Anthelmintic Activity of Pineapple: In Silico Molecular docking and Molecular Dynamics Simulation

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Helal Uddin Chowdhury, Mohuya Majumder, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3859053/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 Helminths are a major group of pathogens, responsible for a wide range of diseases in human and many other animals through their parasitic interaction with the host. At present a number of helminth species are posing serious threat due to their adroit evasion technique from the immune system and resistance to conventional anti-parasitic drugs. In order to find drug to cope with this challenge, a series of computational analysis was conducted on different compounds identified in Pineapple ( Ananas comosus (L.) Merr.). SwissADME tool predicted the drug likeness of the selected compound based on the Lipinski’s rule of five. Out of 33 molecules, five compounds- syringaldehyde, p-hydroxybenzaldehyde, benzaldehyde, phenol and ethyl acetate showed promising binding affinity ranging from − 5.011 to -6.519 as depicted from docking score against tubulin-colchicine, potential receptor site for drug designing against helminths. MM-GBSA analysis showed that Syringaldehyde-1SA0 complex attained lower binding energy of -35.639 kcal/mol relative to ethylacetate, benzaldehyde, p-hydroxybenzaldehyd, and phenol complex. Molecular dynamics simulation results further confirmed the potential anti-helminthic activity of syringaldehyde. The receptor-ligand complex showed promising RMSD and RMSF value of 2.008Å and 1.324Å respectively with the major hydrophobic interactions remaining unchanged even after 10 ns simulation. Thus, in this study, syringaldehyde was found to be a potential inhibitor of the tubulin-cholchicine receptor to prevent the progression of helminthic infection in the host cell. Performance of further clinical experiment with this compound, can reveal its true potential as a novel anti-helminthic drug in near future. Ananas comosus pineapple SwissADME computational analysis molecular dynamics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. INTRODUCTION Diseases due to parasitic nematodes (also referred to as roundworms) have been associated with a wide variety of clinical complications in both animal and human perdurable and long-term morbidity. Helminthic infections (Tape worms, hook worms, round worms) are also acquainted as Neglected Tropical Diseases (NTDs) that mostly invaded in less developed countries owing to their faulty sanitation scheme and unavailability of cognitive knowledge (Ranjan et al. 2018 ). Of those, infection in the gastrointestinal tract (GIT) and lungs are the most frequent and the most hazardous for humans and animals (Zajíčková et al. 2020 ). Helminths differ a lot from many other parasites; these organisms multiply within the definitive host. For survival, they develop anthelmintic resistance in turn through distinctive biochemical and gene expression processes. Although their potential to evade host immune defenses is not completely comprehended yet (Jayaraj et al. 2014 ). In addition to these nematode’s artful evasion of host immune response, fact that is more alarming is their resistance to conventionally prescribed drugs. Conventional synthetic drugs such as mebendazole, pyrantel, oxamniquine, praziquantel, tetrahydropyrimidines have been reported to less responsive due to their poor bioavailability and extensive application (Ullah et al. 2017 ). This reduced activity can be attributed to the helminths’ evolutionary heritable changes or these compounds’ lack of ability to perform on a populace of parasites. Plant can play an important role in this context; about 25% of the conventional drugs consist of plant-derived compounds (Rates 2001 ). Finding new drug compound has become lot easier with the advent of computational drug screening tools that involves molecular docking, molecular dynamics simulation and many other molecular attributes. This modern technique is further associated with adequate morphological and chemical information on parasites and plant products which is also corroborated by numerous plant-derived essential oils’ and metabolites’ exhibiting anti-parasitic activity (Chy et al. 2019 ; David et al. 2016 ; Nayak et al. 2012 ; van Vuuren et al. 2006 ). In this regard, molecular docking is a feasible computational tool for structural molecular biology and computer-aided drug design (CADD) which widely use to predict two molecule interactions (compound-target enzymes) in three-dimensional space (Soureshjani et al. 2015 ). Furthermore, this drug-protein receptor complex subjected to molecular dynamics (MD) simulation to predict their interactions on the basis of molecular motions including