u1aNEiW9JaPXxPlI7t33a5IMmsR+VPpknHbb7jNxeUmeeU21lOyhHVVEzc/UivyzcpV1SUq6q/GfUal6+qHNqo58XPgfXfS//HPReetA2l0PsOGDAg8jmVO67Ml+9vuu8SRc+j9rGdkETN1cC6VrK6GvdpWeVRI5RUiqtlKGXM6XrmWgj7k2pZwnls2MuNbKRW1D5XA6j1ptoqdyy4Sa9XjVch+n+qgfNbdmtb+P9Px5KOI/e8HtdSraOGt5Q9e/aYeVrccRt1/Lp+S//7f//vZl4uuv0edQu+VMo79alGVbWkyit1v5W67b5mzRpT7rgRmVxvAbqNr9v/rnZTc5cO4NN7LVmyxDweNGiQyUlVt136u+LeVwMZSKH31WhQ/v/VXMtulKh89Jn1N9x7Zok7LsPnt1qVtc+LBmMD2bKL+6f0Ok26cve51qzuyr4aXI0BV/ot5atJ0aSarUai71yMarFyJ1/zWldLprmWXe1TvporTfn2Px0jrnYsatJ75quNK7RPV5rbn8K/AW2l75jvu7rtofVTTm59FxPnNYivVtan2/7+vq19Tnf33D6oSXcCCh2Tet69VpOOab2H23/TOl+690/7WMxHfwuIKzM5sCeeeKL27Lx9E6L6cj+4ZhspR87VjuzYscPMsY9qse644w7zWOOWq/bTjV/u5j6tU02qnZKXX37ZzMM0PrnrVD53wmn+f8oVzAWF5jV0PN+aape0z6qGUtsGqBTte927dzc9KGgfdJTDrN4c8t3FcjnOjo5pvcett95qS4D6l5kAVgeybmXoNquj26Lh26yaRIGu6zxbk26F+MGvu12rLmbcbRK93r9Vote75/T6WrrNimzT7V0FkTppad9yAZRrkR2mfa9QIxXttzqp6TasWnn776MW3K6sWh3P6/j1j8fw/8tH39v9P/de+q76/ypzndiLXqty/zdBy8WOW/e+Q4YMMXPR93R/018XWjf+7074/f11p0mPSaVBPnEuOgtx/8ddhLpjigofNITcTl4Rcf+UXqcpfMtCyyp3t1jdLdeoSdxtyPDkbrHke97dcnG3YKKmQrd29HyjybcudUur0eh7x+X2aTflglj7TOEUgtzJzb5qH9dAyR0fEv5/rlGUtosr061Hf3/Ot99LqR3P63uFyzXpNmgUtz9pHbjP6vYlHb/+rVY36bX51pnr4F6fRcvh41frQJPPvTbO5BqFabtEPa/JbVu3XEyc1yC+aq1P7Xvat/T3/eNH+6o71vS8Oy/F5b+PuP3VHSfuWHC/B25Zn8EdU/q77thwCn3eStDfAuLKbDdan376qZmrQUDuezTfXs39KJj5yJEjzWM9p9uk7pa263/Q0f/T87riFdd/obp3EdWK6XnVkOkqGfFoXf3qV7+yS4jy+9//3j7aq1i6hdap9tNwH54Sp2GhaxRV6Y7nXQOp3AmxxfGoWmD/jkeYul7SbVEdo/rM8sYbb5i/p/+vud5Lz6tmWV0z6XupTH8nF1ia/+P6Io2iGlOtA/f9w7SO9Hfc74rkggXz/lpH4n6Lpk+fbubueX0OrTtRbTcai2rvdcxo/xJ3/Djr1683c3V15lJXXM29mwodH9KvXz/zOh3DOiYmTZpkn4mmz+AGfNDn0rL7G8U+L1BrMhvAur4NNTKMDmAdlDqZ/uQnPzHlP/7xj81BrecOOuggcxKKcsUVV5gfj6igQE4++WTzvPozJD+uMJ24ddLWSV/BCflY+SkgVG8B4i6+dNEVRcGQJnUUn28/PeOMM8xc/Wi6W9ru/0VRwFapjufde+qEWOx49LnX+KkT4U759f4KbnXLtEOHDsFvf/vb4Kc//an5O2PGjDGvLeTXv/61mV900UVmHqa+T/V39P6OS7fQb4O47+fyEt3z+mznnHOOeYzGs2LFCjN3FzT+RZAkueiMQ8eLu6jKR+dIXYD6F1eusqbY5wVqTWYDWAWoogNSdPWp7l100lAekEZp+eijj8yBqANbQVUpNHyi6D2L5dJh70l7zpw55rEuKlhn0VQrqZoOV7voahRLzVlTUKljQe+pHFRXqxJe/8rfrHTH8+49XQ2sP/mBYdjtt99u1ouCa9WUSrhTfn1GXQjoM+mCSfucGsjpvV0NbD76v+7CN9+FQRL6rKJ1LHp/NyKWgms0JndxGd7Xk150RvHvhmj/00VUoZxrXXDqt6LQxVW+zwvUmpoNYN2tEU1Rt/fmzZtn5h9++KE5gBWshk9COqj1/92BnYQ7iHXyLPU9GpV+IN3Vvbt9jH0UeM2cOdM8drf8XK8ECsbcySwp1z+n9lMNr6n9VrWdYaoJ1f6s590wnK7mRnckRPu9/q/b7xWEum3qjk39XwXMKi90snPv6Wpg3aRAuxBdpC5evNg8Hj58uFkv5513ngk43Qlbn9HdEnXcXZliNbAvvviimbsa8LZSrbD4d3607vR5L730UvNcPXMN39zFBvZ69913zTycDhD3orPS8n1eoNbUXAAbt6Z0/PjxZq4uSHTwa1Kgq4NOJ1vVvujHQfSexW6tOO7/6MdFt1fdsk7SrkaH2pSWOnbsaOb+enHbx9VAYR+/9tXVTmrf1X6qcuVLuhpNt//FoQs4BXZ6X///6X1V+6l9uhodz+s9lRNbyl0Q/V99dq2X66+/3tQcqVN+9176DO676WLABdmuvJCVK1ea+T/+4z+aeTHueztuf3f7f1QH+/rd0efV564U5TIqkHS9K6RFv61633z5wqoVF6VwlIv+tj5DFoIrV8OpCyl9Znex6It70ZmPu5jUPqdjX/to+K5KXHE+L1BTmiok7T+VO2BNa0m1/FULydxJ1vwNlVdTBVcpahDbPxtyJ/ua+L3Ipy37US6INv9f8zTpd1bvm7tIsCX76HdYz+UuaGxJeehv6+/osyTRlvXZFrmLKPO33bpxyxttjyCifVHP6XzmXpu7QGvVQ4BPz7vXatL/1XvovSS8raK2ndtPXC8aEufzlpP+FhBXxfaWtHdMd5CFp6gf10rSZ0DjYvtng7vgTTvIS0tb9qNqBLAKdvScAtlyyloAi2TYTkgis424wrckdesk9yNa9HYmAOhWdO73r8UADiidGh/qNziNxnAAEEdmA1j9UKobIJ2ENKmrHbXmrmSuGQDUOjUMVE6jy11VIyGVRY0mph4q/JHW1ANFsXxTBa/KUfZzYxnJDEC5ZTaABQAUpuBSvTTobpVrqKfGcCpT0CnqccL1FqKeItQYyFHjIg13WohrDDd69Ggz96lBkN5D9L7q3lC9NPh/2w3yoOBVz7vXix6roZLr9g0AHAJYAKhD6sNaXYopeNVgFLo7pdpOBY2y1vYhqt5VXI8KeqxAU+WuI3s/oAxz76dW8FFdqelv6/38TvFn2Y7yGckMQFsQwAJAHXI1qa62U6JGVFPNqas91ehQCix1+z5ON0quL9183RQykhmAciGABYA6pOBRgaUC2XvvvdeURY2opjxV5aUq3UC395V36tfAFvLP//zPZh63L91CVIsrjGQGIA4CWACoU8p7Ve8Aym1VwBo1olp4xDLlx8apgVVeqmpNlSaQxrCjjT6SWVtoIB+tM79BHFDvCGABoE7pNrwb7WnQoEFmrq4G/Vv+eqwR2tQjgLoidFTud1UY5tIHijXychSI+mp1JLMkdFGgwFG9N0g1RkHThYRq1LWtyrme1HOEJlGgrM9TbDhooKyaKqSCf6qqGuV7IhrbH2nIwn6kUcz0Obfa0Z9qWbnWZ3gAh2oMIuFGy9LgHOWkv6HJyQXMZjnNUbr89weKoQYWAJCIav2UW6t0BKUlNKpaGMDB9Spx3nnnmXmluJp31f4C1UAACwBIREFrU1OT6Z6rUSl9QD08nHbaabak8pRaoAsJpVpUOs2iT58+Zv7yyy+bOVBpBLAAACT07rvvmnmhrr7Co6Ap4NRjlSmf1OXOKqdU5W6EMvd/ijXKcrm2Q4YMMXOp1ChoruEeNbCoFgJYAAASUp+5hYRHQVOweMkllzTf8lftresdQv3zqtzvs1fLrvuzfFwKgwuQfZUYBc01uGOkNFQDASwAACmKGgXtjTfeMIGkgj7NNdKYen3Yf//9Tf+8S5cuNWVKzdCIaOIGeYiioFPBaFTwKvrb+jvlHAVNNbuyY8cOMwcqiQAWAIAUKXAUv0Z18+bNZq7+bpVDrKD2/vvvN7fi1aXYb3/72+CnP/2puX0f7ps3yq9//Wszv+iii8w8jFHQUO8IYAEASFHUKGhHHHGEmT/44IPmlrtSCpQjqxSCW2+91aQb3HHHHS1qYPPR/9Xr0+oBodRR0D766CMzdyO8AZVEAAsAQEIusMuXCxseBU3dXGnZpRFopDEFoT6lHcSpgXWDSPgDT7RFqaOguZrmRu5KDdVDAAsAQEI9e/Y083x5qroN74+CpmWNKqbcVFFwOHXq1KBv377BpEmTmnNOXXkhK1euNPN//Md/NPNi9J6+NEZBU48K4j43UGntmnS/ogJ0VVehP1VVjfI9EY3tjzSwH6WrXOtTXVIpz7WS20rpBwo0Nblb+NWgbrpUU6xg+84777SlbcN+jySogQUAoASuBwD1CFApb775ppm72/7V8tBDD5n5qFGjzByoNGpgU8YVZGNj+yMN7EfpKtf6VG6r+krV7Xb1ydoolD7Qq1cvkz6Q5mhs7PdIoqIBLAAAQD4EsIiLGtiUcQXZ2Nj+SAP7UbpYn9nAdkIS5MACAAAgUwhgAQAAkCkEsHXq4osvbu6D0KfyDz74wDx+9tlnzXKYytX5NgAAQC0igK1TK1asCK688spg586dtmQvle/Zs8c8/uyzz8xymMrd2NgAAAC1hgC2jnXv3t2MsQ0AAFBPCGDr2OzZs4OHH344eOWVV2wJAABA9hHA1rHDDjssmD9/vhmx5fvvv7elrSkP1p/mzp1rnwEAAKg9BLA1rGfPnqZfvCRT//797f/e6/rrrw8OOeSQ4NFHH7UlrU2bNq3FNHjwYPsMAABA7SGArWH//u//Hmzfvt107Bx3WrNmjf3f+9x3333BuHHjWjXock455ZQWU9euXe0zAAAAtYcAtgEoKJ00aZKpjQUAAMg6AtgGMX369MguswAAALKGALZBtG/fPnj88cftEgAAQHZlNoD9+uuvWzVgOuaYY4K7777bvqIwvc79v3qkgQiOO+44u7TX8OHDW5Srx4GoAQtUPnPmTLsEJLNs2TJzXGnu0/Hpjjl/UnmUgQMHRr5eEyrH/VauW7fOluwV3iZu0naLknT7N6LrrrvOrJNt27bZkn3Cx4P/Gj32n4uzTv1zoKbw8QrUvKYKSftPrV271rxn1LR06VL7qta2bt3a1Lt37xavT1Oa79e1a9em7du32yVkQdr7U9aMHTu2+bgqdBw63bp1a5o1a5ZdKm7AgAHmb9S7WtmPtL7d9tRvbjFxt7uTdPuXqlbWZyFaF25d6zzl03bQ5LjjzNFz/vbRc4WOE61z//9rm2k5zjYuJ/8zAcXURQpB7nsEX331VXDZZZeZ5U8//dTMo+zYscPMcwewmTeCH374IVi0aJFdAspDNTgLFy4McidfW1KYavT02ksvvdSWFKZaptWrVwdXXHGFLUE5qYZO6zvu9nQ1eMOGDTPzYpJu/3qmmlfJBZBm7nP7/S233GJLAtMoV9w6X7VqVdC3b1/zWHR+e+GFF+xSaw8++GCLc6C2WS6ADp544glbAtS+usyBPeKII+yj1nSQv/XWW8EZZ5xhS+rfrl27GipgR3XoJKiLyaOPPtqWFHbHHXcEY8eOjf16jSw3YMCAFidqlM+NN95otmdcCrCS/M4k3f717P777w8++ugju9TSm2++aeb+fq91poAzX2XNxx9/nDeNQAGxLhzC58Dzzz+/RVoCUOvqIoBV/s5BBx0ULF++3Jzg4tYAAKgO1b4lqU3ViVW1uyNHjrQlqCWqCUxSm5p0+yMZHSvnnHOOXQLqU93VwOpHUaNJiQJZP0l906ZNphxAdelWZZLa1KeeesrUOHFxWpsWL16cqDY16fZHfEpH0LGiGnSgntVNDqwmlz901113mTmA9Kk21L8wzNfqPJ9SalNvuumm4Nprr7VLSJNqQ/3t6fIx46I2Pb5yt/zX+2vd5ktHAOpJXebAOvpxcMGtphNPPNE+A6BUqmXzjys1IEkiaW2qO8lTo1QeqgX1t6fyMZOgNj0+l1fspjjr4Cc/+YmZ60LB0UVAOI9Vwasu9Io1unO15K+99pqZO2r0RdoBsqRucmA19evXzyzrxzQfV9vgXitaPuCAA+wSgHLKV5vqjs1wrZQaB+n2NGpPodpUbUdtTz/wEmrTk9GFgQJ+NXpz1KBRZe6iwQ9eo9I4XM2vtpfoeNLrHW2rJDnMQC3IbAB7/PHH20f76IBWK9h//dd/tSUAKsUFLJrk8ssvN4918nTc47i1qe7E6roNQuW4oEe/q6KLfi37FxgukIpbm5p0+zcKN4CBq1jROtWyC/6VEqA0DZVpUm2pnybgglH3/9zkbyufatlV0eNep2M1X/AL1Kp2TbqPUQE6SCr0p6oqze951FFHBWvWrAm6du1qS0qjLlX69+8fbN++3ZagXBplP0d5sR+li/WZDWwnJFHXObAAAACoPwSwAAAAyBQCWAAAAGQKAWwFbNy40T5K5osvvjB5sMoLasuk9/i///f/2ncFAADINgLYMtu1a1cwdOjQ4IcffrAl8Vx99dWmpagS2tOY/vCHP9h3BgAAyDYC2ApZtGiR6Qngb/7mb/J2beIoeD3rrLMY9x0AACAC3WilLOp7vvLKK8EzzzwTDB482HSJVahLK4LXbGuU/RzlxX6ULtZnNrCdkAQBbMqKfU/