Exploring potential inhibitors from Eriobotrya japonica targeting AChE and BChE in Alzheimer's Disease through docking, ADMET profiling, and DFT analysis

Exploring potential inhibitors from Eriobotrya japonica targeting AChE and BChE in Alzheimer's Disease through docking, ADMET profiling, and DFT analysis | 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 Article Exploring potential inhibitors from Eriobotrya japonica targeting AChE and BChE in Alzheimer's Disease through docking, ADMET profiling, and DFT analysis Mubashir Afzal, Aleena Sajjad, Muhammad Bilal Iqbal Rehmani, Sameer Nasir, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7521725/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 (AD) is the most common dementia causing disease in the elderly and is strongly associated with cholinergic dysfunction. The crucial enzymes in this mechanism are acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which are prominent therapeutic targets. Recently, natural phytocompounds have been considered as safer substitutes to synthetic inhibitors. In this study, fifty-four phenolic compounds of Eriobotrya japonica were chosen from the literature and evaluated using in-silico methods as prospective dual AChE and BChE inhibitors. Based on molecular docking with the Schrodinger Suite, chrysin appeared to be the most promising candidate as it exhibited high binding affinity and stable interaction with the catalytic residues of both enzymes. Pharmacokinetic and ADME studies indicated that the drug would be well-absorbed and bioavailable orally with low acute toxicity. Moderate solubility, blood-brain barrier penetration and potential CYP-mediated interactions were noted. The electronic stability, antioxidant behavior, and interaction with target proteins of chrysin were also verified by density functional theory (DFT) analysis. Finally, the obtained results point to the potential of chrysin of E. japonica as a multitarget lead compound in the treatment of AD, which exerts combined enzyme inhibition and neuroprotective effects. Its therapeutic potential should be confirmed by further in-vitro and in-vivo studies. Biological sciences/Biochemistry Physical sciences/Chemistry Biological sciences/Computational biology and bioinformatics Biological sciences/Drug discovery Biological sciences/Neuroscience Eriobotrya Japonica Alzheimer’s disease acetylcholinesterase butyrylcholinesterase Molecular docking pharmacokinetics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Alzheimer's disease (AD), which is the most prevalent form of dementia among older individuals today, is a major cause of disability due to its association with impairment of memory and thinking [ 1 ]. No curative or therapeutic mode of Alzheimer's disease (AD) is available currently because of the complexity of its biochemical mechanism [ 2 ]. Two neurochemical modifications found in Alzheimer's disease include cholinergic deficit and reduction of choline formation [ 3 ]. This leads to the pathological activities of some of the enzymes used in neurological signaling. These are known as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which occur in neurofibrillary plaques and neurofibrillary tangles of the brain [ 4 , 5 ]. The hydrolytic enzymes AChE and BChE deactivate acetylcholine (AChE) to eliminate the functioning of a synaptic cleft [ 6 ]. Scientific reports presented previously show that the healthy brain is enriched with substantial amounts of AChE and BChE. Therefore, they contribute to a small extent to the regulation of AChE levels in the brain [ 7 ]. However, in individuals with Alzheimer's, the level of BChE activity gradually rises, and the AChE activity either remains constant or decreases [ 8 ]. This has led both enzymes to be considered viable therapeutic targets in enhancing the cholinergic deficit that is reported to be underlying the decline in cognitive global functioning and behavioral status that is observed in AD [ 9 ]. Although the etiology of AD remains unknown, previous studies revealed that cholinesterase (ChE) activity should be regulated at certain critical stages of AD pathogenesis [ 10 ]. Among the many effective treatment strategies, the inhibition of AChE and BChE was one of them that blocked cholinergic activity and raised levels of ChE [ 11 ]. Both the AChE and BChE inhibitors are developed and employed in the treatment of Alzheimer's disease through enhancing the cholinergic neurotransmitter activity in the brain, therefore minimizing the symptoms of AD [ 12 , 13 ]. The cholinergic hypothesis entails that AD has been associated with a dysfunction in the central nervous system (CNS) and loss of cholinergic ability [ 14 , 15 ]. A decrease in cholinergic functions has been linked to diminished functioning of the brain, which comes with old age[ 16 ]. Such loss of cholinergic activity can be attributed to many factors, including the generation of amyloid peptide and the agglomeration of the tau protein, among others, stress, and an abundance of transition metals [ 17 , 18 ].Three of the four approved Alzheimer's disease-treating drugs so far have been AChE inhibitor development programs [ 19 ]. Alzheimer's dementia has been treated using tacrine (1, 2, 3, 4- 4-tetrahydro-9-aminocridine) [ 20 ]. It became the first AChE inhibitor to be approved by the FDA, and numerous AChE inhibitors such as galantamine, donepezil, and rivastigmine were developed in the following years [ 21 ]. A large number of plant extracts have been studied for their ability to treat neurological and cognitive issues. Galantamine is the initial AChE inhibitor of plant origin that was found [ 22 ]. Numerous herbal medicines such as olive, tea, blueberry, strawberry, peppermint, walnut, immortelle, and sage have been reported to possess AChE-inhibiting effects due to the presence of polyphenols [ 23 ]. Curcumin, (-)-epigallocatechin-3-gallate (EGCG), and several flavonoids were also effective AChE inhibitors when isolated [ 24 ]. Bisphenols have structure-specific inhibitory activity and are capable of inhibiting either acetylcholinesterase (AChE) or butyrylcholinesterase (BChE). Green tea and its principal active phenolic compound, EGCG, turmeric curcumin, and resveratrol have all been associated with an AChE inhibitor [ 25 , 26 ]. Naringenin, a significant flavonoid in citrus, has been shown to have AChE inhibitory activity in vitro and has been demonstrated to be anti-amnesic in vivo[ 27 ]. Although the inhibitory effect of the flavonol quercetin has not been studied in vivo, it also appears to influence cholinergic dysfunction and brain blood flow [ 28 ]. Previously, the inhibition of AChE was the primary target of treatment; nevertheless, some studies have shown that both AChE and BChE inhibition play a significant role in the pathophysiology and pharmacological management of AD [ 29 ]. In addition to the evidence of BChE's role in cholinergic control and the proposed role of BChE in the development of AD, dual inhibition could provide other advantages, particularly in the long term [ 30 ]. The only available dual cholinesterase inhibitor that is clinically used is rivastigmine. It affects enzymes and is active in late-stage AD when BChE levels increase. The next-generation therapeutic approach is dual inhibition of cholinergic support with an antioxidant, anti-amyloid, or multi-target effect [ 31 ]. Current medications (donepezil, galantamine, and rivastigmine) lack efficacy and tolerability, and Alzheimer's disease is a highly complex and multifactorial pathology with involvement of multiple neurotransmitter systems, inflammation, oxidative stress, and protein accumulation [ 32 , 33 ]. Thus, it is of interest to develop new dual inhibitors and non-alkaloid candidates discovered among flavonoids. The polyphenolic compounds that occur naturally not only have antioxidant and anti-inflammatory effects but have also been found to interact with both acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), making them of interest as potential multitarget-directed ligands (MTDLs) [ 34 ]. Loquat, scientifically referred to as Eriobotrya japonica Lindl. The Rosaceae has been used as a traditional medicine in curing many diseases. Loquat has attracted recent interest due to its high phytochemical content, specifically its phenolic content, flavonoids, and terpenoids, which have antioxidant, anti-inflammatory, and enzyme-inhibitory effects. Such bioactive substances have rendered the loquat a promising source to formulate functional foods and natural medicines [ 35 , 36 ]. The existing literature highlights the inhibitory activity of phenolic compounds extracted from Eriobotrya japonica on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). A variety of phenolic compounds, such as tyrosol derivatives and flavonoids, were identified in different parts of plants using phytochemical profiling with ultra-high-performance liquid chromatography in combination with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). The phenolic extracts possessed a high enzyme inhibitory activity, with the root extract exhibiting the highest BChE inhibition (3.64 mg GALAE/g). These findings suggest that E. japonica phenolics have therapeutic potential to be utilized as a natural cholinesterase inhibitor, which paves the way for exploring more research on neurodegenerative disorders [ 37 , 38 ]. The search for new or alternative cheap molecules of natural origin is constantly desired, and it is still under investigation. Computational techniques are one of the quickest and most inexpensive methods. Therefore, through computational biology, it has been found that different groups of chemicals found in both plants and the marine environment have been screened and have been reported to possess a high inhibitory effect on cholinesterase. Nevertheless, fruits do not investigate cholinesterase inhibitors. In this study, therefore, we have carried out a virtual screening to discover new cholinesterase inhibitors in Japonica and also reported the molecular conformations of Japonica chemicals that interact with cholinesterase. Docking was applied to get more information on the significance of binding interactions of the prospective new molecules to treat AD. Material and Methods 2.1. Target proteins retrieval and preparation The 3D X-ray crystal structure of both proteins AChE (PDB ID: 4EY7) and BChE ( PDB ID: 5DYW) was downloaded from the protein data bank PDB ( https://www.rcsb.org ) [ 39 , 40 ]. The Protein Preparation Wizard panel of SchrödingerSuite2022-3 was used to prepare the proteins co-crystallized with the native ligands. The target proteins were ready to assign bond ordering, adding hydrogen or forming disulfide bonds, and Prime was used to fill in missing side chains and loops. The protein was reduced using OPLS3, after which it was optimized [ 41 ]. Finally, the receptor grid file was created to define the ligand-binding pocket. 