vibration, bond stretching, angle bonding, and bond formation (Ru et al. 2013 ), which actually a force-field based process and utilized in the CADD more thoroughly for the simulation of interacting drug-receptor proteins complex (Pai et al. 2019 ). Due to the presence of various secondary metabolites, like- alkaloids and flavonoids, pineapple is able to exert inhibitory effect against many pathogens. Pineapple ( Ananas comosus (L.) Merr.) is herbaceous, perennial (monocotyledonous) of the liliopsidae family, cultivated at wide ranges of latitude 30˚N and 33˚58ˈS in northern and southern hemisphere respectively, that grows to 1–2 m high and 1–2 m wide (Mahomoodally et al. 2019 ; Raimundo et al. 2019 ) In addition to ample supply of vitamins and minerals, pineapple has also been reported to have many physiologically crucial constituents such as alkaloids, phytate, oxalate, tannins, cardenolides, dienolides, cardiac glycosides, flavonoids, Sulphur containing esters, isoflavones, catechins, anthocyanins, and other phenolic compounds, and the fruit extract can act substrate for the production of ethanol, methane, citric acid, and antioxidant agents (Corzo et al. 2012 ; Dabesor et al. 2017 ; Hossain and Rahman 2011 ; Marlesa and Farnsworthb 1995 ; Nor et al. 2018 ). Studies have shown a wide variety of biological activities such as anti-inflammatory, anthelmintic, antioxidative, anti-browning, anti-diarrhea, digestive aid, and injury healer, with some of this mode of action contributed by the bromelain enzyme complex (Agyare et al. 2014 ; Bahmani et al. 2014 ; Behnke et al. 2008 ; Gurib-fakim 2006 ). This research was intended to evaluate the anthelmintic activity of various compounds identified in Pineapple as well as identify the molecular interactions existing between various phytoconstituents with the target receptors involved in anthelmintic activity of host. 2. MATERIALS AND METHODS 2.1 Phytochemical mining A wide range of phytochemicals; 35 compounds(Adedeji et al. 1991 ) to be exact present in A. comosus were obtained from various literature that reported to isolate from or identify them in the plant extract. The SMILE ID of those compounds were retrieved from PubChem ( https://pubchem.ncbi.nlm.nih.gov/ ) to study their pharmacokinetic properties in the next step. 2.2 Determination of pharmacokinetic properties Drug-like properties or pharmacokinetics of compounds derived through literature review was evaluated by SwissADME ( http://www.swissadme.ch/ ), an online resource following Lipinski’s rule of five. According to that, any chemical constituent should act as a drug when it does not infringe upwards of one of the following criteria: (i) Molecular weight not exceeding 500; (ii) acceptors of H-bonds ≤ 10; (iii) donors of H-bonds ≤ 5; (iv) lipophilicity (LogP) < 5; and (v) molar refractivity between 40 and 130. Lipinski’s rule of five evaluates drug likeness and determine whether a chemical compound when ingested can likely being active as drug in humans. 2.3 Ligand preparation The key prolific and active substances contained in A. comosus species (tracked out by literature review) have been subjected to rigorous molecular docking analysis to evaluate the anthelmintic activities. The concerned phytocompound’s configurations were obtained from NCBI PubChem database, a public molecular information repository. All such phytocompounds were ready through using subsystem LigPrep of the Schrödinger suite (LigPrep, version 42013, Schrödinger). The minimization process was done by using OPLS3 force field. All feasible ionic states were formed with target pH of 7.2 ± 2 using Epik 2.2. For each ligand plausible stereo isomers of lesser energy ring conformations were also devised, one per ligand. 2.4 Receptor preparation Tubulin-colchicine enzyme (PDB: 1SA0) (Ravelli et al. 2004 ) was elected as a target receptor protein and downloaded in Maetsro v11.2 from RCSB Protein Data Bank (Berman et al. 2002 ). The structures were also formulated employing protein preparation wizard of the Schrödinger. At first, concerning receptor had been pre-processed by assigning bond orders, adding hydrogen, filling empty side chains and loops with PRIME and eventually removing all water in the crystal structures. After optimization of these crystal structures, restrain minimization with root mean square deviation (RMSD) 0.3 Å was carried out applying OPLS3 force field. 2.5 Grid generation and molecular docking Using the "Receptor Grid Generation" panel, the minimized protein structures were then used for grid generation. For each protein, a grid implementing the consequent default parameters was set up- Van Der Waals scaling factor 1.00 and charging cut-off value 0.25, according to the force field of OPLS3. A cubic receptor grid box was centroid with a 14 Å × 14 Å × 14 Å size from the center of the selected co-crystallized ligand. The Standard Precision (SP) scoring method of Glide was using for molecular docking assay that was embedded into Schrödinger suite-Maestro version 11.2 (Friesner et al. 2006 ; Friesner et al. 2004 ). 