VviqYXbp0qS3Zh+A1+/gBRhrYj9LF+swGthOSIIWgwpYvXx5cdtllZnCBmTNnBuvXrzfl9913H8ErAABADNTApqzY91Q6gWpaRcMvrlq1KnjkkUeCXr16mTJkGzUISAP7UbpYn9nAdkISBLApi/M9v/3226Bjx47m8UknnUQAW0f4AUYa2I/SxfrMBrYTkiCFoApc8Or6hyV4BQAAiI8Ator2228/Uxur/FcNNqAutpRSAAAAgPwIYKtg4sSJwcqVK4MePXoECxcuDD755JNgzZo1wfPPPx/MmjXLvgoAAABRyIFNWbHvedttt7WY+xTYHnnkkcGECRNsCbKGHC6kgf0oXazPbGA7IQkC2JQV+p6Fglc5/vjjgxUrVpjH6i924MCBQZ8+fcwysoEfYKSB/ShdrM9sYDshCVIIKqRY8CqjR48OTj/99GDo0KFmWV1uAQAAoCVqYFOW73sq53XIkCF2KT+/iy1kDzUISAP7UbpYn9nAdkISBLAp4wBsbGx/pIH9KF2sz2xgOyEJUggAAACQKRWtgQUAAMiHGljERQpByrgF0tjY/kgD+1G6WJ/ZwHZCEqQQAAAAIFOogU1ZJb7nCy+8EPz1X/+1XSrdX/7yl+D888+3S0gDNQhIA/tRulif2cB2QhIEsCkr9/ecPHly8PTTTwdHHHGELSndp59+Glx88cXBPffcY0vQVvwAIw3sR+lifWYD2wlJEMCmrNzfM86ACHGl+V7Yix9gpIH9KF2sz2xgOyEJcmABAACQKQSwAAAAyBQCWAAAAGQKASwAAAAyhQAWAAAAmZL5AHbdunWm5aKmu+++25YWtmnTpmDYsGHN/0+PVQag7ZYtW2aOK83DrrvuuubjTpOO30LCr496T5SXflejtpW/Xfxp4MCB9hUtHXPMMZGvVzlaC6+vbdu22Wda0vrW88WODbcd3cSxhKzLfAA7f/58M+/UqVMwc+ZM87iYXr16BcuXL7dLgXl8ySWX2CUApVLAefnll9ullvTcwoULTTc5mpYuXRr069cv74nZnWD91+u9870e6VNwdNNNN9mlltx28ScZOXKkmYd99NFHrV7frVu34Nprr7WvgKPgVYPMuPU0a9Yss67CdIxovRaj4FXb0b2fO5aKXUACtSzTAezXX39tgs/LLrvM1KLu3r07eO655+yz+fXu3TtYu3atOZAXLVpkyrZu3WrmAEqjk6kC1HzHkp7TidPRMauT8lNPPWVLWtLz999/v10KgtNOO83Md+zYYeYoLwU9q1evjv3b6C44tN3iUPCk97700kttCRytlzPPPNMuBcEZZ5xhH7V0yy23BIsXL7ZL+T344IMmCHbcsffEE0/YEiB7Mh3Avvjii2Y+ZMiQ5oP917/+tZkX8tZbbwV9+/Y1j3v27GnmANpGJ0VdFB599NG2pDjVNH388cd2qbDZs2ebk647dlFeN954o9mecSmY8oOkYu64445g7NixifaXRjFgwACzPh23rny6wNDxU+x40B0LBcThIFg1vNzNQJZlOoBduXKlmatm5rzzzjOPk+b1uBSEqVOnmjmA8giflKXY7U8/B/aFF16IdbsUlaff3SS1qap9Ve3uFVdcYUvgW7VqVYscWAX5/t0IUUpA+HgCGklmA1iXPqB0AB3cBx54oEklUBqBC2IfeOCB5h8ATVr26XXuPe68805b2lj2228/+wgoL52UFeT4x6RO0oXopO3y9lQLpf9D3l7t0W3sJLWpunWtCxpq06OpZlQBvtaR7joo/cavnNGFndY36w+NLLMBrMub27BhQ/PJ0DXMcjWzhUybNs0ksSvo1Ym1EezcuTNYsGCBmcuECRPM5MqdZ5991kxhKnv77bftEhqVTq7umNOUr9V5FBeMukm6du1q5sUoRUEndPL20qULAn97KjhKImltqvYfBWT5Gns1EgWl/rpXWoDWj4JW5Yvr3KS7Dn6jK7f+Jk2aZN8FaFC5k0hFpP2nevfubd4z3/TVV1/ZV7aWOwma10ydOtWWpEfvW07Tp083Uylywb75fKNGjbIle7lyZ+jQoWYKU9n8+fPtEqKUe/tnhdZD7qRrl6Jt3brVvG7t2rW2pDgdu2PHjrVL9auW9qNi20nbQ9slrlmzZjXlAjS7VBlZOi513ER9XpXpOfd81JRvveo5rXefXhsuqzZ9TiCuTNbA6gpUNa+6Ss19hxaT0gHENfAKc7UFctddd7W4+g2nGNSrhx9+mJpUVJ2OX/82qKsJdLdKVRPo3zZNWtOH8itUm+pqF7XdfMrdpOus/H7yk5+Yub/vu8d6zjWW9CdRLa3LEXd9vmr7iI4zvzs0vV+SnGWgFmUygHXBadSP4DXXXGPm+boW2X///e2jxqWGa7od9f3339sSoO1cwKJJtI/psU6m4jfI0qQW6+GGKT7dInXvoUl9xqr7O/L+KsMFQbrQEK1/LfuBlesZIm7XWW5fUA8HiKb9W/u5v+/rcVv2fR1nSr/x308BLD1AIMva5a7e9l6+lZkOmgr9qaoq9/e87bbbWsyTUK2raqj1+Y499tjghhtuCK6//voW5XLxxRcHmzdvNs/75s6d2/x/EK1R9nOUF/tRulif2cB2QhIEsClL8j2//fbboGPHjnYpnp/97GfBa6+9ZgLQJHT76OCDD24OVF3Qqk7hNRHApoMfYKSB/ShdrM9sYDshCQLYlCX5nieddFKwYsWK2K2wN27caHKZ1HPAIYccYkvj6dGjR/D555+3CFQnT55sbiOpR4ZwACtPP/20mTsqP/fccwlgC+AHGGlgP0oX6zMb2E5IggA2ZUm+Z6dOnUzivQJTNU4ZPXp03lwyvWbixIkm4E1aa+uEUwWUA6ucYPWBqyDWlRPAlo4fYKSB/ShdrM9sYDshiUyPxJV1ar2rhizfffddMH36dBOgKq0gLI3gNUr79u2Dxx9/3ASvAAAAWUEAW0WqbV2zZk0wY8YMc4tfwgHq+vXryxK8OsOHD6dVNwAAyBQC2BqxaNEik0Ig6qbGjQ72yiuvpBa8dunSxXShFaZ+Yf1y9ekY1a+jyvr06WOXAAAAqoMc2JSV+j2VJjB06FDzWEHi+++/b3oOiNu/ImoDOVxIA/tRulif2cB2QhIEsClry/fctWtX8MMPP5heCWbOnGlyY5VegOzgBxhpYD9KF+szG9hOSIIANmVpfE8Fsccff3zw+uuvB507d7alyAJ+gJEG9qN0sT6zge2EJMiBrSHKd3W9ECiIXblyZfNwgqqRBQAAAAFszVCjLY10td9++5lJ/cNu2rQpGDx4sLkiVXdbUV1sAQAANBpSCFJWyvdU8PrAAw+YoFXBa5hqZm+//XbT5RZqG7fAkAb2o3SxPrOB7YQkqIGtsmLBq2iUrgEDBpga2Pvuu890uQUAANCoCGCrSP29FgteZcSIESa94Kijjgo++eSTYMuWLabHAgAAgEZECkHKknxPBbBDhgwpGLwiW7gFhjSwH6WL9ZkNbCckQQCbMg7Axsb2RxrYj9LF+swGthOSIIUAAAAAmVLRGlgAAIB8qIFFXKQQpIxbII2N7Y80sB+li/WZDWwnJEEAm7Ja+p5r164N/uM//sM0EuvTp48tRTnxA4w0sB+li/WZDWwnJEEAm7Ja+Z7qX/YXv/hFcMwxx5hhadevX2+f2efss8+2j/Y566yz7KN9FPweeOCBwamnnmpLkA8/wEgD+1G6WJ/ZwHZCEgSwKauF76mA9fjjjw9ef/31oHPnzra0NY3wFRZVpvfZuHGjGdq20PuBH2Ckg/0oXazPbGA7IQkC2JTVwvccO3ZscOKJJwZjxoyxJW2nEcA0iMKcOXNsCaLwA4w0sB+li/WZDWwnJEEAm7Jqf0+lCkycONHUmqYpbq1uo+MHGGlgP0oX6zMb2E5Ign5g64iCTNW+PvLII7YkPWoIdsMNNwSzZs2yJQAAANVBDWzKqvk9b7vtthbztFELWxw1CEgD+1G6WJ/ZwHZCEtTA1gk1slq9enUwZcoUW5I+amEBAEAtIICtE0odUAMrBZnlpIZhyrNVwAwAAFANBLB1YObMmaZP10oMVqAA+aabbgpuv/12WwIAAFBZ5MCmrNLf8+OPPw4uuOCC4J133il77avvpJNOMo3FevXqZUsg5HAhDexH6WJ9ZgPbCUkQwKas0t/z22+/NVPXrl1tSWWsXLkyePTRR4MVK1bYEgg/wEgD+1G6WJ/ZwHZCEqQQVNHFF19spjCVLViwwDx+++23zUH97LPPmmXHlXfs2LHiwasMGTLE9ESgngkAAAAqiQA2IwYPHhx8//33dqn69Fmuueaa4P/9v/9nS/ZSuYJr54MPPjBTmMp27txplwAAAOIjgM2IoUOHBvPmzbNL1bdly5agd+/eJo3A58oddesV1bWXyp5++mm7BAAAEB8BbEaop4Fp06a1qN2sBePGjaMmFQAAVBQBbJWpEZRyWf0pqmHUscceG9x5553BhAkTbEltmDRpUnD99dfbJQAAgPLLfAC7adOmYNiwYc3B36mnnho899xz9tnWvv766+C6664LDjjggFivLzelBqjVpT+pLMr48eODL774IliyZIktqb7p06ebgDvcyMz35Zdfmppjf1IZ6tOyZcvMsaV52N133918rGrSciEDBw5s8fp169bZZ1ApbpuF172/XfxJ2yyK2y/CE6Idc8wxLdbTtm3b7DOBeew/p9fGpfOf/k+xYw+odZkOYBW89u/fP1i+fLktCYINGzYEF154oV1q7ec//3mwcOHCYPfu3WbZvd7/cahV7du3Dx588MHgyiuvDPbs2WNLq0uf6fHHHy/YyEwnPtUe+xOBSH3SyfHyyy+3Sy3phKlBMNyF2tatW81yVKArKj/66KObX6/R5vr162efRSUoGNU2iuK2iz/JyJEjzTyfqP+DlhSQnn/++c3rSMN3d+vWzT679zhbu3Zt8/M6llRWjH53df7z3wvIqkwHsJdccokJRNVoSAewDmQd1H4jojB1O7V06VLzWn841B07dthHtU0jbqmG9tprr7Ul1Td8+PCCjcz0nBps+VO+WmZklwJOnRx1LEbRoBsDBgywS4EJTgudSHVn5f7777dLe9NVhIufytAFx+rVq/NuzzB3IaLthrbROj/zzDPtUhCcccYZ9tFeq1atCvr27WuXAhPgvvDCC3YpvzvuuMOc/4B6kNkAVrWv7odVNbA6GYoO6rfeess8jqIfWfcD62oxO3XqFBx//PHmcRaoj9gPP/zQLtUG18jsvffesyVoNDqudGHojsUwnZAVELkAVMeijuG4AY+7yOzSpYuZo7xuvPFGsz3juuWWW0wghbbThZ7Wp6PAU3cg8tHFYbE0Ah1vH330ERcYqBuZDWBd8Kna1nwnzHxc3pBuRyp4Vf7mgQceaJ+tfYceemgwf/58u1QbXCMzpTcAUXTiVO2Pjjsdf0o1SBIgPfHEE6bGNunxjvJzFyOXXnqpLcnP/f5qcrW2aEk1rH4OrPZ5/25EmO58nHPOOXYpmgJiBcJAvchsAPvHP/7RPsrPNdTSpMdRlIKgnK1q5MC62+lhKnMt+0855ZTIk7yeT3LyrwQ1MgMKWbx4sZm72qR8DX7CXO6e+/+oLdou2qaFLi5cDb2bdDGjixhSQlrT+Uh3K1QTq4s27fv5gn3lvuo1qjHPR+kgCoipfUU9yWwA++Mf/9jM1QhLPQsk4X5AVWPg8mdnz55tn0Uc+++/f6s8VjXoWrNmTYtyrd+onGSVHX744XYJWRJuAR03CHWv07Gn2iTNdZIu1vhEf0+1tgp4/Lw/pEMBpL894zQG8un/azteccUVtiQeBVMKvF577TVb0ngUlPrrXoGm9netF+3vqonVbf98wb5er+BWrylEDfH8lASgLuROIhVRjj/VqVMn8765YKgpF4Saso0bN5rlfPTc2rVrzWP9n9wVrnmPyy67zJS1VQVXqfHII4805YJGu4Rqq/T2r1VaD7mTrl3aK6ps7Nix5hjMR8eo/t+sWbNsSWOopf3IbQP3uxlWbBsWkgvUKrJta2l9FqNjJOrzqsw/frTeVObOfflou+l1+aZaUmufB7WtYntLOXZMd6BHTflEvVZTvh/npPRelfTOO+809erVyy5Vzvbt2+0j+Cq9/WuV1kM4WFWwEg509DoFQOJOtO7/NWrwKrW0HxUKYN1z4W0t7vfZ/T9tez/YihuApaGW1mcx4eNAwuuy2Lor9nylLhySytJ2QvVluhst3YL6zW9+06JrHt2aVlk+uR+AFq/XY70+q7cmc8Fr0LVr12DlypW2pPzU/RjdYCHMvx0quuXpbouKbnNqcq/RpLzJfI1TXFqPbn/6/yduygLaRttN61u3s8U1vvNzMbWN9Hyc3Eq1NdBr3XZ0fQLTKK8lnYt0nnLHjyY9Vpk7T7m+ef31qYlGcWgk7RTF2sdlpYOrQn+qqqrxPRVQXn311cE777xjS8rnhx9+MINHKO9KwTNaapT9HOXFfpQu1mc2sJ2QRKZrYLGXAklNlWihfd9995nBFAheAQBAtVADm7Jqfc9du3YFp59+uhlIYL/99rOl6Xr//ffNrazXX3+9bH8j66hBQBrYj9LF+swGthOSoAa2TnTu3DkYMmRIsGjRIluSPuUrzpkzh+AVAABUFTWwKavm9yxnLawCYw3fq9xX5EcNAtLAfpQu1mc2sJ2QBAFsyqr9PSdOnBgceeSRwYQJE2xJ2ykwVsMtpQ507NjRliIKP8BIA/tRulif2cB2QhIEsCmr9vdUsKnhZx955JHgr//6r02ZamP79OljHpdCXWaNGDHCpCigMH6AkQb2o3SxPrOB7YQkCGBTVu3vqW6ujjjiCDNpuFdXtn79evPYp54EwjWqWj7xxBPtUhBs2bIl+I//+I/gySeftCUohB9gpIH9KF2sz2xgOyEJAtiUVft73nzzzUGHDh2CKVOm2JL81H/st99+a5f20rLKnY8//ji4/fbbTVoCiuMHGGlgP0oX6zMb2E5IggA2ZdX8ngo81VPAmjVr6CmgSvgBRhrYj9LF+swGthOSoButGqchYt0ABUoFUI5rPhqNS70EELwCAIB6RgBb49544w1zG1+DCKiLrJNOOsmMhhU2c+ZMM0Y8I2QBAIB6RwpBytL+nqpxVS8Ayk1dsWKFKdOy+nr1aYQs9TxA7Wt1cQsMaWA/ShfrMxvYTkiCGtgapxG21P+qAtYePXqYmljNRcHtbbfdZoLbpUuXErwCAICGQACbMQpolVKgkbE0uMCf//xnUyOr/FgAAIBGQApByirxPdWoS7mxM2bMMMtHHXVUsHv3bvMY1cUtMKSB/ShdrM9sYDshCWpgM2jkyJGmtwENOqCus1zDrVWrVplaWTXoAgAAqFfUwKasUt9Tea8KYJU6oKBVtHzTTTeZvmDV4MvlyqJyqEFAGtiP0sX6zAa2E5IggE1ZJb6nglZ1p6XGXQpaFcyqcVefPn3M8506dQq2b99unlO+bNeuXU05yo8fYKSB/ShdrM9sYDshCVIIMkjDxY4ePdoEqKK5C15dYy71SKDXqXZ24sSJpgwAAKAeEMBmzPr16800YcIEW9KSAtfp06ebWtgOHTqYmtg5c+bYZwEAALKPFIKUlfN7unxXNeBixK3axC0wpIH9KF2sz2xgOyEJamAzRL0LDBgwgOAVAAA0NALYDNEgBlOmTLFLAAAAjYkUgpRxC6Sxsf2RBvajdLE+s4HthCSogQUAAECmEMACAAAgUyqaQgAAAJAPKQSIixzYlJHD09jY/kgD+1G6WJ/ZwHZCEqQQIJYtW7bYRwAAANVFDWzKsv49N27cGHz88cdmvmnTpubHhx56aDBr1qzgyiuvtK9EFGoQkAb2o3SxPrOB7YQkCGBTlpXvqeFoFZy+//77wRtvvBHs2rXLBKoaJKFr167BiSee2PxYc40CdsEFFwQzZswI+vTpY98FYfwAIw3sR+lifWYD2wlJEMCmrNa+5yuvvGKCUxeouqBVQaiC0+OOO8481iAJxUb40vsMHTo0WLp0qfm/aI0fYKSB/ShdrM9sYDshCQLYlNXS97z22muDV199NTj55JObA1UFnj169LCvSE61tGPHjg3WrFkT7LfffrYUDj/ASAP7UbpYn9nAdkISBLApq6XvedRRR5lAM+3a0pUrVwaPPvposGLFClsChx9gpIH9KF2sz2xgOyEJeiGoU0odUOBajlv9Q4YMMbW4M2fOtCUAAACVQwBbp1RDOmLECLuUPjXmUk6tamMBAAAqiRSClNXC91SPAer2aufOnWXNU9Xf6d+/f7Bw4cKiDcAaBbfAkAb2o3SxPrOB7YQkqIGtQ8uWLTO3+cvdyErvrx4J1KhLPRQAAABUAgFsHSp3+oBPObZz5swJLr/8clMjCwAAUG6ZD2A1WtSwYcPMrQdNp556avDcc8/ZZ/PT/3P/54ADDrCl2ad+XjWdffbZtqT81D3X6NGjg6uvvtqWoJHpDoCOK819xxxzTPMx508qL2Tbtm3mddddd50tQSXdfffdZv2vW7fOlrQ0cODAFtsz3+scbUf/9eH9pNFp/fnrx5+0LSS8DjVpOxQSPv50XAFZlukAVkGocjCXL19uS4Jgw4YNwYUXXmiX8rvmmmvsoyDYvXu3fZR9ixcvrljtq08XEaqNpWeCxqYTq2rjo3z00Ucmv82funXrZvorzkfBjV6D6lBQdNNNN9ml1hQUHX300S22ad++fe2zren9FDj5r9dvB/bR+vPXj6a1a9ea5y699FIzlwEDBrR4zapVq+wzrem4vOOOO5pfq7Sv888/3z4LZFOmA9hLLrnEBJ+9e/cOtm7dag5MHehaLuSBBx4wgW6x12WR0gdGjhxplyqLngkam4JNNejTsRiHapr0Wv+k7FOgo2BYedY6WaOyVNu3evXqvNvT1Zzef//9Zl6Mtrfer1CghWhPPPGEOQZ0sVAKbSP/QuHMM8+MfZwCtSqzAaxqX90BqBpYd2Dr6vWtt94yj6N8/fXXwc0332xqdW6//XZbWlvUIOq+++6zS/GVs+/XuBRszJo1y4zYhcaiE6QuIuOeZFUjpJqgfK93NXvU0FXHjTfeaNZ/Prrbk6QWzwVhSEYXcrowvOWWW2xJ2+m9dOwBWZbZAHbPnj1mrlrUJFelt956q6m1nTdvXvDjH//YltaW008/vaRuqSrZeCsf1zPB4MGDg2+//daWAi252rgrrrjCliBrlBLi8pPdVCgP0+Vc+q8vlv+MIJg9e7apcAmnZuj48delW7/5+DmwuvCIW3MO1KrMBrB//OMf7aP81DjLHbB6rFpbXcledtllwT/8wz/YV9UW15JfwZ8aY8Wl/6db97VQW6UgVp+nY8eOtgRoydXGFcqXRDaoltZNCqpcQ6Mo4TxooXFeYTpn6W6FT8Gnvx5Vm1osV9xf96LzIpBlmQ1gXe2pclmVFhCHflxFKQc6ePv162eWpVYOZgV/jzzyiKlNVQO1uC109bpK9P0ah24t/rf/9t/sEupNklq3KO6WaLVytdFSuNV7koDynHPOsY/2UiD18ssv26XWwikHasD3wgsv2KXGo99tf92Hg3+3XKxiYtKkSWaubRmHq32Ne34BalFmA1jV3HTq1Mk8di1bRbWs6kpLvvnmm+YrTj3u0KGDKa916gJrxYoVJpCdO3euLS1MDdPUlVUtqIVUBpSPy011U9JGOU899ZSpLSK3tTaEW73HvbWsYDR8l0i/w/lSuhTshm9z6/83chqByxt3k/KOfQ8++KBpUwCgtcwGsOJ+aFULqxOirmCVO6rlKArw/B8L1zWJaLmWLFq0yNRmTJ8+3Zbk9/7775uUA/XHWm3r1683qQM9evSwJUBL6pYpqussVxNIrVA2qCW7atJdUBrOa3a1i65W8IwzzjDPu2Vq4gvT+svXS0c46FetuZ8nq5pbrXu3bfR6/+Ihbs0uUNNygVtFlOtP/eY3v2kaMGCAeX9NvXv3NmVxbNy40fyfTp062ZK2S+N7vvPOO025ALBp9+7dtqSwKVOmNM2YMcMuVdeYMWOaciclu9R4yrWfZ8HSpUubj0N/mjVrln1Fk3mssii5C0rznN5HcifvFu/jJh3v9U7fs9rctgpPbvtI+DX+c25/0HZ1wvuIv2+Uk/5W1uQC0qaxY8fapZZU7q/H8DHhtouOIQmvd021qFY/F2pTO/2T22nKTleDFfpTVZXG91Q3WuqJQLfhldca1SOBalzVVZWmadOmmSv1zp0722erQw23jjrqqOC9995r2AZcjbKfo7zYj9LF+swGthOSyHQKQb1SIKr8Vxk6dKjJMVTAqpQCNez6m7/5GxMoqh/bTz75xAS4tTB4gD6D8nfpfQAAAJQTNbApK/V7qtZVuaya+3lJGnRBNZsa5Uo5URqkQLmufm8Del6BrnILFUBWywUXXBDccMMNiVul1xNqEJAG9qN0sT6zge2EJAhgUxb3e2rULHXnpaDVb/ikvjGnTJlialw1jKbrVqtYraZer9pZ9V5QjZG4FHifdNJJwc6dO21JY+IHGGlgP0oX6zMb2E5IggA2ZXG/pwJYBa8KWsM1qqK+VF999dXmVII49H5XX3118Pzzz1f8Nv7MmTOD7777ztQUNzJ+gJEG9qN0sT6zge2EJAhgU5bW91QwqlvySgnQsKxqzBWH8mXVd6yC2ErSZ50zZ07Dd5/FDzDSwH6ULtZnNrCdkAQBbMrS/J4uvWDWrFnB0qVLI3sjiEJtaPXwA4w0sB+li/WZDWwnJEEvBDVMtZlqEKX0AjXUiks5tBrhJu0O4d9++23zA/Pss8/akr1cuXPxxRebKUxlCxYssEsAAAClIYCtYcqTVcMs9S6QdJQt5c5qeFnV4KZNKQ3ff/+9XQIAAKgsAtgapl4K1C1VKcP9qdZWaQcTJ05sNV55W6nLrnnz5tklAACAyiKArWGjR482/cCqFla9EiSlARE01ri640qSglCMcmw1+pdSBwAAACqNALaGqdGW+lWdPn266VlAfb0mpfdQCoKC2LQce+yxwZ133hlMmDDBlrSm/miVF+tPKgMAAGgrAtgap1QAdaX1+uuvl9y3q7rg+ulPf2pqc0uh2lsNVOAbP3588MUXXwRLliyxJS0pzUCtSf1JZQAAAG1FAJsR4YEOklLPBOqWa+XKlbakNQWqaji2aNGi5tSFQw89NOjUqVOrFIb27dsHDz74YHDllVcGe/bssaUAAADlRz+wKavl76kAVUGp0hH+/d//3QS0n3zyiempQI+VoqDeDtR915FHHtn8WLm0opzX3r17t/h+6hpr8+bNwYcffthc7rrQevrpp83cUfm5554bXH/99bak/jTKfo7yYj9KF+szG9hOSIIANmW1/j3VI8EZZ5wRHHfccXkD1XyiAljl6Hbp0sU8duUEsPW/n6O82I/SxfrMBrYTkiCFoMF07do12LFjR7BmzRrTQ4FSC5RjWyx4zUcpBvPnz7dLAAAA5UcNbMq4gmxsbH+kgf0oXazPbGA7IQlqYAEAAJApBLAAAADIlIqmEAAAAORDCgHiIgc2ZeTwNDa2P9LAfpQu1mc2sJ2QBCkEAAAAyBQCWAAAAGQKASyK0gAES5YssUv7qPyDDz4wj5999tnmAQx8Kr/rrrvsEgAAQNsRwDaIhx56KFi1alWwa9cuWxLfihUrgiuvvNKMuuVT+Z49e8zjzz77zCyHqXzDhg12CQAAoO0IYBuAglbVgt59993BSSedZEbPuuCCC4LbbrstWLlypRletpju3bsHt956q10CAACoHgLYBjBr1qxg/Pjxwcsvv2xqUd95553ghhtuMM89+uijQf/+/YNOnTqZuYLaZcuWBe+//7553pk9e3bw8MMPB6+88ootAQAAqA660UpZrX1PBaKXX3558Prrrwf77befLW3t22+/DTZu3GgC1C1btpjHS5cuDXr16mW+k9IA1q9fH8ydOzf43e9+F7Rv3765/JRTTgkWLFgQjBs3Lhg6dKh9x702b94cnHDCCcHTTz9tS+ob3cAgDexH6WJ9ZgPbCUkQwKas1r6nAsoRI0YEQ4YMsSXJ6Tu5QLVfv37BsGHDguuvv75FuQtgw/muqs3dunUrASyQAPtRulif2cB2QhKkENQxNdr64Ycf2hS8ht13330mUA036HIUzPpT165d7TMAAADpyGwA+/XXX5urNX865phjTEOlQlQjGP5/mjZt2mRfUT9uvvnmYMaMGXYpHQpKJ02aZGpggSjuGNM8ynXXXdfi2Mv3Ohk4cGCL165bt84+g0rRb2qhdZ9kG+k32n/ttm3b7DMI89eT1luUYtvGca+L855AVmQ2gH3vvffso310q/qmm24qeEL89NNP7aNsKKXbK1m0aFHQp08fk8OatunTp0d2mQUoOFXOdT4KdhS06Dahm5SSEkXH8dFHH938urFjx5oUFlSOtpd+U/NREORvI019+/a1z7akIOraa69tft2AAQOC888/3z4LnwJM7e9uXWk9a1v4im2bsG7dujW/n6aPPvrIPgNkU12kEOhg/Oqrr4LLLrvMLMcJUtUy3z+YTzzxRPtMbVCjqqOOOsp0c5WU0gb0/RRoloMacD3++ON2CdhLAefChQvNhWQU1RKtXr3apLbEocD2/vvvt0uBqfkXamErQwGntle+7ekqCvxtVMiNN95oJueWW24x700tbEtR61XrStvCrati2wZoBHWZA3vEEUfYR/npylVXuQcccID5Mag16g1AtadjxoyxJfHdfvvtwejRo4POnTvbkrZRw6zjjjvOLu01fPjwFuUahSvcgEtUPnPmTLuEeqaAUxeDqpGL8sQTT5hat1Lt2LHDzLt06WLmKC8Fm9qe+SxevLhNNai///3vzTzf/oJ93D7vjoFi2wZoBHURwCoQPeigg4Lly5ebE2S+W5ISDm53795tgtlaC2J1e0jpA8cff3yivlf1f3QFP2HCBFvSdsp7Va1rmF+uwRG0HKbyY4891i6hkbnaI5eDpylJHp4CYN0GJeCpDboFrW3qb8/wbe5CFAC35YKmXp122mlm7p+TXODaFqqt9bcVdzKQdXVXA6vbKtOmTTOPFcj6B6waarlaIk1+2oE6+a8l6rNVfbcq11Q5hUopiEN5U3PmzCnY52tb6Rawu80FJKGgxx1/rgZJebPF6GSr9AQFPagt/vbU72+cygD9fui1cdMPGoku0NQHt7tLqOmOO+6wz5bG1di6SSlmyicnfQNZVjc5sJrWrl1rljVsahwHHnig6RKqVqk2VTmwCkY7duxoS/PT4AMaFjbNbrOiKJh+5pln7BIaTVtq3cK3nNWo54UXXrBL0fT3dLLVST1fAyGUThcH/vaMc0HhnHPOOfbRXrqALlYZoL+ni3L9Xjd6bboCeX/du+Dfr2jR5AL9tNJnXC7ym2++aeZAFtVlDqyjHwf/R0ANtfTD8Nxzz5nn1RXX/PnzzeM4AWIlKXg9/fTTg++++87UxMZx9dVXB4888ohdKh/17apAGY1JQYd/XMVtlKVgJ1zjo/2oUBqBXq+0AdUYFUoNQul0UeBvz7i1oroYCf8OaHsVCkoVvHIxsk84UPUbufmeeuop0meAsNxBUxFp/6nc1bt5z6hpwIAB9lWtXXbZZZH/R++XBr1XGtasWdPUp08fu1TcihUrmoYMGWKXymvnzp1NnTt3tkvwpbX9s