2.2. Ligand retrieval and preparation The previous literature was used to retrieve the fifty-four phenolic phytocompounds of the Eriobotrya japonica [ 37 ]. PerkinElmer Informatics ( https://informatics.perkinelmer.com ) was used to construct the 2D and 3D structures and SDF file of the compounds. A control molecule, rivastigmine, was applied, and its chemical structure was downloaded from PubChem. LigPrep of SchrödingerSuite2022-3 was used to generate ligands. It was done by recreating the structures in three dimensions with low energy and proper chiralities. It was assumed that all ligands could exist in potential ionized forms at physiologic pH 7.2 +/- 0.2 [ 42 ]. 2.3. Receptor grid generation The binding orientation and the size of the active site of protein-ligand docking are determined by receptor grid generation. Scoring coordinates of AChE and BChE binding pocket were identified utilizing the receptor grid generation module of Schrodinger Maestro 12.5 based on the co-crystallized ligand [ 41 ]. 2.4. Molecular docking procedure The prepared ligands were docked into the defined active site of AChE and BChE via in Schrodinger Maestro 12.5 Glide-SP (standard precision), followed by XP (extra precision) to correct false-positive results. The van der Waals scaling factor was set at 0.80 for the ligand atoms. The docking protocol was validated by splitting the co-crystallized ligand from the protein, preparing it, and re-docking it into the binding site of AChE and BChE. The calculated root-mean-square deviation (RMSD) of AChE and BChE was 0.6652Å and 2.215Å, respectively (normal range: 1–2 Å), confirming the reliability and reproducibility of the docking approach. 2.5 Evaluation of Drug profile through ADME and toxicity analysis Pharmacokinetics of the chosen phytochemicals was analyzed in the Swiss ADME ( http://www.swissadme.ch ) and PKCSM ( http://biosig.unimelb.edu.au/pkcsm/ ). The server was uploaded with canonical SMILES of the molecules. The compound was chosen that crosses the blood-brain barrier only. The determination of pharmacokinetics features and drug-likeness was carried out using the Lipinski Rule of Five (LRF). The rule consisted of four parameters that gauged the molecular weight of the phytochemicals, hydrogen donors, hydrogen acceptors, and lipophilicity. Bioavailability of the phytochemicals was also analyzed using the server [ 43 ]. Then, the phytochemicals' toxicity was analyzed with the Pro Tox-II webserver ( https://tox-new.charite.de/protox_II/ ). The online server can predict the toxicity of compounds by ranking the compounds' toxicity on a scale of 1 (toxic) to 6 (non-toxic) [ 44 ]. 2.6 Density functional theory analysis The theoretical approaches used to compare the chemical and biological activities of compounds are nowadays widespread. The study of physicochemical properties of some bioactive compounds of E. Japonica using a quantum chemical calculation through density functional theory (DFT) was conducted to predict compounds with strong biological activities. DFT calculation using the B3LYP functional method and 6-31G basis set as per the Gaussian 09W package [ 45 ]. Due to the calculations conducted with the help of this approach, a significant number of parameters can be derived. Some of the parameters that are found during the calculations are highest occupied molecular orbital energy (E HOMO ), lowest unoccupied molecular orbital energy (E LUMO ), energy band gaps (Eg) ionization energy (I), electron affinity (A), chemical hardness (η), chemical softness (δ), chemical potential (µ), electronegativity (χ), electronic energy, enthalpy, Gibb free energy and dipole moment (D)) [ 46 , 47 ]. Results and discussion Docking Results The fifty-four compounds were docked with both proteins in their active site. The compounds that were selected were those that crossed the blood-brain barrier and displayed high binding affinity with both proteins. Chrysin will be depicted as the top hit compound based on binding scores and BBB (Table S1 ). The molecular docking indicates that the natural compound selected from the Japonica interacted with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) in their active pockets. In contrast to the control drug Rivastigmine, which was selected. The most desirable is a parasympathomimetic or cholinergic agent of the cholinesterase inhibitor type that acts as a dual-targeted inhibitor of AChE and BChE [ 23 ]. This drug has U.S. Food and Drug Administration (FDA)-approved status for treating Alzheimer’s disease and other neurological disorders [ 32 ]. The binding of all types of compounds was discovered to occur readily at the same site with some deviation. Some of the key amino acid residues were identified in the interaction between the chrysin (CID:5281607) and PDB ID 4EY7, which is attributed to the stability and specificity of the binding. Chrysin was found to have a binding mode characterized by predominant π-π stacking and π-π T-shaped interactions, signifying that it had great affinity to the aromatic gorge of AChE, with most of the interactions involving residues Tyr72, Tyr124, Tyr337, Tyr341, Phe295, Phe338, and Trp286. These aromatic residues have been found to play an essential role in the recognition of substrate and stabilization of ligands. Also, chrysin established two typical hydrogen bonds with Tyr72 and Tyr124, further stabilizing the molecule in the active site of the enzyme and adding to the binding affinity. Remarkably, these interactions indicate that chrysin binds to the peripheral anionic site (PAS) of AChE, possibly blocking the access to acetylcholine or aggregation of amyloid-beta, thus making it a prospective scaffold in multifunctional Alzheimer therapy. Conversely, the binding interaction analysis of Rivastigmine with acetylcholinesterase (AChE, PDB ID: 4EY7) shows a wide array of stabilizing interactions that hold the molecule in place inside the catalytic active site gorge of the enzyme. A standard hydrogen bond is seen between the carbonyl oxygen of Rivastigmine and Tyr124, which is a residue known to be involved in substrate orientation. Also, π-π stacking and π-alkyl interactions are established with some of the most essential aromatic residues, such as Tyr341, Tyr337, Tyr72, and Trp286, that are components of the peripheral anionic site (PAS) and the catalytic anionic site (CAS) of AChE [ 48 ]. Such interactions play an essential role in ligand stabilization and enzyme inhibition. Also, His447, part of the catalytic triad (Ser203, His447, Glu334), is involved in a 5–6 stacking interaction and may be involved in a pseudo-irreversible covalent bond formation characteristic of carbamate inhibitors such as Rivastigmine. Phe338 also plays a role in the 2-p stacking that promotes hydrophobic interaction in the active-site gorge. Such a widespread interaction profile indicates that Rivastigmine not only carbamylates the catalytic serine, but also binds to several residues in the binding gorge, which enhances its binding affinity and residence time, in line with its application as a dual AChE/BChE inhibitor in the treatment of Alzheimer's disease [ 39 , 49 ]. The comparative study indicates that the two compounds, although effective in targeting critical residues in the AChE active site region, are presumably likely to act differently as inhibitors. Chrysin, which has a longer and aromatic system and a peripheral binding motif, is expected to behave mainly as a PAS occupant and hydrophobic stacker and may contribute to allosteric regulation or an anti-amyloid agent in addition to inhibiting the enzyme (Table 1, Fig. 2). Table 1 Docking interactions of Rivastigmine (control) and Chrysin with AChE (PDB:4EY7). Compounds Docking score PubChem ID Residue Interaction Type Distance(Å) Rivastigmine (Control) -7.1kcal/mol 77991 TYR124 H-bond 1.87 TRP286 Pi-Pi Stacked 4.86 TYR341 Pi-Pi Stacked 4.22 PHE338 Pi-Alkyl 4.61 HIS447 Pi-Alkyl 4.79 Chrysin -9.3kcal/mol 5281607 PHE295 H-bond 2.16 HOH728 H-bond 2.77 TYR72 H-bond 3.08 TYR341 Pi–Pi Stacked 3.81 TYR 337 Pi–Pi T-shaped 4.47 Chrysin (CID:5281607) has 2, 3-dimensionally stacking interactions with Trp82 and Trp430 in the active site gorge, and hydrogen bonding with Thr120 and Glu197 of BChE (Protein ID 5dyw). It is worth noting that the hydroxyl functionalities of the flavone nucleus at positions 5 and 7 are involved in standard hydrogen bonding with Glu197, which forms the catalytic triad. Further stabilization is offered by 3-sigma interaction with Ala328 as well as carbon-hydrogen interactions with Gly439, pointing to a more complex binding mechanism that includes both polar and hydrophobic interactions. This complex binding motif, present non-catalytically adjacent and not directly at the catalytic site, suggests the possibility of an allosteric modulation mechanism, which can be added to the known antioxidant and anti-inflammatory actions of chrysin in neuroprotection [ 50 ]. In the Docking complex of Rivastigmine with butyrylcholinesterase (BCHE; PDB ID: 5DYW), various meaningful molecular interactions enable stable binding in the active site of the enzyme. The binding of rivastigmine is stabilized through conventional hydrogen bonds with the backbone amide nitrogen of Gly116 and Gly117, critical residues that surround the oxyanion hole of BCHE. Such hydrogen bonds play essential roles in ligand stabilization in the catalytic pocket. An interaction between a carbon-hydrogen bond and His438 also helps to position the ligand in the right way. The aromatic ring of Rivastigmine is involved in 2 pi-pi T-shaped and pi-sigma interactions with Tyr332, which suggests the significance of aromatic stacking in keeping the ligand in the enzyme gorge. Also, there is an O-alkyl interaction with Trp82 and Trp231, which form hydrophobic interactions that strengthen the binding affinity. All these interactions show that Rivastigmine interacts with both the catalytically active site and the peripheral anionic site of BChE, which agrees with its identity as a dual cholinesterase inhibitor [ 40 , 51 ]. The interaction of chrysin with Glu197, a member of the catalytic triad, does not necessarily affect the catalytic serine but is in its vicinity, indicating the possible allosteric regulation of the activity and not active-site inhibition. The difference suggests Rivastigmine as a pseudo-irreversible inhibitor that directly inactivates the catalytic serine [ 52 ]. In contrast, Chrysin can have modulatory effects that increase its neuroprotective nature without permanently impairing the activity of the enzyme. Such differences in binding orientation and interaction profile underline the complementary nature of synthetic and natural inhibitors in the development of multi-targeted therapeutics of Alzheimer's disease. Therapeutically, the results indicate that chrysin derivatives may be designed as multifunctional molecules acting on cholinesterase inhibition as well as oxidative stress pathways, and Rivastigmine may continue to be the model of effective, selective cholinesterase inhibitors. The structural observations of this study can inform the logical development of new BChE inhibitors that merge desirable properties of each of the two molecular scaffolds (Table 2, Fig. 