2.6 Prime MM-GBSA (molecular mechanics-generalized born surface area) calculation As a post docking validation tool, Molecular mechanics-generalized Born surface area (MMGBSA) method was utilized by exerting default parameters of Prime MM-GBSA modules embedded in Schrodinger software to calculate the free energies of binding (Jacobson et al. 2002 ; Vijayakumar et al. 2014 ). For calculation purposes Prime MM-GBSA employs optimized potential for liquid simulations (OPLS) force field in conjunction with molecular mechanics energies (EMM), a model for polar solvation based on the VSGB (GSGB), and a solvation term that isn't polar (GNP) (Kar et al. 2020 ). Each protein-ligand complex's absolute free energy of binding was calculated as follows: ∆G bind = ∆G complex – (∆G protein + ∆G ligand ) 2.7 Molecular dynamics simulation Simulation of molecular dynamics was conducted to check the structural stability of the best docking scored protein-ligand complex over water molecules and ions. The simulation was performed with YASARA Dynamics v.19.9.17 (Krieger and Vriend 2015 ) using the default Amber14 (Shao and Zhu 2018 ) force field, and trajectories have been analyzed over 10 ns duration. The specific MD simulation model has been obtained from the syringaldehyde docked complex with receptor tubulin beta chain (PDB code: 1SA0, chain B). The complex was kept in cell length (X = 88.9, Y = 88.9, Z = 88.9) along with the TIP3 cubic simulation water box with periodic boundary condition and PME (Darden et al. 1993a ) algorithm to assign a charge. At pH 7.4 and 298 K, the water density was set to 0.997 g/cmᶾ, and sodium and chloride ions are included (NaCl 0.9%) to neutralize the charge of the system. The system had undergone energy minimization, and simulated annealing refinement and charge to amino acid were assigned using Particle Mesh Ewald algorithm (Darden et al. 1993b ) with cutoff radius 8 Å. The production of MD simulation was subsequently performed for 10 ns time scale using step size of 2.5 fs separately for each complex system and snapshot have been recorded at 100 picoseconds up to 10ns which have been used in the analysis, as done in (John R.Giudicessi, BA.Michael J.Ackerman. 2008) to determine receptor interaction with ligands, root mean square deviation (RMSD) and root mean square fluctuation (RMSF). 3. RESULT 3.1 Pharmacokinetic properties Pharmacokinetic properties of 34 chemical compounds screened through literature survey was determined using Swiss ADME tool, out of which all of them were found to be pharmacologically pertinent. Following the Lipinski’s rule of five, we did find all of the selected molecules passed through this step of screening as no single compound violated more than one rule (Table 1) . Table 1: ADME/T properties of the isolated compounds of Ananas comosus by SwissADME. Name of molecules Pubchem ID Molecular weight 1 (g/mol) Hydrogen bond acceptor 2 Hydrogen bond donor 3 Log P 4 Molar refractivity 5 2-butoxyethanol 8133 118.17 2 1 1.02 33.30 2-Pentanol 22386 88.15 1 1 1.22 27.31 2-Pentanone 7895 201.28 3 1 1.96 59.08 2-phenylethanol 6054 122.16 1 1 1.64 37.38 3-Hydroxyphenethyl alcohol 83404 138.16 2 2 1.25 39.40 3-methylbutanol 31260 88.15 1 1 1.16 27.31 4-Allyl-2,6 dimethoxyphenol 226486 194.23 3 1 2.29 55.55 Acetic acid 176 60.05 2 1 -0.09 13.50 Benzaldehyde 240 106.12 1 0 1.57 31.83 Delta-Hexalactone 13204 114.14 2 0 1.22 30.13 Delta-Octanolactone 12777 142.20 2 0 1.91 39.74 Dimethyl malonate 7943 132.11 4 0 0.18 28.72 Ethyl 4-acetoxyhexanoate 529297 202.25 4 0 1.91 52.75 Ethyl 4-acetoxyoctanoate 529298 230.30 4 0 2.61 62.37 Ethyl acetate 8857 88.11 2 0 0.75 22.63 Ethyl hexanoate 31265 144.21 2 0 2.16 41.85 Ethyl propenoate 8821 100.12 2 0 1.07 26.96 Gamma -valerolactone 7921 100.12 2 0 0.91 25.32 Gamma-Decalactone 12813 170.25 2 0 2.61 49.35 Gamma-Hexalactone 12756 114.14 2 0 1.19 30.13 Gamma-nonalactone 7710 156.22 2 0 2.24 44.55 Gamma-octalactone 7704 142.20 2 0 1.88 39.74 Hexanal 6184 100.16 1 0 1.66 31.16 Hexanoic acid 8892 116.16 2 1 1.47 32.73 Methyl 4-methylpentanoate 17008 130.18 2 0 1.79 37.05 Methyl 5-acetoxyhexanoate 526152 188.22 4 0 1.53 47.95 Methyl butanoate 12180 102.13 2 0 1.15 27.43 Methyl octanoate 8091 158.24 2 0 2.70 46.66 Methyl pentanoate 12206 116.16 2 0 1.57 32.24 4- hydroxybenzaldehyde 126 122.12 2 1 1.17 33.85 Phenol 996 94.11 1 1 1.41 28.46 Propyl acetate 7997 102.13 2 0 1.14 27.43 Syringaldehyde 529894 182.17 4 1 0.93 46.84 Vanillin 1183 152.15 3 1 1.20 40.34 Notes: 1 Molecular weight (acceptable range: <500); 2 Hydrogen bond donor (acceptable range: ≤5); 3 Hydrogen bond acceptor (acceptable range: ≤10); 4 High lipophilicity (expressed as LogP, acceptable range: <5); 5 Molar refractivity should be between 40 and 130. 