07rIRek2KW93DHrjrWtW7e2eJ173i2753PBq1luJPretcJth/BvpLaTyvW8hLeve94th7dvJenvZlV4PfrybRsdMyp32yYX/Jq5M3bs2JpcJ1neTqi8iu0tae+YX331lXlPf9JBqgNXz+Wj59zBq0kBbdQPQ6n0nmkZOXJkU8eOHZtmzJhhS6L96U9/auratasJLCtlv/32M38XLaW5/bPGnWjDkx+Ahl/jPxcOcPzj1J8KXaDWC33PanNBUHjyA9Dwa/zn3LZ2v6/abv5r3aTtXG76O1kSXkcuEHWKbRv3vPt/4deHA9paoc8GxNVO/+R2mrJTfk+F/lRVpf09lW960kknBWvWrMk7LOsNN9wQ/O3f/m3qo24Vot4R1MCsR48etgTSKPs5yov9KF2sz2xgOyGJus6BzTrll2k4WOXnKnhVIy0t9+/f30w62DU99thjJl+2ksiDBQAA1UIAW2Xvv/++6edV3QPddtttpiGWltWIS0GqGp6p9tXp0KGDGWFLk65UNe3cudPUvirArRQCWAAAUC0EsFVy3333mdrToUOHmpGzXn31VVN+1llnmRG4FMCq5lVdFLkeElQ+ZcqU4OyzzzaTo262nn/++WDixIkVC2KPPPLI4JNPPrFLAAAAlUMObMrS/J6LFi0y3QcpcFW+aTGqEXVdaeXLl02LuihTX7BLly61JZBG2c9RXuxH6WJ9ZgPbCUlQA1vDxowZE2zfvt3Uxq5fv96W5qegVcGrgthy394nhQAAAFQLAWwNUy7sBRdcEPzwww+mFjYOBZYaSlZBbNzhZ0uhv7N161a7BAAAUDkEsDVKta4KQtVF1jvvvGPyXONSsKsg1gW/adL7qcGZej34+7//e1sKAABQOQSwNa7UWlQFseqpQGOOpxHE6nPMnDnT9P+qBmfqGUE1xAAAAJVGAFujOnfubPJZ1VBKAxmUEoSqB4MRI0aYILZUqglW7wb6DN99913w+uuvV6SRGAAAQD70QpCycnxPdbmlbrPi5sGG6Za/ak0VeMal7rjmzp0brFq1KrjpppuCkSNHNnfnhfxoRYs0sB+li/WZDWwnJEEAm7Ja/Z4KgtVvq3JjC1FagLruUs2r8m8VuCI+foCRBvajdLE+s4HthCQIYFNWy99TI335c5/6dVXgqlpW1bgq/QDJ8QOMNLAfpYv1mQ1sJyRBDmwDUeD6xRdfmAESRHm1enzUUUeZXFulGKhxFsErAACoZdTApiwL31Pdc+3evTvYtGmTCVZV40qjrHRQg4A0sB+li/WZDWwnJEEAm7IsfE91iXXrrbcG06ZNM70dID38ACMN7EfpYn1mA9sJSRDApowDsLGx/ZEG9qN0sT6zge2EJMiBBQAAQKZUtAYWAAAgH2pgEVfFAlgAAAAgDaQQAAAAIFMIYAEAAJApBLAAAADIFAJYAAAAZAoBLAAAADKFABYAAACZQgALAACATCGABQAAQKYQwAIAACBTCGABAACQKQSwAAAAyBQCWAAAAGQKASwAAAAyhQAWAAAAmUIACwAAgEwhgAUAAECmEMACAAAgUwhgAQAAkCkEsAAAAMgUAlgAAABkCgEsAAAAMoUAFgAAAJlCAAsAAIBMIYAFAABAphDAAgAAIFMIYAEAAJAhQfD/AyUIXVDvvHqwAAAAAElFTkSuQmCC\" width=\"688\" height=\"542\"\u003e\u003c/p\u003e \u003cp\u003eAs mentioned earlier, 30 ligands showed higher binding affinities than myricetin after the structural modifications, and from these, ligands \u003cb\u003eB-1\u003c/b\u003e, \u003cb\u003eA-2\u003c/b\u003e, \u003cb\u003eC-3\u003c/b\u003e, and \u003cb\u003eC-4\u003c/b\u003e displayed higher DockScores than donepezil. Using ligand \u003cb\u003eB-1\u003c/b\u003e containing an azetidine substituent as an example, the significant gains over the original myricetin come from lipophilic reward (32%), electrostatic reward (111%), and the electrostatic complementarity for having ligand atoms in a favourable electrostatic environment of the protein (300%). From the frequency of occurrence of the ligands, imine and hydrazine-containing compounds (\u003cb\u003eB\u003c/b\u003e and \u003cb\u003eC\u003c/b\u003e, respectively) showed better binding affinities than the hydrazides \u003cb\u003eA\u003c/b\u003e. This could be due to a reduced interaction from the highly polar hydrazides, as the binding site analysis of the AChE binding gorge showed a highly hydrophobic environment [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Molecular Dynamic simulations: interaction stability of the protein-ligand complex\u003c/h2\u003e \u003cp\u003eThe room-mean-square deviation (RMSD) for all the protein-ligand complexes was calculated for every frame in the trajectory. This was done to determine the average displacement of all the atoms for a specific frame compared to a reference frame. The RMSD for frame x is given by:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:RMSDₓ=\\:\\sqrt{\\frac{1}{N}\\sum\\:_{i=1}^{N}\\left({r}_{i}^{{\\prime\\:}}\\left({t}_{x}\\right)-{r}_{i}\\:\\left({t}_{ref}\\right)\\right)\u0026sup2;}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere N gives the number of atoms in the atom selection, t is the reference time and r' is the post-superimposed position of the selected atoms in frame x with respect to the reference frame, while frame x is recorded at time t\u003csub\u003ex\u003c/sub\u003e. The procedure is repeated for every frame in the simulation trajectory [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe RMSD of the protein-ligand complex for donepezil, myricetin, and modified myricetins \u003cb\u003eB-1\u003c/b\u003e, \u003cb\u003eA-2\u003c/b\u003e and \u003cb\u003eC-3\u003c/b\u003e are shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, b, c, d, and e, respectively. In the donepezil complex, both the protein and the ligand showed equilibration at around 12 ns, and no apparent divergence was observed till the end of the 20 ns simulation time. The protein showed a lower RMSD value than the donepezil ligand, but the fluctuational changes in the two cases were in the order of ~\u0026thinsp;1\u0026Aring;. Comparing myricetin and its derivatives, the most stable ligand is hydrazine \u003cb\u003eB-1\u003c/b\u003e followed by hydrazide \u003cb\u003eA-2\u003c/b\u003e and then imine \u003cb\u003eC-3\u003c/b\u003e, while myricetin showed some levels of divergence towards the end of the simulation. This result agrees with their dock scores and MM-GBSA values. Ligand \u003cb\u003eB-1\u003c/b\u003e achieved the equilibration point at approximately 5 ns, and this was maintained throughout the simulation time. In all the cases, including the donepezil complex, hAChE protein has RMSD values below 1.8 \u0026Aring; while ligands \u003cb\u003eB-1\u003c/b\u003e and \u003cb\u003eA-2\u003c/b\u003e have RMSD values below 3.0 \u0026Aring; and 2.4 \u0026Aring;, respectively, after they attained the equilibration. In contrast, both myricetin and \u003cb\u003eC-3\u003c/b\u003e showed RMSD values above 5 \u0026Aring;.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMolecular dynamics studies show the significant binding interactions between donepezil, myricetin, and the myricetin derivatives with the highest MM-GBSA scores. The protein-ligand contacts are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003e. As expected, the amino groups of the azetidine substituent on \u003cb\u003eB-1\u003c/b\u003e and \u003cb\u003eA-2\u003c/b\u003e and that of the piperazine substituent on \u003cb\u003eC-3\u003c/b\u003e displayed the most important interactions. Ligand \u003cb\u003eB-1\u003c/b\u003e formed a new water-bridged interaction between Gln71 and its protonated amino group of azetidine moiety. At the same time, there was no change in the frequency of interaction with Tyr72 except for the increase in the percentage of water-bridged interaction in \u003cb\u003eB-1\u003c/b\u003e with the accompanying decrease in H-bond interaction compared to myricetin. The interaction of myricetin with Tyr72 was coming from the 5\u0026rsquo;-OH group of the phenyl moiety at 41% of the simulation time. However, in ligand \u003cb\u003eB-1\u003c/b\u003e, the formation of the hydrazine group causes a change in the binding pose, resulting in a water-bridged interaction between Tyr72 and the protonated amino group of the azetidine group. The significant gain for ligands \u003cb\u003eB-1\u003c/b\u003e, \u003cb\u003eA-2\u003c/b\u003e, and \u003cb\u003eC-3\u003c/b\u003e came from different interactions with Asp74, with ligand \u003cb\u003eB-1\u003c/b\u003e having the highest interactions with this residue, as shown in the 2D interactions diagram in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e (close attention should be paid to the scale of the y-axis). The interactions include different H-bonds, Pi-cation interactions, and water-bridged H-bond interactions. The interaction of the modified ligands with Thr83 disappeared in \u003cb\u003eB-1\u003c/b\u003e and was almost insignificant in \u003cb\u003eC-3\u003c/b\u003e but was maintained in \u003cb\u003eA-2\u003c/b\u003e. All the modified ligands showed an increased frequency of interactions with Trp86. The frequency of interaction with Asn87 only decreased in \u003cb\u003eB-1\u003c/b\u003e, saw an increase in \u003cb\u003eA-2\u003c/b\u003e, and was maintained in \u003cb\u003eC-3\u003c/b\u003e. Additional interactions in the modified myricetins, especially ligands \u003cb\u003eB-1\u003c/b\u003e and \u003cb\u003eA-2\u003c/b\u003e, involved Ser125, Glu202, Phe297, Phe338, Gly372, and His447 compared to myricetin. All these could explain the increased DockScore and the stability of the modified ligands.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.6 ADME-Tox profiling and drug-likeness\u003c/h2\u003e \u003cp\u003eBefore a medicine can be approved, it must be screened for pharmacokinetic properties and drug-likeness potential [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Several guidelines have been proposed to assess if a drug candidate would be orally bioavailable, depending on the pharmacological class. Lipinski's rule is a widely used standard for determining a compound's bioavailability in small-molecule inhibitors [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. According to Lipinski and colleagues' careful analysis of orally active drugs, a potential drug candidate with an oral route of administration should not violate more than one of the following criteria: molecular weight less than 500 Da; the number of hydrogen bond donors\u0026thinsp;\u0026le;\u0026thinsp;5; the number of hydrogen bond acceptors\u0026thinsp;\u0026le;\u0026thinsp;10; and octanol-water partition co-efficient\u0026thinsp;\u0026le;\u0026thinsp;5 [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Molecules with poor absorption and low permeability characteristics are considered poor inhibitors, especially if they violate more than one of these conditions [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The results of this investigation, as given in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, suggest that Quercetin and Epicatechin have the potential to be outstanding drug-like molecules since they do not violate any of Lipinski's principles. However, Myricetin its modified analogues (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) and Epigallocatechin only violated one rule with more than the required number of hydrogen bond donors. As a result, there is a good possibility that any of these compounds may act as promising candidates for drug development.\u003c/p\u003e \u003cp\u003eHigh-throughput screening tests of several pharmacokinetic parameters are undertaken early in drug development; computational-based ADME-Tox predictions are currently enhancing this labour-intensive and capital-intensive effort. \u003cem\u003eIn silico\u003c/em\u003e ADME-Tox prediction analyses drug candidates' probable distribution and pharmacokinetics within a single global model. This prediction shows if the candidate will be suitable for drug development in the future, avoiding late-stage attrition and clinical development costs. MetStabOn [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], admetSAR [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], ADMETlab [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and CypReact[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] have all been shown to be highly effective in predicting drug candidates\u0026rsquo; pharmacokinetic and toxicological endpoints. Early screening for pharmacokinetic and pharmacodynamic features is increasingly being used to prevent undesired qualities from delaying the advancement of a drug candidate into the clinic. To that end, the top four phenolic compounds and myricetin analogues were subjected to the admetSAR analysis to determine their future potential as drug candidates. Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e present our results of pharmacokinetic predictions of Quercetin, Myricetin, Epigallocatechin, Epicatechin, the standard drug (donepezil) and myricetin analogues. For the prediction of absorption and distribution features of our drug candidates, we identified human intestinal absorption (HIA), P-glycoprotein substrate, and penetration through the blood-brain barrier (BBB) (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The selected compounds' and myricetin analogues in Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e depict positive HIA values, including the standard, may suggest that they are easily absorbed in the gut following ingestion. In the distribution section, Quercetin, Myricetin, Epicatechin, and Epigallocatechin exhibit negative BBB test results, indicating that they cannot cross the blood-brain barrier and thereby protect the central nervous system. However, the standard drug (donepezil) and myricetin analogues has strong correlation showing a positive score for BBB, indicating that it has a more significant dispersion and may have a neurological impact. Quercetin, Myricetin, Epicatechin, and Epigallocatechin were also predicted to be non-substrates of P-glycoprotein. This implies that these substances may have favourable distribution characteristics. However, the standard drug (donepezil) and the myricetin analogues may act as a P-glycoprotein inhibitors, limiting its distribution by P-glycoprotein efflux mediation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Cyp450 families have been recognized as a key pharmacological parameter in metabolism. Inhibition of these protein families, according to Lynch, may result in drug-drug interactions and bioaccumulation [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. According to our results, Quercetin and Myricetin inhibit one or more of these metabolic enzymes, while Myricetin analogues exhibit minimal or no inhibition of metabolic enzymes. It is crucial to note that non-acceptable toxicological profiles are important reasons for drugs' failure to pass clinical trials; hence we have included Ames mutagenicity, acute oral toxicity, hERG inhibition, and carcinogenicity tests in this study (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The carcinogenicity test results for all