3). Table 2 Docking interactions of Rivastigmine (control) and Chrysin with BChE (PDB:5DYW). Compounds Docking score PubChem ID Residue Interaction Type Distance(Å) Rivastigmine (control) -7kcal/mol 77991 GLY116 H-bond 2.50 GLY117 H-bond 2.58 TYR332 π–π T-shaped 5.09 TRP82 π–π T-shaped 5.13 HIS438 π–Sigma 5.02 Chrysin -7.7kcal/mol 5281607 GLU197 H-bond 2.54 THR120 H-bond 2.20 TRP82 Pi-Pi Stacked 3.78 GLY439 C-H bond 3.50 ALA328 Pi-Sigma 3.90 ADME and toxicity Results The pharmacokinetic and toxicity profile of the selected phytochemical chrysin demonstrates several favorable properties for drug development. Swiss ADME results indicate that only six compounds cross the blood-brain barrier (Fig. 4) . Chrysin was chosen because of its high binding affinity with both proteins and has a good bioavailability score. Absorption and Bioavailability The PKCSM prediction given in Table 3 shows that chrysin is good intestinal (93.952%) and implies that it has good oral bioavailability. However, it is moderately soluble in water (-3.588 log S), which may limit absorption in the gastrointestinal tract and lower systemic exposure. A moderate CaCO 2 permeability (1.037 log Papp) implies that chrysin can potentially cross intestinal epithelial permeability barriers. However, its substrate status towards P-glycoprotein implies that efflux-mediated reduced absorption is possible. Also, the skin permeability (-2.751 log Kp) was recorded as insignificant; therefore, transdermal delivery was not an option in administering the drug [ 53 ]. Distribution and Tissue Penetration The low distribution volume (0.065 L/kg) shows that chrysin might be mostly circulating in the systemic circulation but not in tissues. The plasma protein binding was estimated to be 84.9%, so 15.1% is unbound to perform pharmacological activity. Importantly, the blood-brain barrier (BBB) penetration of chrysin is moderate ( -0.05 log BB) and the central nervous system permeability is moderate (-1.924 log PS), indicating a moderate likelihood of central nervous system activity [ 54 ]. Metabolism and Drug Interaction Potential Chrysin is not a substrate of CYP2D6 or CYP3A4, which decreases the propensity of interactions with drugs metabolized by these enzymes[ 55 ]. Nevertheless, it is an inhibitor of CYP1A2, CYP2C19, and CYP2C9, which may disrupt the metabolism of other drugs that one may be taking, like warfarin, theophylline, and some antidepressants. This inhibition pattern requires caution in the case of polypharmacy. Excretion and clearance Its total clearance rate (0.584 mL/min/kg) signifies moderate clearance primarily via hepatic pathways since chrysin is not a substrate of the renal OCT2 transporter, and thus there is negligible renal excretion. Table 3 PKCSM pharmacokinetic parameters of the selected phytochemicals Pharmacokinetic Properties Selected Phytochemical Properties Model Name Chrysin Absorption Water solubility -3.588 Caco2 permeability 1.037 Intestinal absorption (human) 93.952 Skin Permeability -2.751 P-glycoprotein substrate yes P-glycoprotein I inhibitor No P-glycoprotein II inhibitor No Distribution VDss (human) 0.065 Fraction unbound (human) 0.151 BBB permeability -0.05 CNS permeability -1.924 Metabolism CYP2D6 substrate No CYP3A4 substrate No CYP1A2 inhibitor Yes CYP2C19 inhibitor Yes CYP2C9 inhibitor Yes CYP2D6 inhibitor No CYP3A4 inhibitor No Excretion Total Clearance 0.584 Renal OCT2 substrate No Toxicity AMES toxicity No Max. tolerated dose (human) 0.175 hERG I inhibitor No hERG II inhibitor No Oral Rat Acute Toxicity (LD50) 2.206 Oral Rat Chronic Toxicity (LOAEL) 1.207 Hepatotoxicity No Skin Sensitization No T.Pyriformis toxicity 0.643 Minnow toxicity 1.181 Toxicity and Safety Assessment Analysis by Stop-Tox (Table S2 ) and Pro-Tox II showed that chrysin is non-mutagenic (AMES negative) and does not block HERG channels, which suggests the low likelihood of genotoxicity and cardiotoxicity. Nonetheless, there is oral rat LD50 (2.206 mol/kg) and chronic toxicity (LOAEL: 1.207 log mg/kg/day) data indicating that high doses might be toxic. Pro-Tox II analysis is given in Table 4, which also suggests the possibility of hepatotoxicity (68%), interaction with nuclear receptors, including AhR (95%), ER (94%), and AR (99%), and potentially endocrine-modulating effects. Skin sensitization was flagged as well (70% probability), and one should be careful about topical applications. Table 4 Parameters obtained through the Pro-Tox II Classification Target Chrysin Pre Pro Organ toxicity Hepatotoxicity I 0.68 Toxicity endpoints Carcinogenicity I 0.51 Immunotoxicity I 0.93 Mutagenicity I 0.64 Cytotoxicity I 0.82 Tox21-Nuclear receptor signaling pathways AhR A 0.95 AR I 0.99 AR-LBD I 0.97 Aromatase A 0.57 ER A 0.94 ER-LBD A 0.88 PPAR-Gamma A 0.65 nrf2/ARE I 0.98 Tox21-Stress response pathways HSE I 0.98 MMP A 0.88 p53 A 0.66 ATAD5 A 0.94 Density functional theory Results The reactivity and interaction potential of chrysin with cholinesterase enzymes were further assessed by evaluation of the electronic properties of chrysin with the help of Density Functional Theory (DFT). Frontier molecular orbitals HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital) were visualized to determine the electron-donating and electron-accepting areas of the molecule[ 56 ]. The HOMO was mainly concentrated on the phenolic A-ring and the neighbouring double bond system; thus, these regions can be considered central points of electron donation and possible nucleophilic contacts with active site residues of AChE and BChE. Conversely, LUMO was localized near the carbonyl group and the neighbouring aromatic systems, which indicates the electrophilic reaction and the hydrogen bonding with nucleophilic amino acids in the enzyme binding pocket. The electrostatic potential map also justified these results, and areas colored red indicate electron-rich areas (namely, the hydroxyl and carbonyl groups) and areas colored blue indicate electron-poor areas. Such electronic features indicate that chrysin possesses well-balanced nucleophilic and electrophilic centers, increasing its ability to participate in both hydrogen bonding and pi-pi stacking interactions in the cholinesterase enzyme catalytic gorge. This bilateral interaction potential may also be a factor in its inhibitory potency against AChE and BChE and is of interest as a multifunctional Alzheimer's therapeutic agent. Its capacity to form stable complexes through the hydrogen bond and aromatic interaction is enhanced by the presence of 1-electron-rich systems and polar functional groups, which also favours its medicinal properties. Some of the parameters that can be derived through the calculation include highest occupied molecular orbital energy (E HOMO ), lowest unoccupied molecular orbital energy (E LUMO ), energy band gaps (Eg) ionization energy (I), electron affinity (A), chemical hardness (η), chemical softness (δ), chemical potential (µ), electronegativity (χ), electronic energy, enthalpy, Gibb free energy and dipole moment (D) are given in Table.5. DFT calculations provided the data on the molecular properties of chrysin. It is chemically moderately reactive (the HOMO-LUMO energy gap is 0.16295 A.U. / 4.43 eV) and a moderate electrophile (electrophilicity index is 3.611 eV), which agrees with its antioxidant character. It is a polar molecule (dipole moment 5.5618 Debye) and affects solubility and binding affinities [ 57 , 58 ]. Table 5 DFT analysis parameters of the top hit compound Parameters Score Dipole moment (Debye) 5.5618 HOMO (A.U) –0.22848 LUMO (A.U) –0.06553 Energy Gap (ΔE Gap ) 0.16295 Ionization Potential (eV) 6.221 Electron affinity (eV) 1.783 Electronegativity χ (eV) 4.002 Electrochemical potential µ (eV) –4.002 Hardness η (eV) 2.219 Softness S (eV) 0.451 Electrophilicity ω (eV) 3.611 Mechanistically, these electronic features rationalize two experimentally-observed phenomena: (i) that chrysin can scavenge radicals (antioxidant activity), which is dependent on the availability of phenolic H-atoms and conjugation to stabilize the resulting radical, properties that correlate with HOMO localization and ΔE, and (ii) that chrysin can moderately but reproducibly inhibit AChE/BChE, where noncovalent interactions (H-bonding, 2-dimensional stacking, hydrophobic contacts A similar trend has been observed in several recent DFT and docking studies of flavonoids molecules which have localized HOMO on phenolic rings and a sufficient 6E value exhibit both antioxidant reactivity and good docking pose in cholinesterases [ 59 ]. The DFT calculations place chrysin in the category of electronically balanced flavones whose HOMO/LUMO distributions, modest HOMO-LUMO gap, reasonable electrophilicity, and significant dipole moment mutually explain its overall activity as an antioxidant and moderate AChE/BChE inhibitory capacity. Conclusion This study presents convincing in silico data that phenolic compounds found in Eriobotrya japonica, especially Chrysin, have a potential inhibitory effect against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which are the most essential enzymes in Alzheimer's disease (AD). Molecular docking showed a binding affinity of Chrysin with key residues in the active site of both enzymes. DFT analysis further indicated its good electronic and structural characteristics that justify its antioxidant and neuroprotective effects. Pharmacokinetic and toxicity modelling showed that chrysin has good oral bioavailability and a safety margin. Still, specific barriers, including moderate water solubility, P-gp efflux, and hepatotoxicity at high doses, must be overcome before clinical usage. Collectively, these results indicate that chrysin may be a useful natural scaffold to develop multifunctional therapeutic agents against cholinesterase inhibition and oxidative stress in AD. However, there is a need to conduct more in vitro and in vivo validation and optimize formulation strategies to establish its efficacy, safety, and translational potential in the treatment of Alzheimer's disease. Declarations Funding: This work has received no funding. Author Contribution Mubashir Afzal: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft.Aleena Sajjad: Data curation, Formal analysis, Investigation, Methodology, Software.Muhammad Bilal Iqbal Rehmani: Formal analysis, Investigation, Validation, Visualization.Sameer Nasir: Formal analysisMuhammad Yahya Waseem: Data curation, Formal analysis, Resources, Software.Muhammad Asif Akram: Conceptualization, Project administration, Supervision, Validation, Writing – review & editing.Iqra Irshad: Formal analysis, Resources, Validation.Shagufta Bashir: Validation, Visualization, Writing – review & editing.Mehdi Rahimi: Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing. Data Availability Data is provided within the manuscript and supplementary information files References Ferreira-Vieira, H. T et al Alzheimer's disease: Target. cholinergic Syst. 14 (1): 101–115. (2016). Lane, C. 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A. et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings . 64 : pp. 4–17. (2012). Luo, S. et al. Enhanced neuroprotective effects of epicatechin gallate encapsulated by bovine milk-derived exosomes against Parkinson’s disease through antiapoptosis and antimitophagy. 69(17): pp. 5134–5143. (2021). Lynch, T. and A.J.A.f.p. Price, The effect of cytochrome P450 metabolism on drug response, interactions, and adverse effects . 76 (3): pp. 391–396. (2007). AL-Makhzumi, Q. M. A. H. et al. Theoretical study of N-Methyl-3-Phenyl-3-(4-(Trifluoromethyl) Phenoxy) Propan as a drug and its five derivatives . 6 (08): p. 80. (2018). Van Mortier, W. J. Genechten, and J.J.J.o.t.A.C.S. Gasteiger. Electronegativity equalization: application parametrization . 107 (4), 829–835 (1985). Obot, I. et al. Theoretical evaluation of triazine derivatives as steel corrosion inhibitors: DFT and Monte Carlo simulation approaches. 42: pp. 4963–4983. (2016). Malak, N. et al. Density functional theory calculations and molecular docking analyses of flavonoids for their possible application against the acetylcholinesterase and triose-phosphate isomerase proteins of Rhipicephalus microplus . 28 (8): p. 3606. (2023). Additional Declarations No competing interests reported. Supplementary Files TableS2.docx TableS1.docx floatimage1.png 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. 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1","display":"","copyAsset":false,"role":"figure","size":444905,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic presentation of the workflow of docking, ADME-Toxicity, and DFT analysis of Eriobotrya japonica phytochemicals against Alzheimer targets.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/6f01648fa36927e8d13604e1.png"},{"id":92209333,"identity":"9e40df21-6bdd-461d-a621-bee37b8a6327","added_by":"auto","created_at":"2025-09-25 19:47:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9474501,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking interactions of rivastigmine (control) and chrysin with AChE (PDB:4EY7). Figures (A) and (B) depict 2D and 3D binding interactions of rivastigmine. Figures (E) and (F) depict 2D and 3D interactions of chrysin.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/54436c2dfbaad2229f4dad76.png"},{"id":92209135,"identity":"c38a1ebf-e2a6-4a63-b605-68171f6337c8","added_by":"auto","created_at":"2025-09-25 19:39:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6546719,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking interactions of rivastigmine (control) and chrysin with 5DYW. Figures (E) and (F) depict 2D and 3D binding interactions of rivastigmine. Figures (G) and (H) represent 2D and 3D interactions of chrysin.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/350b8df2d4306a0628f96001.png"},{"id":92209331,"identity":"a095c8b7-eaa3-4b83-a149-738070a2c910","added_by":"auto","created_at":"2025-09-25 19:47:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":52902,"visible":true,"origin":"","legend":"\u003cp\u003eThe boiled egg generated through the Swiss ADME represents the compounds that cross the BBB\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/ed58be0e6d43280733c68cf3.png"},{"id":92209863,"identity":"69f1638a-7f30-49a9-a77b-215bb2fb7b12","added_by":"auto","created_at":"2025-09-25 19:55:06","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":6041589,"visible":true,"origin":"","legend":"\u003cp\u003eThe HOMO-LUMO distribution and electrostatic potential mapped surface of chrysin calculated by DFT, including orbital energies and reactive sites\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/3d908388137fc970c408fda7.png"},{"id":92866824,"identity":"e0b0655c-753d-4233-8bab-bcbb00b37eb7","added_by":"auto","created_at":"2025-10-06 13:17:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":23384950,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/4ef69ca9-9e7d-484b-b200-1918f984f0b4.pdf"},{"id":92209124,"identity":"e7e83237-dd6e-49e8-8741-582fcedb72ee","added_by":"auto","created_at":"2025-09-25 19:39:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13755,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/eb5f89c627c0c4d899c855d1.docx"},{"id":92209332,"identity":"da5153ed-444b-4340-8f8e-7693a185c655","added_by":"auto","created_at":"2025-09-25 19:47:06","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18364,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/f6081c25a58924649b63ab57.docx"},{"id":92209133,"identity":"65ceed32-45b7-4afb-9df9-ce56724d9608","added_by":"auto","created_at":"2025-09-25 19:39:06","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1306681,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7521725/v1/a222c18c5e755aaebb17ea08.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring potential inhibitors from Eriobotrya japonica targeting AChE and BChE in Alzheimer's Disease through docking, ADMET profiling, and DFT analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAlzheimer's disease (AD), which is the most prevalent form of dementia among older individuals today, is a major cause of disability due to its association with impairment of memory and thinking [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. No curative or therapeutic mode of Alzheimer's disease (AD) is available currently because of the complexity of its biochemical mechanism [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Two neurochemical modifications found in Alzheimer's disease include cholinergic deficit and reduction of choline formation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This leads to the pathological activities of some of the enzymes used in neurological signaling. These are known as acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which occur in neurofibrillary plaques and neurofibrillary tangles of the brain [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The hydrolytic enzymes AChE and BChE deactivate acetylcholine (AChE) to eliminate the functioning of a synaptic cleft [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Scientific reports presented previously show that the healthy brain is enriched with substantial amounts of AChE and BChE. Therefore, they contribute to a small extent to the regulation of AChE levels in the brain [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, in individuals with Alzheimer's, the level of BChE activity gradually rises, and the AChE activity either remains constant or decreases [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This has led both enzymes to be considered viable therapeutic targets in enhancing the cholinergic deficit that is reported to be underlying the decline in cognitive global functioning and behavioral status that is observed in AD [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although the etiology of AD remains unknown, previous studies revealed that cholinesterase (ChE) activity should be regulated at certain critical stages of AD pathogenesis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Among the many effective treatment strategies, the inhibition of AChE and BChE was one of them that blocked cholinergic activity and raised levels of ChE [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Both the AChE and BChE inhibitors are developed and employed in the treatment of Alzheimer's disease through enhancing the cholinergic neurotransmitter activity in the brain, therefore minimizing the symptoms of AD [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The cholinergic hypothesis entails that AD has been associated with a dysfunction in the central nervous system (CNS) and loss of cholinergic ability [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A decrease in cholinergic functions has been linked to diminished functioning of the brain, which comes with old age[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Such loss of cholinergic activity can be attributed to many factors, including the generation of amyloid peptide and the agglomeration of the tau protein, among others, stress, and an abundance of transition metals [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].Three of the four approved Alzheimer's disease-treating drugs so far have been AChE inhibitor development programs [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Alzheimer's dementia has been treated using tacrine (1, 2, 3, 4- 4-tetrahydro-9-aminocridine) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. It became the first AChE inhibitor to be approved by the FDA, and numerous AChE inhibitors such as galantamine, donepezil, and rivastigmine were developed in the following years [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. A large number of plant extracts have been studied for their ability to treat neurological and cognitive issues. Galantamine is the initial AChE inhibitor of plant origin that was found [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Numerous herbal medicines such as olive, tea, blueberry, strawberry, peppermint, walnut, immortelle, and sage have been reported to possess AChE-inhibiting effects due to the presence of polyphenols [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Curcumin, (-)-epigallocatechin-3-gallate (EGCG), and several flavonoids were also effective AChE inhibitors when isolated [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Bisphenols have structure-specific inhibitory activity and are capable of inhibiting either acetylcholinesterase (AChE) or butyrylcholinesterase (BChE). Green tea and its principal active phenolic compound, EGCG, turmeric curcumin, and resveratrol have all been associated with an AChE inhibitor [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Naringenin, a significant flavonoid in citrus, has been shown to have AChE inhibitory activity in vitro and has been demonstrated to be anti-amnesic in vivo[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Although the inhibitory effect of the flavonol quercetin has not been studied in vivo, it also appears to influence cholinergic dysfunction and brain blood flow [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Previously, the inhibition of AChE was the primary target of treatment; nevertheless, some studies have shown that both AChE and BChE inhibition play a significant role in the pathophysiology and pharmacological management of AD [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In addition to the evidence of BChE's role in cholinergic control and the proposed role of BChE in the development of AD, dual inhibition could provide other advantages, particularly in the long term [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The only available dual cholinesterase inhibitor that is clinically used is rivastigmine. It affects enzymes and is active in late-stage AD when BChE levels increase. The next-generation therapeutic approach is dual inhibition of cholinergic support with an antioxidant, anti-amyloid, or multi-target effect [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Current medications (donepezil, galantamine, and rivastigmine) lack efficacy and tolerability, and Alzheimer's disease is a highly