3.2 Molecular docking analysis There in investigation of anthelmintic activity, the 34 molecules stated above docked for anthelmintic action against crystalline structure of the tubulin-colchicine enzyme (PDB: 1SA0). In reference to tubulin-colchicine receptor enzyme; syringaldehyde and ethyl 4-acetoxyoctanoate generated a great and poor binding affinity score in the range of -6.519 kcal / mol to -0.363 kcal/mol than any other compound (Table 2). Table 2: Docking results of selected compounds from Ananas comosus with 1SA0. Compound Name Compound ID Docking Score 2-butoxyethanol 8133 -1.127 2-pentanol 22386 -3.991 2-pentanone 7895 -4.847 2-phenylethanol 6054 -4.535 3-Hydroxyphenethyl alcohol 83404 -3.922 3-methylbutanol 31260 -2.968 4-Allyl-2,6-dimethoxyphenol 226486 Acetate acid 176 -2.453 Benzaldehyde 240 -5.432 Delta-Hexalactone 13204 -4.754 Delta-Octanolactone 12777 -4.184 Dimethyl malonate 7943 -3.01 Ethyl 4-acetoxyhexanoate 529297 -2.638 Ethyl 4-acetoxyoctanoate 529298 -0.363 Ethyl acetate 8857 -5.011 Ethyl hexanoate 31265 -1.82 Ethyl propenoate 8821 -2.403 Gamma -valerolactone 7921 -4.872 Gamma-Decalactone 12813 -3.444 Gamma-Hexalactone 12756 -4.186 Gamma-nonalactone 7710 -2.487 Gamma-octalactone 7704 -3.995 Hexanal 6184 -2.28 Hexanoic acid 8892 -2.271 Methyl 4-methylpentanoate 4275592 -2.652 Methyl 5-acetoxyhexanoate 526152 -2.442 Methyl butanoate 12180 -3.412 Methyl octanoate 8091 -1.36 Methyl pentanoate 12206 -2.494 p- hydroxybenzaldehyde 126 -5.608 Phenol 996 -5.233 Propyl acetate 7997 -3.715 Syringaldehyde 529894 -6.519 vanillin - - Albendazole 83969 -5.586 Levamisole 26879 -6.267 Mebendazole 4030 -5.285 Contrariwise standard drug albendazole, levamisole and mebendazole attained -5.586 kcal/mol, -6.267 kcal/mol and -5.285 kcal/mol against same receptor protein. The top five compounds according to docking score against this receptor was as follows: syringaldehyde (>albendazole, levamisole, mebendazole) > p-hydroxybenzaldehyde (>albendazole, aebendazole) > benzaldehyde (>mebendazole) > phenol (Almost nearest to mebendazole) > ethyl acetate (almost nearest to mebendazole). From alluded above categorized classification order of docking score, A number of hydrogen and hydrophobic bonds were identified between the ligand and active site residue of the tubulin-colchichine enzyme (1SA0). The details binding mode of those complexes demonstrated in Figure 1. 3.3 Prime MM-GBSA analysis The compound syringaldehyde, p-hydroxybenzaldehyde, benzaldehyde, phenol, and ethyl acetate all had worthy binding scores of < -5.00 kcal/mol towards tubulin-colchichine enzyme receptor (1SA0) is further subjected to estimate binding free energies (∆G bind ) of the concerned receptor-ligand complexes through applying molecular mechanics-generalized born surface area (MM-GBSA) method in order to evaluate their binding capacity with respective proteins. It has been formulated that MM-GBSA delivers precise measurements of binding free energies of protein-ligand complexes, with a lower value indicating greater binding (Aamir et al. 2018). Beside this, those compounds were assessed for their coulomb interaction energies, van der waals interaction energies, lipophilic energy of the complex, solvation energy of the complex, and ligand strain energy. According to the ∆G bind MMGBSA scores of Syringaldehyde with the tubulin-colchichine enzyme receptor, this compound had a greater binding potential with the selected tubulin-colchichine enzyme proteins followed by ethyl acetate (-29.334 kcal/mol), benzaldehyde (-25.283 kcal/mol), p-hydroxybenzaldehyde (-24.585 kcal/mol), and phenol (-18.056 kcal/mol) as evidenced by the ∆G bind MMGBSA scores of syringaldehyde (-35.639 kcal/mol) with the tubulin-colchichine proteins (Table 3) . Table 3: Prime MM-GBSA calculation of the top five docked complexes. Protein Compound Docking Score ∆G bind (kcal/mol) ∆G coul ∆G vdw ∆G lipo Solv GB Ligand Strain Energy Interacting Residues 1SA0 Syringaldehyde -6.519 -35.63 -16.835 -24.98 -15.34 18.502 1.884 VAL 238, CYS 241, LEU 248, ALA 316, ALA 317, ALA 354 Ethyl Acetate -5.011 -29.33 -6.935 -13.99 -16.1 7.795 0.705 TYR 202, VAL 238, CYS 241, LEU 242, LEU 255 Benzaldehyde -5.432 -25.28 -3.06 -20.25 -8.722 8.687 0.308 VAL 315, LYS 352 p-hydroxybenzaldehyde -5.608 -24.58 -7.166 -18.21 -12.31 12.847 0.373 VAL 238, CYS 241, ALA 250, LEU 255 Phenol -5.233 -18.05 -4.439 -15.99 -9.613 13.649 0.209 MET 259, VAL 315, ALA 316, ASN 350, LYS 352 Therefore, that compound exhibited considerable amount of coulomb interaction energies (-16.835 kcal/mol), van der waals interaction energies (-24.980 kcal/mol), lipophilic energy of the complex (-15.340 kcal/mol), solvation energy of the complex (18.502 kcal/mol) than others with 1.884 kcal/mol of ligand strain energy which is per lower than standard penalty energy of 3 kcal/mol (Perola and Charifson 2004). As a result, for Molecular Dynamics Simulation, we considered Syringaldehyde-1SA0 complex for furthermore validation. 