compounds including the myricetin analogues and the standard drug are negative, which clarifies why they are not carcinogenic. The hERG and Ames mutagenicity are important pharmacological indicators for determining if a drug-like substance is capable of causing cardiac arrhythmia[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and mutating DNA. The standard drug (donepezil) and Myricetin excel in the Ames mutagenicity test. However, Quercetin, Epigallocatechin, Epicatechin, and Myricetin analogues show positive Ames test results, suggesting they may have the potential to modify DNA. The standard drug (donepezil), which has a positive hERG test result, may influence the heart's potassium channel rhythm (cardiac arrhythmia). In contrast, the other compounds including myricetin analogues have negative values for the hERG test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLipinski's character of donepezil and the top four ligands from the DockScore\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigand\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLogP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003enHBA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003enHBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003enViolation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDonepezil\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e379.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMyricetin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e318.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQuercetin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e302.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.448\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEpigallocatechin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e306.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEpicatechin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e290.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: LogP: Octanol-water partition coefficient; nHBD: number of hydrogen bond donors; nHBA: number of hydrogen bond acceptors; nViolation: number of Violation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrediction of the toxicity profiles of donepezil and the top four compounds from the molecular docking\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eParameters/Ligands\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDonepezil\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMyricetin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEpigallocatechin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEpicatechin\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBlood brain barrier (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.9250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.6750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.6750)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHuman intestinal absorption (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.9838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+(0.9071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+(0.9071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+(0.8922)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+(0.8922)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep-gp inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.8860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9191)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9207)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9411)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLogS (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.425)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.999)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(3.101)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(3.101)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHuman oral Bioavailability (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7857)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7857)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCaco-2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.6843)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7367)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.6417)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9372)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9406)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCarcinogenicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9600)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(1.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(1.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9700)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9700)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAmes mutagenicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+(0.8410)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+(0.6100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+(0.6000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcute oral toxicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII (0.5250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eII (0.7348)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eII (0.7348)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIV (0.6433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIV (0.6433)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHuman either - a -go -go inhibition\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.9520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7812)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8410)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.4416)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.4678)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHepatotoxicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.8677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+(0.6625)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+(0.9025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e+(0.6427)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7375)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2C19 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8356)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9041)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9041)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP1A2 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.5072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+(0.9106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+(0.9106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9046)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9046)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP3A4 