complex and multifactorial pathology with involvement of multiple neurotransmitter systems, inflammation, oxidative stress, and protein accumulation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Thus, it is of interest to develop new dual inhibitors and non-alkaloid candidates discovered among flavonoids. The polyphenolic compounds that occur naturally not only have antioxidant and anti-inflammatory effects but have also been found to interact with both acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), making them of interest as potential multitarget-directed ligands (MTDLs) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eLoquat, scientifically referred to as Eriobotrya japonica Lindl. The Rosaceae has been used as a traditional medicine in curing many diseases. Loquat has attracted recent interest due to its high phytochemical content, specifically its phenolic content, flavonoids, and terpenoids, which have antioxidant, anti-inflammatory, and enzyme-inhibitory effects. Such bioactive substances have rendered the loquat a promising source to formulate functional foods and natural medicines [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The existing literature highlights the inhibitory activity of phenolic compounds extracted from Eriobotrya japonica on acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). A variety of phenolic compounds, such as tyrosol derivatives and flavonoids, were identified in different parts of plants using phytochemical profiling with ultra-high-performance liquid chromatography in combination with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). The phenolic extracts possessed a high enzyme inhibitory activity, with the root extract exhibiting the highest BChE inhibition (3.64 mg GALAE/g). These findings suggest that E. japonica phenolics have therapeutic potential to be utilized as a natural cholinesterase inhibitor, which paves the way for exploring more research on neurodegenerative disorders [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe search for new or alternative cheap molecules of natural origin is constantly desired, and it is still under investigation. Computational techniques are one of the quickest and most inexpensive methods. Therefore, through computational biology, it has been found that different groups of chemicals found in both plants and the marine environment have been screened and have been reported to possess a high inhibitory effect on cholinesterase. Nevertheless, fruits do not investigate cholinesterase inhibitors. In this study, therefore, we have carried out a virtual screening to discover new cholinesterase inhibitors in Japonica and also reported the molecular conformations of Japonica chemicals that interact with cholinesterase. Docking was applied to get more information on the significance of binding interactions of the prospective new molecules to treat AD.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Target proteins retrieval and preparation\u003c/h2\u003e\u003cp\u003eThe 3D X-ray crystal structure of both proteins AChE (PDB ID: 4EY7) and BChE ( PDB ID: 5DYW) was downloaded from the protein data bank PDB (\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) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The Protein Preparation Wizard panel of Schr\u0026ouml;dingerSuite2022-3 was used to prepare the proteins co-crystallized with the native ligands. The target proteins were ready to assign bond ordering, adding hydrogen or forming disulfide bonds, and Prime was used to fill in missing side chains and loops. The protein was reduced using OPLS3, after which it was optimized [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Finally, the receptor grid file was created to define the ligand-binding pocket.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Ligand retrieval and preparation\u003c/h2\u003e\u003cp\u003eThe previous literature was used to retrieve the fifty-four phenolic phytocompounds of the Eriobotrya japonica [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. PerkinElmer Informatics (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://informatics.perkinelmer.com\u003c/span\u003e\u003cspan address=\"https://informatics.perkinelmer.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to construct the 2D and 3D structures and SDF file of the compounds. A control molecule, rivastigmine, was applied, and its chemical structure was downloaded from PubChem. LigPrep of Schr\u0026ouml;dingerSuite2022-3 was used to generate ligands. It was done by recreating the structures in three dimensions with low energy and proper chiralities. It was assumed that all ligands could exist in potential ionized forms at physiologic pH 7.2 +/- 0.2 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Receptor grid generation\u003c/h2\u003e\u003cp\u003eThe binding orientation and the size of the active site of protein-ligand docking are determined by receptor grid generation. Scoring coordinates of AChE and BChE binding pocket were identified utilizing the receptor grid generation module of Schrodinger Maestro 12.5 based on the co-crystallized ligand [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Molecular docking procedure\u003c/h2\u003e\u003cp\u003eThe prepared ligands were docked into the defined active site of AChE and BChE via in Schrodinger Maestro 12.5 Glide-SP (standard precision), followed by XP (extra precision) to correct false-positive results. The van der Waals scaling factor was set at 0.80 for the ligand atoms. The docking protocol was validated by splitting the co-crystallized ligand from the protein, preparing it, and re-docking it into the binding site of AChE and BChE. The calculated root-mean-square deviation (RMSD) of AChE and BChE was 0.6652\u0026Aring; and 2.215\u0026Aring;, respectively (normal range: 1\u0026ndash;2 \u0026Aring;), confirming the reliability and reproducibility of the docking approach.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Evaluation of Drug profile through ADME and toxicity analysis\u003c/h2\u003e\u003cp\u003ePharmacokinetics of the chosen phytochemicals was analyzed in the Swiss ADME (\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) and PKCSM (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://biosig.unimelb.edu.au/pkcsm/\u003c/span\u003e\u003cspan address=\"http://biosig.unimelb.edu.au/pkcsm/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The server was uploaded with canonical SMILES of the molecules. The compound was chosen that crosses the blood-brain barrier only. The determination of pharmacokinetics features and drug-likeness was carried out using the Lipinski Rule of Five (LRF). The rule consisted of four parameters that gauged the molecular weight of the phytochemicals, hydrogen donors, hydrogen acceptors, and lipophilicity. Bioavailability of the phytochemicals was also analyzed using the server [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Then, the phytochemicals' toxicity was analyzed with the Pro Tox-II webserver (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://tox-new.charite.de/protox_II/\u003c/span\u003e\u003cspan address=\"https://tox-new.charite.de/protox_II/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The online server can predict the toxicity of compounds by ranking the compounds' toxicity on a scale of 1 (toxic) to 6 (non-toxic) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Density functional theory analysis\u003c/h2\u003e\u003cp\u003eThe theoretical approaches used to compare the chemical and biological activities of compounds are nowadays widespread. The study of physicochemical properties of some bioactive compounds of E. Japonica using a quantum chemical calculation through density functional theory (DFT) was conducted to predict compounds with strong biological activities. DFT calculation using the B3LYP functional method and 6-31G basis set as per the Gaussian 09W package [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Due to the calculations conducted with the help of this approach, a significant number of parameters can be derived. Some of the parameters that are found during the calculations are highest occupied molecular orbital energy (E\u003csub\u003eHOMO\u003c/sub\u003e), lowest unoccupied molecular orbital energy (E\u003csub\u003eLUMO\u003c/sub\u003e), energy band gaps (Eg) ionization energy (I), electron affinity (A), chemical hardness (η), chemical softness (δ), chemical potential (\u0026micro;), electronegativity (χ), electronic energy, enthalpy, Gibb free energy and dipole moment (D)) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cp\u003e\u003cb\u003eDocking Results\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe fifty-four compounds were docked with both proteins in their active site. The compounds that were selected were those that crossed the blood-brain barrier and displayed high binding affinity with both proteins. Chrysin will be depicted as the top hit compound based on binding scores and BBB (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The molecular docking indicates that the natural compound selected from the Japonica interacted with acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) in their active pockets. In contrast to the control drug Rivastigmine, which was selected. The most desirable is a parasympathomimetic or cholinergic agent of the cholinesterase inhibitor type that acts as a dual-targeted inhibitor of AChE and BChE [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This drug has U.S. Food and Drug Administration (FDA)-approved status for treating Alzheimer\u0026rsquo;s disease and other neurological disorders [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The binding of all types of compounds was discovered to occur readily at the same site with some deviation. Some of the key amino acid residues were identified in the interaction between the chrysin (CID:5281607) and PDB ID 4EY7, which is attributed to the stability and specificity of the binding. Chrysin was found to have a binding mode characterized by predominant π-π stacking and π-π T-shaped interactions, signifying that it had great affinity to the aromatic gorge of AChE, with most of the interactions involving residues Tyr72, Tyr124, Tyr337, Tyr341, Phe295, Phe338, and Trp286. These aromatic residues have been found to play an essential role in the recognition of substrate and stabilization of ligands. Also, chrysin established two typical hydrogen bonds with Tyr72 and Tyr124, further stabilizing the molecule in the active site of the enzyme and adding to the binding affinity. Remarkably, these interactions indicate that chrysin binds to the peripheral anionic site (PAS) of AChE, possibly blocking the access to acetylcholine or aggregation of amyloid-beta, thus making it a prospective scaffold in multifunctional Alzheimer therapy.