3.4 Molecular dynamics simulation In MD simulation, the complex had an average RMSD and RMSF of 2.008Å and 1.324Å, respectively (Figures 2-4) , which shows the stability of the complex even after the stimulation period. The complex exhibited one backbone hydrogen bond with Ala317 (Figure 5) and ten hydrophobic interactions (Ala316, Ala354, Val318, Val238, Ile378, Leu242, Cys241, Leu255, Leu248, and Ala250). 4. DISCUSSION The widespread exposition of Trichuris, Ascaris , and hookworms in third-world nations is making helminthiasis one of the biggest health issues that includes iron deficiency-like sickness, malnutrition, rectal prolapse, diarrhea, gastrointestinal system, dysentery, and respiratory issues (Hossain et al. 2012 ). Because of the development of the parasitic gastroenteritis disease that causes paramphistomosis and the immune-suppressing effects of some parasites from the Platyhelminthes phylum and Paramhistomidae family, the morbidity and mortality rates are significantly increased. Patients may also become more susceptible to diseases like HIV, malaria, and tuberculosis (Brown 2005 ; Panyarachun et al. 2010 ). The fact that current anthelmintic drugs’ showing resistance to common nematodes have raised the necessity to discover new drug components to fight this issue (Kaminsky 2003 ; Kaplan and Vidyashankar 2012 ; Prichard 2007 ). To counteract the fact, different plant’s anthelmintic activity inspired our search for a novel natural compound that can effectively bind and inhibit the activity of nematodes by synchronizing their historical effectiveness against helminths from antiquity (Eguale and Giday 2009 ; Ibrahim 1992 ; Mamidou Koné et al. 2012 ; Manoj A, Urmila A, Bhagyashri W, Meenakshi V, Akshaya W and NG 2008). Many studies up to now had reported the key role of colchicine binding domain of tubulin complex which led us to run our computational experiments targeting this protein in order to inhibit it’s activity (Köhler 2001 ; Ranjan et al. 2018 ; Ranjan et al. 2017 ). All the compounds screened through literature review had been found pharmacokinetically fit to be used as drug in human while assessed by SwissADME (Daina et al. 2017 ). Each compound under consideration also complies to the acceptable range of the parameters that determine the drug likeness of natural products (Bade et al. 2010 ; Lipinski 2004 ; Tian et al. 2015 ). To demonstrate the pharmaceutical credibility, a drug administered orally should first comply with the Lipinski principle. The rule describes molecular properties important for drug pharmacokinetics in the human body, including its absorption, distribution, metabolism and excretion (ADME). Molecule weight of all the selected compound fall under the acceptable range of < 500 g/mol indicating easy mobility of the drug component throughout the body. Although some compounds violated the acceptable range of refractivity index, they could also be considered for further analysis as single violation of Lipinski’s rule is acceptable; more than that would question their bioavailability (Daisy et al. 2011 ; Hou et al. 2007 ). In the following step, molecular docking was performed to model the atomic interaction between the screened ligands and our target enzyme tubulin-colchicine (PDB ID: 1SA0). The Standard Precision (SP) scoring method of Glide was using for molecular docking assay that was embedded into Schrödinger suite-Maestro version 11.2 (Friesner et al. 2006 ; Friesner et al. 2004 ). This process allowed us to elucidate the binding behavior of our small ligands in the active site of target enzyme (McConkey et al. 2002 ). Following the docking process syringaldehyde complex divulged signatory binding affinities over the standard drugs albendazole, levamisole and mebendazole complex binding score in contrast to other compounds p-hydroxybenzaldehyde, benzaldehyde, phenol and ethyl acetate complex. Syringaldehyde binding pattern may hinder the substrate accessibility as it was found to bind extensively with the tubulin-colchicine enzyme. The binding involves pocket constructed by a number of network interactions such as three hydrogen bond interaction of Val 238, Cys 241 and Ala 317; four hydrophobic interactions of Leu 248, Cys 241, Ala 316, and Ala 354 with attaining the prominent binding affinity of -6.519 kcal / mol. These binding properties shows even higher binding affinity than all three standard drugs. Whereas