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.7411)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e+(0.6951)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+(0.6951)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8309)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8309)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2C9 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9071)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2D6 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e+(0.8684)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9287)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9231)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLipinski's character of the five modified analogues of Myricetin from the DockScore\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLigand\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular weight\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLogP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003enHBA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003enHBD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003enViolation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eB-1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e371.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eA-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e399.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e385.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e384.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eB-5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e385.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote: LogP: Octanol-water partition coefficient; nHBD: number of hydrogen bond donors; nHBA: number of hydrogen bond acceptors; nViolation: number of Violation.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrediction of the toxicity profiles of modified analogues of Myricetin from the molecular docking\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eParameters/Ligands\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB-1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA-2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC-3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC-4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eB-5\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBlood brain barrier (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.0020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e+(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e+(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.0230)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+(0.0020)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHuman intestinal absorption (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.0070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e+(0.0180)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e+(0.0750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+(0.0020)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ep-gp inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e+(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e+(0.0070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.0020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+(0.0060)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLogS (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.5760)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.9420)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026minus;\u0026thinsp;(2\u003c/b\u003e.9720)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.6620)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(2.5480)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCaco-2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(6.1220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(6.1430)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(6.1360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(6.0800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(6.1300)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCarcinogenicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.4860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.4880)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.1740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.1460)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.5860)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAmes mutagenicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.8070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e+(0.8240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e+(0.7540)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.7700)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+(0.8250)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHuman either - a -go -go inhibition\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.249)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.318)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.307)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eHepatotoxicity\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.8270)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e+(0.7360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e+(0.9030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.9030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e+(0.8440)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2C19 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP1A2 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e+(0.0060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0290)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.6640)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0680)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0860)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP3A4 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.8230)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9580)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e+(0.9400)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.9920)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2C9 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0040)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0010)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCYP2D6 Inhibitor (+/-)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0010)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\u0026thinsp;(0.0000)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Limitation of the study\u003c/h2\u003e \u003cp\u003eThe findings presented in this study are derived solely from computational \u003cem\u003e(In silico)\u003c/em\u003e experiments. Additionally, in vivo and in vitro laboratory tests are required to validate the outcomes reported here. As this study is predictive, the results should be interpreted with appropriate caution. Also, While we recognize that longer simulations could provide more comprehensive insights, the current analysis provides valuable preliminary insights into the protein-ligand dynamics and interaction stability. Future studies can explore this system further with extended simulations when computational resources become available.