\u003c/p\u003e\u003cp\u003eConversely, the binding interaction analysis of Rivastigmine with acetylcholinesterase (AChE, PDB ID: 4EY7) shows a wide array of stabilizing interactions that hold the molecule in place inside the catalytic active site gorge of the enzyme. A standard hydrogen bond is seen between the carbonyl oxygen of Rivastigmine and Tyr124, which is a residue known to be involved in substrate orientation. Also, π-π stacking and π-alkyl interactions are established with some of the most essential aromatic residues, such as Tyr341, Tyr337, Tyr72, and Trp286, that are components of the peripheral anionic site (PAS) and the catalytic anionic site (CAS) of AChE [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Such interactions play an essential role in ligand stabilization and enzyme inhibition. Also, His447, part of the catalytic triad (Ser203, His447, Glu334), is involved in a 5\u0026ndash;6 stacking interaction and may be involved in a pseudo-irreversible covalent bond formation characteristic of carbamate inhibitors such as Rivastigmine. Phe338 also plays a role in the 2-p stacking that promotes hydrophobic interaction in the active-site gorge. Such a widespread interaction profile indicates that Rivastigmine not only carbamylates the catalytic serine, but also binds to several residues in the binding gorge, which enhances its binding affinity and residence time, in line with its application as a dual AChE/BChE inhibitor in the treatment of Alzheimer's disease [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The comparative study indicates that the two compounds, although effective in targeting critical residues in the AChE active site region, are presumably likely to act differently as inhibitors. Chrysin, which has a longer and aromatic system and a peripheral binding motif, is expected to behave mainly as a PAS occupant and hydrophobic stacker and may contribute to allosteric regulation or an anti-amyloid agent in addition to inhibiting the enzyme \u003cb\u003e(Table\u0026nbsp;1, Fig.\u0026nbsp;2).\u003c/b\u003e\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\u003eDocking interactions of Rivastigmine (control) and Chrysin with AChE (PDB:4EY7).\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=\"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=\"left\" 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\u003eCompounds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDocking score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePubChem ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResidue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eInteraction Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDistance(\u0026Aring;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eRivastigmine\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(Control)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-7.1kcal/mol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e77991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTRP286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Pi Stacked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.86\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Pi Stacked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePHE338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Alkyl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHIS447\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Alkyl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eChrysin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-9.3kcal/mol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e5281607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePHE295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHOH728\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi\u0026ndash;Pi Stacked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.81\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR 337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi\u0026ndash;Pi T-shaped\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.47\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\u003c/p\u003e\u003cp\u003eChrysin (CID:5281607) has 2, 3-dimensionally stacking interactions with Trp82 and Trp430 in the active site gorge, and hydrogen bonding with Thr120 and Glu197 of BChE (Protein ID 5dyw). It is worth noting that the hydroxyl functionalities of the flavone nucleus at positions 5 and 7 are involved in standard hydrogen bonding with Glu197, which forms the catalytic triad. Further stabilization is offered by 3-sigma interaction with Ala328 as well as carbon-hydrogen interactions with Gly439, pointing to a more complex binding mechanism that includes both polar and hydrophobic interactions. This complex binding motif, present non-catalytically adjacent and not directly at the catalytic site, suggests the possibility of an allosteric modulation mechanism, which can be added to the known antioxidant and anti-inflammatory actions of chrysin in neuroprotection [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the Docking complex of Rivastigmine with butyrylcholinesterase (BCHE; PDB ID: 5DYW), various meaningful molecular interactions enable stable binding in the active site of the enzyme. The binding of rivastigmine is stabilized through conventional hydrogen bonds with the backbone amide nitrogen of Gly116 and Gly117, critical residues that surround the oxyanion hole of BCHE. Such hydrogen bonds play essential roles in ligand stabilization in the catalytic pocket. An interaction between a carbon-hydrogen bond and His438 also helps to position the ligand in the right way. The aromatic ring of Rivastigmine is involved in 2 pi-pi T-shaped and pi-sigma interactions with Tyr332, which suggests the significance of aromatic stacking in keeping the ligand in the enzyme gorge. Also, there is an O-alkyl interaction with Trp82 and Trp231, which form hydrophobic interactions that strengthen the binding affinity. All these interactions show that Rivastigmine interacts with both the catalytically active site and the peripheral anionic site of BChE, which agrees with its identity as a dual cholinesterase inhibitor [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The interaction of chrysin with Glu197, a member of the catalytic triad, does not necessarily affect the catalytic serine but is in its vicinity, indicating the possible allosteric regulation of the activity and not active-site inhibition. The difference suggests Rivastigmine as a pseudo-irreversible inhibitor that directly inactivates the catalytic serine [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In contrast, Chrysin can have modulatory effects that increase its neuroprotective nature without permanently impairing the activity of the enzyme. Such differences in binding orientation and interaction profile underline the complementary nature of synthetic and natural inhibitors in the development of multi-targeted therapeutics of Alzheimer's disease. Therapeutically, the results indicate that chrysin derivatives may be designed as multifunctional molecules acting on cholinesterase inhibition as well as oxidative stress pathways, and Rivastigmine may continue to be the model of effective, selective cholinesterase inhibitors. The structural observations of this study can inform the logical development of new BChE inhibitors that merge desirable properties of each of the two molecular scaffolds \u003cb\u003e(Table\u0026nbsp;2, Fig.\u0026nbsp;3).\u003c/b\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\u003eDocking interactions of Rivastigmine (control) and Chrysin with BChE (PDB:5DYW).\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=\"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=\"left\" 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\u003eCompounds\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDocking score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePubChem ID\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eResidue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eInteraction Type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDistance(\u0026Aring;)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eRivastigmine\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e(control)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-7kcal/mol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e77991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLY116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLY117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTYR332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eπ\u0026ndash;π T-shaped\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTRP82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eπ\u0026ndash;π T-shaped\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHIS438\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eπ\u0026ndash;Sigma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e5.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eChrysin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e-7.7kcal/mol\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e5281607\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLU197\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTHR120\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eH-bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.20\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTRP82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Pi Stacked\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGLY439\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eC-H bond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALA328\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePi-Sigma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.90\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\u003c/p\u003e\n\u003ch3\u003eADME and toxicity Results\u003c/h3\u003e\n\u003cp\u003eThe pharmacokinetic and toxicity profile of the selected phytochemical chrysin demonstrates several favorable properties for drug development. Swiss ADME results indicate that only six compounds cross the blood-brain barrier \u003cb\u003e(Fig.\u0026nbsp;4)\u003c/b\u003e. Chrysin was chosen because of its high binding affinity with both proteins and has a good bioavailability score.