p-hydroxybenzaldehyde, benzaldehyde, ethyl acetate and phenols upon docking with the target protein 1SA0 disclosed comparative lower energy of hydrogen bond and hydrophobic like convenient associations (Table 3 ). Importantly this syringaldehyde is a intricate polyphenolics meanwhile literature statements about phenolic substances that could be the reason why plants have anthelmintic effects since they are protein coagulants, which can affect intestinal worms in a variety of ways (Waterman et al. 2010 ). As predicted by the docking tool, various interaction like hydrogen bonding, van-dar-waal and electrostatic interactions played vital role in the determination of binding free energy and stability of receptor-ligand complex. Thereafter, MM-GBSA process employed for the estimation of precise binding free energies of concerning ligand-receptor complex. Whereas in aligned with larger negative value implies better binding efficacy, Syringaldehyde-1SA0 complex attained lower binding energy of -35.639 kcal/mol relative to ethyl acetate, benzaldehyde, p-hydroxybenzaldehyd, and phenol complex (Table 3 ). Meanwhile, this syringaldehyde molecule, which had a higher docking score and ∆G bind MM-GBSA scores with 1SA0 proteins than other phytochemicals, was chosen for a Molecular Dynamics Simulation investigation. MD simulation is a latest computational approach used to analyze and predict the dynamic nature of ligand-receptor complex as a function of time or residue position (Chan 1999 ; Haile et al. 1993 ; Hollingsworth and Dror 2018 ). It has added a whole new dimension in the field of drug discovery by analyzing the dynamic nature of drug-receptor complex in host by simulating the force field as per requirement (Borhani and Shaw 2012 ; Durrant and McCammon 2011 ; Liu et al. 2018 ; De Vivo et al. 2016 ). In this study, structural parameters such as- RMSD and RMSF were used to evaluate the stability and dynamic behavior of protein-drug complex. The complex between syringaldehyde and tubulin-colchicine showed quite promising RMSD value of 2.008 Å, which stayed stable over the whole simulation session. This indicates the stability of the complex in the biological system. On the other hand, despite having a lower mean RMSF value of 1.324Å, Leu216, Lys217, Leu218 showed higher mobility indicated by their larger RMSF value of 4.9, 4.8, and 5.1 Å respectively. Hence their impact on the final integrity on the protein-drug complex needs to be confirmed using Dictionary of Secondary Structure of Proteins (DSSP) algorithm. But as observed from the interaction of drug with the target site residues, most of the hydrophobic interaction (Ala317, Leu248, Leu255, Ala316, Ala354, Ala250, Cys241, Ile378 and Val318) and the backbone hydrogen bond with Ala317 remained unchanged even after the 10ns simulation. A similar interaction was observed for tubulin residue with different inhibitors; for instance, in one study(Hamed et al. 2021 ; Sun et al. 2019 ) compound, PMMB-317 interaction with tubulin also showed residue Ala316, Val318, and Leu255 near to the binding pocket. Furthermore, another study(Elmaaty et al. 2021 ; Mukunthan et al. 2017 ) showed hydrogen bonding between compound 7 and Ala250 of tubulin as well as non-hydrogen bonding interaction with residue Ala316 highlighting the importance of this residue in the design of potential inhibitor. These data strongly suggest the high binding affinity of the drug with the target protein and their stability in the biological system. 5. CONCLUSION This is the first report describing an in silico correlation between the predicted pharmacological activities of A. comosus as per our knowledge. All the in-silico analysis including molecular docking and molecular dynamics simulation concludes that syringaldehyde can be the next promising anthelmintic drug. However, further studies remain necessary to elucidate the underlying mechanism. Thus, this study can offer some precursory evidence for the ethnomedical uses of A. comosus and it reveals that this plant does contain some active agent that may be responsible for anthelmintic activity. Declarations Conflicts of interest None. Source of funding None. Ethical approval This case report has been reported in line with the Case Report (CARE) guidelines. Research registration number (UIN) Not applicable. Trial registry number Not applicable. Author contribution Conceptualization, methodology, formal analysis, original draft preparation- A.P, M.M.K; software, investigation, data curation- T.D, M.H.U.C, M.M; manuscript review and editing- T.B.E; supervision, project administration- M.M.K Statements and Declarations We have read and understood the policy on declaration of interests and have no relevant interests to declare. 