\u003c/p\u003e \u003c/div\u003e"},{"header":"4.0 Conclusion","content":"\u003cp\u003eIn this study, thirty-eight plant-based phenolic compounds were retrieved from the PubChem database. These compounds, in addition to the cognate donepezil, were virtually screened against Acetylcholinesterase. The results of the virtual screening showed that myricetin, quercetin, epigallocatechin, and epicatechin displayed the highest binding affinities, though lower than donepezil. The molecular modification of myricetin was done by Schiff base formation using custom R group enumeration of the Schr\u0026ouml;dinger suite to give different hydrazides \u003cb\u003eA\u003c/b\u003e, hydrazines \u003cb\u003eB\u003c/b\u003e, and imines \u003cb\u003eC\u003c/b\u003e, which were subsequently subjected to different virtual screenings. Four of these ligands from the three molecular classes showed better binding affinities than donepezil, in addition to the better stability of their protein-ligand complexes. The result of the molecular dynamics simulation agrees with the docking scores and the MM-GBSA values. From these, various molecular interactions were observed, which include hydrogen bondings, π- π stacking, π-cation, and more importantly, hydrophobically packed H-bonding, which is essential in maintaining ligand stability within a binding pocket. From the results of the molecular docking, the top four phenolics with the highest binding affinities (myricetin, quercetin, epigallocatechin, and epicatechin) including myricetin analogues derivatives were subjected to ADMET properties prediction and drug-likeness calculation using the Lipinski rule of five (Ro5). The favourable predicted results show these compounds could be further developed into potential drug candidates. However,\u0026ensp;highly powerful phenolic compounds also face hurdles such as poor bioavailability, labile structures, toxicity concerns, and lack of clinical data. Overcoming these challenges necessitates advanced drug delivery platforms, structural optimization,\u0026ensp;uniform formulation and robust clinical trials. The integration of nanotechnology, artificial intelligence, omics, sustainable production practices, and regulatory support will enable the effective promotion as well as\u0026ensp;clinical translation of phenolics.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Centre for High Performance Computing (CHPC, Cape Town, South Africa) for access to the CHPC Lengau Cluster and Schr\u0026ouml;dinger molecular docking software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest\u0026nbsp;\u003c/strong\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u0026nbsp;\u003c/strong\u003eNot applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.A. Ashiru and R.A. Adigun: Conceptualization, investigation, methodology, validation, visualization, writing-original draft preparation, writing review, and editing. M.O. Babalola, S.O.Ogunyemi, I.O. Junaid, M.T. Bello-Hassan, M.A. Fategbe: Conceptualization, writing review and editing. M.G Baker, K.A Alabi, P.O. Emmanuel, M.O. Balogun: investigation, validation, visualization, writing-original draft preparation and writing review, and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMojeed Ayoola Ashiru ([email protected])\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;Some of the datasets generated during and/or analysed during the current study are in the manuscript while the rest are available from the corresponding author on reasonable request.\u0026rdquo;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eN.R. Jabir, M.T. Rehman, K. Alsolami, S. Shakil, T.A. Zughaibi, R.F. Alserihi, M.S. Khan, M.F. AlAjmi, S. 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Imaga, In vitro Analysis and Molecular Docking of Gas Chromatography-Mass Spectroscopy Fingerprints of Polyherbal Mixture Reveals Significant Antidiabetic Miture, Nigerian Journal of Experimental and Clinical Biosciences 10 (2022) 105\u0026ndash;115. https://doi.org/10.4103/njecp.njecp_15_22.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acetylcholinesterase, ADMET Modeling, Alzheimer’s disease, Molecular Docking, Molecular Dynamics","lastPublishedDoi":"10.21203/rs.3.rs-6356281/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6356281/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Alzheimer's disease is the most prevalent cause of dementia, accounting for more than seventy per cent of all the reported cases. Among the various treatment strategies, inhibiting the action of acetylcholinesterase that breaks down the neurotransmitter acetylcholine is the most common. In this report, thirty-eight phenolic compounds were retrieved from the PubChem database and screened in silico against acetylcholinesterase. Non-covalent molecular docking, molecular mechanics-generalized born surface area (MM-GBSA), and molecular dynamics (MD) were used to predict their binding mode, affinity, free energy, and the stability of the protein-ligand complex. These were followed by drug-likeness screening and a rigorous prediction of their absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters. Myricetin (-13.9 kcal/mol) was predicted to have the highest binding affinity among the phenolics, though lower than the bound donepezil (-16.3 kcal/mol). To increase the binding affinity of myricetin, it was modified via a Schiff base formation, which gave the hydrazine B-1 a binding affinity of -17.7 kcal/mol, higher than donepezil. The molecular dynamics simulation showed that the modified ligands have better stability than myricetin. The ADMET and drug-likeness studies showed that the top four phenolics and myricetin analogue derivatives could be further developed as potential drug candidates.","manuscriptTitle":"Acetylcholinesterase Inhibitory Potential of Plant-Based Phenolics in the Treatment of Alzheimer's Disease: An In Silico Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:18:02","doi":"10.21203/rs.3.rs-6356281/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"822e94eb-82b6-4b33-9d04-1f095bd14c17","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-21T16:08:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-07 06:18:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6356281","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6356281","identity":"rs-6356281","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}