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eAbsorption and Bioavailability\u003c/h3\u003e\n\u003cp\u003eThe PKCSM prediction given in Table\u0026nbsp;3 shows that chrysin is good intestinal (93.952%) and implies that it has good oral bioavailability. However, it is moderately soluble in water (-3.588 log S), which may limit absorption in the gastrointestinal tract and lower systemic exposure. A moderate CaCO\u003csub\u003e2\u003c/sub\u003e permeability (1.037 log Papp) implies that chrysin can potentially cross intestinal epithelial permeability barriers. However, its substrate status towards P-glycoprotein implies that efflux-mediated reduced absorption is possible. Also, the skin permeability (-2.751 log Kp) was recorded as insignificant; therefore, transdermal delivery was not an option in administering the drug [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eDistribution and Tissue Penetration\u003c/h3\u003e\n\u003cp\u003eThe low distribution volume (0.065 L/kg) shows that chrysin might be mostly circulating in the systemic circulation but not in tissues. The plasma protein binding was estimated to be 84.9%, so 15.1% is unbound to perform pharmacological activity. Importantly, the blood-brain barrier (BBB) penetration of chrysin is moderate ( -0.05 log BB) and the central nervous system permeability is moderate (-1.924 log PS), indicating a moderate likelihood of central nervous system activity [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMetabolism and Drug Interaction Potential\u003c/h3\u003e\n\u003cp\u003eChrysin is not a substrate of CYP2D6 or CYP3A4, which decreases the propensity of interactions with drugs metabolized by these enzymes[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Nevertheless, it is an inhibitor of CYP1A2, CYP2C19, and CYP2C9, which may disrupt the metabolism of other drugs that one may be taking, like warfarin, theophylline, and some antidepressants. This inhibition pattern requires caution in the case of polypharmacy.\u003c/p\u003e\n\u003ch3\u003eExcretion and clearance\u003c/h3\u003e\n\u003cp\u003eIts total clearance rate (0.584 mL/min/kg) signifies moderate clearance primarily via hepatic pathways since chrysin is not a substrate of the renal OCT2 transporter, and thus there is negligible renal excretion.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePKCSM pharmacokinetic parameters of the selected phytochemicals\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePharmacokinetic Properties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSelected Phytochemical\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProperties\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChrysin\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003e\u003cb\u003eAbsorption\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWater solubility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-3.588\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCaco2 permeability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntestinal absorption (human)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.952\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSkin Permeability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.751\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP-glycoprotein substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eyes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP-glycoprotein I inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP-glycoprotein II inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eDistribution\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVDss (human)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFraction unbound (human)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.151\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBBB permeability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCNS permeability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.924\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003e\u003cb\u003eMetabolism\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP2D6 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP3A4 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP1A2 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP2C19 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP2C9 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP2D6 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCYP3A4 inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eExcretion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Clearance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.584\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRenal OCT2 substrate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e\u003cp\u003e\u003cb\u003eToxicity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAMES toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMax. tolerated dose (human)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.175\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ehERG I inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ehERG II inhibitor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOral Rat Acute Toxicity (LD50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.206\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOral Rat Chronic Toxicity (LOAEL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.207\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHepatotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSkin Sensitization\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eT.Pyriformis\u003c/em\u003e\u0026nbsp;toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.643\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinnow toxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eToxicity and Safety Assessment\u003c/h3\u003e\n\u003cp\u003eAnalysis by Stop-Tox \u003cb\u003e(Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e)\u003c/b\u003e and Pro-Tox II showed that chrysin is non-mutagenic (AMES negative) and does not block HERG channels, which suggests the low likelihood of genotoxicity and cardiotoxicity. Nonetheless, there is oral rat LD50 (2.206 mol/kg) and chronic toxicity (LOAEL: 1.207 log mg/kg/day) data indicating that high doses might be toxic. Pro-Tox II analysis is given in Table\u0026nbsp;4, which also suggests the possibility of hepatotoxicity (68%), interaction with nuclear receptors, including AhR (95%), ER (94%), and AR (99%), and potentially endocrine-modulating effects. Skin sensitization was flagged as well (70% probability), and one should be careful about topical applications.\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\u003eParameters obtained through the Pro-Tox II\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eClassification\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTarget\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eChrysin\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePre\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePro\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\u003eOrgan toxicity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHepatotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eToxicity endpoints\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCarcinogenicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eImmunotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMutagenicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCytotoxicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e\u003cp\u003e\u003cb\u003eTox21-Nuclear receptor signaling pathways\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAhR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAR-LBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAromatase\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eER-LBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePPAR-Gamma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003enrf2/ARE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eTox21-Stress response pathways\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMMP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eATAD5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\n\u003ch3\u003eDensity functional theory Results\u003c/h3\u003e\n\u003cp\u003eThe reactivity and interaction potential of chrysin with cholinesterase enzymes were further assessed by evaluation of the electronic properties of chrysin with the help of Density Functional Theory (DFT). Frontier molecular orbitals HOMO (Highest Occupied Molecular Orbital) and LUMO (Lowest Unoccupied Molecular Orbital) were visualized to determine the electron-donating and electron-accepting areas of the molecule[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The HOMO was mainly concentrated on the phenolic A-ring and the neighbouring double bond system; thus, these regions can be considered central points of electron donation and possible nucleophilic contacts with active site residues of AChE and BChE. Conversely, LUMO was localized near the carbonyl group and the neighbouring aromatic systems, which indicates the electrophilic reaction and the hydrogen bonding with nucleophilic amino acids in the enzyme binding pocket. The electrostatic potential map also justified these results, and areas colored red indicate electron-rich areas (namely, the hydroxyl and carbonyl groups) and areas colored blue indicate electron-poor areas. Such electronic features indicate that chrysin possesses well-balanced nucleophilic and electrophilic centers, increasing its ability to participate in both hydrogen bonding and pi-pi stacking interactions in the cholinesterase enzyme catalytic gorge. This bilateral interaction potential may also be a factor in its inhibitory potency against AChE and BChE and is of interest as a multifunctional Alzheimer's therapeutic agent. Its capacity to form stable complexes through the hydrogen bond and aromatic interaction is enhanced by the presence of 1-electron-rich systems and polar functional groups, which also favours its medicinal properties. Some of the parameters that can be derived through the calculation include highest occupied molecular orbital energy (E\u003csub\u003eHOMO\u003c/sub\u003e), lowest unoccupied molecular orbital energy (E\u003csub\u003eLUMO\u003c/sub\u003e), energy band gaps (Eg) ionization energy (I), electron affinity (A), chemical hardness (η), chemical softness (δ), chemical potential (\u0026micro;), electronegativity (χ), electronic energy, enthalpy, Gibb free energy and dipole moment (D) are given in Table.5. DFT calculations provided the data on the molecular properties of chrysin. It is chemically moderately reactive (the HOMO-LUMO energy gap is 0.16295 A.U. / 4.43 eV) and a moderate electrophile (electrophilicity index is 3.611 eV), which agrees with its antioxidant character. It is a polar molecule (dipole moment 5.5618 Debye) and affects solubility and binding affinities [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\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\u003eDFT analysis parameters of the top hit compound\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScore\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\u003eDipole moment (Debye)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5.5618\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHOMO (A.U)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.22848\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLUMO (A.U)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.06553\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEnergy Gap (ΔE\u003c/b\u003e\u003csub\u003e\u003cb\u003eGap\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.16295\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIonization Potential (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6.221\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eElectron affinity (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.783\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eElectronegativity χ (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eElectrochemical potential \u0026micro; (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;4.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHardness η (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.219\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSoftness S (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.451\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eElectrophilicity ω (eV)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.611\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\u003eMechanistically, these electronic features rationalize two experimentally-observed phenomena: (i) that chrysin can scavenge radicals (antioxidant activity), which is dependent on the availability of phenolic H-atoms and conjugation to stabilize the resulting radical, properties that correlate with HOMO localization and ΔE, and (ii) that chrysin can moderately but reproducibly inhibit AChE/BChE, where noncovalent interactions (H-bonding, 2-dimensional stacking, hydrophobic contacts A similar trend has been observed in several recent DFT and docking studies of flavonoids molecules which have localized HOMO on phenolic rings and a sufficient 6E value exhibit both antioxidant reactivity and good docking pose in cholinesterases [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The DFT calculations place chrysin in the category of electronically balanced flavones whose HOMO/LUMO distributions, modest HOMO-LUMO gap, reasonable electrophilicity, and significant dipole moment mutually explain its overall activity as an antioxidant and moderate AChE/BChE inhibitory capacity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents convincing in silico data that phenolic compounds found in Eriobotrya japonica, especially Chrysin, have a potential inhibitory effect against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which are the most essential enzymes in Alzheimer's disease (AD). Molecular docking showed a binding affinity of Chrysin with key residues in the active site of both enzymes. DFT analysis further indicated its good electronic and structural characteristics that justify its antioxidant and neuroprotective effects. Pharmacokinetic and toxicity modelling showed that chrysin has good oral bioavailability and a safety margin. Still, specific barriers, including moderate water solubility, P-gp efflux, and hepatotoxicity at high doses, must be overcome before clinical usage. Collectively, these results indicate that chrysin may be a useful natural scaffold to develop multifunctional therapeutic agents against cholinesterase inhibition and oxidative stress in AD. However, there is a need to conduct more in vitro and in vivo validation and optimize formulation strategies to establish its efficacy, safety, and translational potential in the treatment of Alzheimer's disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis work has received no funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMubashir Afzal: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing \u0026ndash; original draft.Aleena Sajjad: Data curation, Formal analysis, Investigation, Methodology, Software.Muhammad Bilal Iqbal Rehmani: Formal analysis, Investigation, Validation, Visualization.Sameer Nasir: Formal analysisMuhammad Yahya Waseem: Data curation, Formal analysis, Resources, Software.Muhammad Asif Akram: Conceptualization, Project administration, Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.Iqra Irshad: Formal analysis, Resources, Validation.Shagufta Bashir: Validation, Visualization, Writing \u0026ndash; review \u0026amp; editing.Mehdi Rahimi: Conceptualization, Funding acquisition, Project administration, Supervision, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript and supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFerreira-Vieira, H. \u003cem\u003eT et al Alzheimer's disease: Target. cholinergic Syst.\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e(1): 101\u0026ndash;115. (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLane, C. A. \u0026amp; Hardy, J. J.E.j.o.n. Schott. \u003cem\u003eAlzheimer's disease\u003c/em\u003e. \u003cb\u003e25\u003c/b\u003e (1), 59\u0026ndash;70 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen, Z. R. et al. \u003cem\u003eRole of cholinergic signaling in Alzheimer\u0026rsquo;s disease\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e(6): p. 1816. (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJasiecki, J. \u0026amp; Targońska, M. and B.J.I.j.o.m.s. Wasąg, \u003cem\u003eThe role of butyrylcholinesterase and iron in the regulation of cholinergic network and cognitive dysfunction in Alzheimer\u0026rsquo;s disease pathogenesis.\u003c/em\u003e 22(4): p. 2033. (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDubois, B. et al. \u003cem\u003eAdvancing research diagnostic criteria for Alzheimer's disease: the IWG-2 criteria.\u003c/em\u003e 13(6): pp. 614\u0026ndash;629. (2014).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFranjesevic, A. J. et al. \u003cem\u003eResurrect. reactivation acetylcholinesterase butyrylcholinesterase\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e(21): 5337\u0026ndash;5371. (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHughes, C. G. et al. \u003cem\u003eAssociation between cholinesterase activity Crit. Illn. brain Dysfunct.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e(1): 377. (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGreig, N. H., Lahiri, D. K. \u0026amp; Sambamurti, K. J. I. \u003cem\u003eButyrylcholinesterase: important new. target. Alzheimer's disease therapy\u003c/em\u003e \u003cb\u003e14\u003c/b\u003e(S1): 77\u0026ndash;91. (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalawu, F. K. \u0026amp; Umar, J. T. and A.B.J.A.o.A.m. Olokoba. \u003cem\u003eAlzheimer's disease: Rev. recent. developments\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e(2). (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBekdash, R. \u003cem\u003eThe cholinergic system, the adrenergic system and the neuropathology of Alzheimer\u0026rsquo;s disease\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e(3): p. 1273. (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR\u0026ouml;sler, M. J.I.j.o.c.p.S. \u003cem\u003eThe efficacy cholinesterase inhibitors Treat. Behav. symptoms dementia\u003c/em\u003e (127): pp. 20\u0026ndash;36. (2002).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLane, R. M. \u0026amp; Kivipelto, M., and N.H.J.C.n. Greig, \u003cem\u003eAcetylcholinesterase and its inhibition in Alzheimer disease\u003c/em\u003e. \u003cb\u003e27\u003c/b\u003e(3): pp. 141\u0026ndash;149. (2004).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnsari, N. \u0026amp; Khodagholi, F. J. C. \u003cem\u003eNatural products as promising drug candidates for the treatment of Alzheimer\u0026rsquo;s disease: molecular mechanism aspect\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e(4): pp. 414\u0026ndash;429. (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchliebs, R. T.J.B.b.r. Arendt. \u003cem\u003echolinergic Syst. aging neuronal degeneration\u003c/em\u003e. \u003cb\u003e221\u003c/b\u003e (2), 555\u0026ndash;563 (2011).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoreira, N. C. 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Gasteiger. \u003cem\u003eElectronegativity equalization: application parametrization\u003c/em\u003e. \u003cb\u003e107\u003c/b\u003e (4), 829\u0026ndash;835 (1985).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eObot, I. et al. \u003cem\u003eTheoretical evaluation of triazine derivatives as steel corrosion inhibitors: DFT and Monte Carlo simulation approaches.\u003c/em\u003e 42: pp. 4963\u0026ndash;4983. (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMalak, N. et al. \u003cem\u003eDensity functional theory calculations and molecular docking analyses of flavonoids for their possible application against the acetylcholinesterase and triose-phosphate isomerase proteins of Rhipicephalus microplus\u003c/em\u003e. \u003cb\u003e28\u003c/b\u003e(8): p. 3606. (2023).\u003c/span\u003e\u003c/li\u003e\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":"Eriobotrya Japonica, Alzheimer’s disease, acetylcholinesterase, butyrylcholinesterase, Molecular docking, pharmacokinetics","lastPublishedDoi":"10.21203/rs.3.rs-7521725/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7521725/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAlzheimer’s disease (AD) is the most common dementia causing disease in the elderly and is strongly associated with cholinergic dysfunction. The crucial enzymes in this mechanism are acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), which are prominent therapeutic targets. Recently, natural phytocompounds have been considered as safer substitutes to synthetic inhibitors. In this study, fifty-four phenolic compounds of\u003cem\u003e Eriobotrya japonica\u003c/em\u003e were chosen from the literature and evaluated using in-silico methods as prospective dual AChE and BChE inhibitors. Based on molecular docking with the Schrodinger Suite, chrysin appeared to be the most promising candidate as it exhibited high binding affinity and stable interaction with the catalytic residues of both enzymes. Pharmacokinetic and ADME studies indicated that the drug would be well-absorbed and bioavailable orally with low acute toxicity. Moderate solubility, blood-brain barrier penetration and potential CYP-mediated interactions were noted. The electronic stability, antioxidant behavior, and interaction with target proteins of chrysin were also verified by density functional theory (DFT) analysis. Finally, the obtained results point to the potential of chrysin of\u003cem\u003e E. japonica \u003c/em\u003eas a multitarget lead compound in the treatment of AD, which exerts combined enzyme inhibition and neuroprotective effects. Its therapeutic potential should be confirmed by further in-vitro and in-vivo studies.\u003c/p\u003e","manuscriptTitle":"Exploring potential inhibitors from Eriobotrya japonica targeting AChE and BChE in Alzheimer's Disease through docking, ADMET profiling, and DFT analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-25 19:39:01","doi":"10.21203/rs.3.rs-7521725/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":"5f0c8e4f-cf3c-4e85-ad6c-94356430782a","owner":[],"postedDate":"September 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55192457,"name":"Biological sciences/Biochemistry"},{"id":55192458,"name":"Physical sciences/Chemistry"},{"id":55192459,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":55192460,"name":"Biological sciences/Drug discovery"},{"id":55192461,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-10-06T13:09:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-25 19:39:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7521725","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7521725","identity":"rs-7521725","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}