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Anthelmintic activity of medicinal plants used in Côte d’Ivoire for treating parasitic diseases. Springer. 2012 Jun;110(6):2351–62. Manoj A, Urmila A, Bhagyashri W, Meenakshi V, Akshaya W K, NG. Anthelmintic activity of Ficus bengalensis. Int. J. Green Pharm. 2008;2(3):170–2. Marlesa RJ, Farnsworthb NR. Antidiabetic plants and their active constituents 1. Phytomedicine. Gustav Fischer Verlag, Struttgart · Jena · New York; 1995;2(2):137–89. McConkey BJ, Sobolev V, Edelman M. The performance of current methods in ligand-protein docking. Curr Sci. 2002. Mukunthan KS, Satyan RS, Patel TN. Pharmacological evaluation of phytochemicals from South Indian Black Turmeric (Curcuma caesia Roxb.) to target cancer apoptosis. J Ethnopharmacol. Elsevier Ireland Ltd; 2017;209:82–90. Nayak A, Gayen P, Saini P, Mukherjee N, Sinha Babu SP. Molecular evidence of curcumin-induced apoptosis in the filarial worm Setaria cervi. Parasitol Res. Parasitol Res; 2012 Sep;111(3):1173–86. Nor A, Ramli M, Hasmaliana N, Manas A, Azzar A, Hamid A, et al. Comparative structural analysis of fruit and stem bromelain from Ananas comosus. Food Chem. Elsevier; 2018;266(January):183–91. Pai R V., Monpara JD, Vavia PR. Exploring molecular dynamics simulation to predict binding with ocular mucin: An in silico approach for screening mucoadhesive materials for ocular retentive delivery systems. Journal of Controlled Release. Elsevier B.V; 2019;309:190–202. Panyarachun B, Sobhon P, Tinikul Y, Chotwiwatthanakun C, Anupunpisit V, Anuracpreeda P. Paramphistomum cervi: surface topography of the tegument of adult fluke. Exp Parasitol. Elsevier; 2010;125(2):95–9. Perola E, Charifson PS. Conformational Analysis of Drug-Like Molecules Bound to Proteins: An Extensive Study of Ligand Reorganization upon Binding. J Med Chem. American Chemical Society ; 2004 May 6;47(10):2499–510. Prichard RK. Markers for benzimidazole resistance in human parasitic nematodes. Parasitology. 2007;134(8):1087–92. Raimundo C, Cláudia A, Barbosa DO, Fortes C, Vidigal F, Souza D, et al. Scientia Horticulturae Diversity of microorganisms associated to Ananas spp . from natural environment , cultivated and ex situ conservation areas. Sci Hortic. Elsevier; 2019;243(March 2018):544–51. Ranjan P, Athar M, Vijayakrishna K, Meena LK, Vasita R, Jha PC. Deciphering the anthelmintic activity of benzimidazolium salts by experimental and in-silico studies. J Mol Liq. Elsevier B.V; 2018. Ranjan P, Kumar SP, Kari V, Jha PC. Exploration of interaction zones of β-tubulin colchicine binding domain of helminths and binding mechanism of anthelmintics. Comput Biol Chem. Elsevier Ltd; 2017 Jun;68:78–91. Rates SMK. Plants as source of drugs. Toxicon. Elsevier; 2001;39(5):603–13. Ravelli RBG, Gigant B, Curmi PA, Jourdain I, Lachkar S, Sobel A, et al. Insight into tubulin regulation from a complex with colchicine and a stathmin-like domain. Nature. 2004 Mar 11;428(6979):198–202. Ru Q, Fadda HM, Li C, Paul D, Khaw PT, Brocchini S, et al. Molecular dynamic simulations of ocular tablet dissolution. J Chem Inf Model. J Chem Inf Model; 2013 Nov 25;53(11):3000–8. Shao Q, Zhu W. Assessing AMBER force fields for protein folding in an implicit solvent. Physical Chemistry Chemical Physics. Royal Society of Chemistry; 2018;20(10):7206–16. Soureshjani EH, Babaheydari AK, Saberi E. DNA Methyltransferases Directed Anti-Cancerous Plant Medicine (Xanthomicrol and Galloyl) Based Molecular Docking and Dynamics Simulation. Comput Mol Biosci. 2015;05(02):13–9. Sun WX, Han HW, Yang MK, Wen ZL, Wang YS, Fu JY, et al. Design, synthesis and biological evaluation of benzoylacrylic acid shikonin ester derivatives as irreversible dual inhibitors of tubulin and EGFR. Bioorg Med Chem. Elsevier Ltd; 2019. Tian S, Wang J, Li Y, Li D, Xu L, Hou T. The application of in silico drug-likeness predictions in pharmaceutical research. Adv Drug Deliv Rev. Elsevier; 2015. p. 2–10. Ullah R, Rehman A, Zafeer MF, Rehman L, Khan YA, Khan MAH, et al. Anthelmintic Potential of Thymoquinone and Curcumin on Fasciola gigantic. PLoS One. 2017;12(2):1–19. Vijayakumar B, Parasuraman S, Raveendran R, Velmurugan D. Identification of natural inhibitors against angiotensin i converting enzyme for cardiac safety using induced fit docking and MM-GBSA studies. Pharmacogn Mag. Medknow Publications; 2014 Jul 1;10(39):S639–44. De Vivo M, Masetti M, Bottegoni G, Cavalli A. Role of Molecular Dynamics and Related Methods in Drug Discovery. J Med Chem. American Chemical Society; 2016. p. 4035–61. van Vuuren SF, Viljoen AM, van Zyl RL, van Heerden FR, Başer KHC. The antimicrobial, antimalarial and toxicity profiles of helihumulone, leaf essential oil and extracts of Helichrysum cymosum (L.) D. Don subsp. cymosum. South African Journal of Botany. Elsevier; 2006 May 1;72(2):287–90. Waterman C, Smith RA, Pontiggia L, DerMarderosian A. Anthelmintic screening of Sub-Saharan African plants used in traditional medicine. J Ethnopharmacol. Elsevier; 2010 Feb 17;127(3):755–9. Zajíčková M, Nguyen LT, Skálová L, Raisová Stuchlíková L, Matoušková P. Anthelmintics in the future: current trends in the discovery and development of new drugs against gastrointestinal nematodes. Drug Discov Today. Elsevier Ltd; 2020;25(2):430–7. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3859053","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267151950,"identity":"cac8562f-5e0d-4932-b134-1bb60a5c356c","order_by":0,"name":"Arkajyoti Paul","email":"","orcid":"","institution":"Jagannath University","correspondingAuthor":false,"prefix":"","firstName":"Arkajyoti","middleName":"","lastName":"Paul","suffix":""},{"id":267151951,"identity":"23845c6f-7244-4e3c-9fad-45476b23479b","order_by":1,"name":"Tuhin Das","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFACHoYDQDKBjYEZREvIEKEBroUtAaSFhygtIABUzmMAESAE7CVyDx4uYNiWx8fe8/nVjRoLHgb2w0c34LVFIi/h8AyG28VsPGe3WeccAzqMJy3tBn4tOQaHeRhuJ7ZJ5G4zzmEDapHgMSNWS84z45x/JGphfpzbRoyWM2+AWgxAfjlmxpzbJ8HDRsgv7O05xp95Km7nybc3P/6c861Ojp/98DG8WiAAHCMMbBJgkrByBGD+QIrqUTAKRsEoGDkAAH/7QVz1qXnaAAAAAElFTkSuQmCC","orcid":"","institution":"University of Chittagong","correspondingAuthor":true,"prefix":"","firstName":"Tuhin","middleName":"","lastName":"Das","suffix":""},{"id":267151952,"identity":"ae820d3a-8c71-4e21-b819-814a4ce04985","order_by":2,"name":"Md. Helal Uddin Chowdhury","email":"","orcid":"","institution":"University of Chittagong","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Helal Uddin","lastName":"Chowdhury","suffix":""},{"id":267151953,"identity":"57034d17-45da-4bea-b168-b947fe202691","order_by":3,"name":"Mohuya Majumder","email":"","orcid":"","institution":"East West University","correspondingAuthor":false,"prefix":"","firstName":"Mohuya","middleName":"","lastName":"Majumder","suffix":""},{"id":267151954,"identity":"b506e212-eaab-4902-849a-e0291639aa90","order_by":4,"name":"Md. Murad Khan","email":"","orcid":"","institution":"Jagannath University","correspondingAuthor":false,"prefix":"","firstName":"Md.","middleName":"Murad","lastName":"Khan","suffix":""},{"id":267151955,"identity":"3c1abc8c-b469-4214-a058-b8277ac78ef0","order_by":5,"name":"Talha Bin Emran","email":"","orcid":"","institution":"BGC Trust University Bangladesh","correspondingAuthor":false,"prefix":"","firstName":"Talha","middleName":"Bin","lastName":"Emran","suffix":""}],"badges":[],"createdAt":"2024-01-13 04:59:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3859053/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3859053/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49661204,"identity":"4169a3bb-e508-4fca-8dc7-4d33457736be","added_by":"auto","created_at":"2024-01-16 05:31:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":906677,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular docking interaction of (A) Syringaldehyde-1SA0, (B) p-hydroxybenzaldehyde-1SA0, (C) Benzaldehyde-1SA0, (D) phenol-1SA0, (E) ethyl acetate-1SA0\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/7173200549e70ec8ceb8455f.png"},{"id":49661202,"identity":"18a22892-1dad-4cf2-8d67-2b9cf7f6e10c","added_by":"auto","created_at":"2024-01-16 05:31:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":30100,"visible":true,"origin":"","legend":"\u003cp\u003eRMSD of backbone versus time in picoseconds. It can be seen very little fluctuation and the value of RMSD below 2.5 Å throughout the simulation, providing evidence of the stability of the protein-ligand complex.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/334a38488a810fe530c3bf46.png"},{"id":49661335,"identity":"a2a315fd-3a6d-40dc-85d1-155e52cb13db","added_by":"auto","created_at":"2024-01-16 05:39:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38510,"visible":true,"origin":"","legend":"\u003cp\u003eRMSF distance in angstrom values of the complex of syringaldehyde with tubulin beta chain. The peak RMSF observed values were 4.9, 4.8, and 5.1 Å for the residues Leu216, Lys217, Leu218.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/1a25929a375de0dd10612ded.png"},{"id":49661206,"identity":"4b042690-be38-4a2c-897b-6f963aa25dd5","added_by":"auto","created_at":"2024-01-16 05:31:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":119832,"visible":true,"origin":"","legend":"\u003cp\u003eThe interaction of syringaldehyde tubulin beta chain after docking.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/0333aee726544d0d1ad550a1.png"},{"id":49661203,"identity":"5e413337-c638-4e33-b9a2-e046653fb9b9","added_by":"auto","created_at":"2024-01-16 05:31:58","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110003,"visible":true,"origin":"","legend":"\u003cp\u003eThe interaction of the syringaldehyde tubulin beta chain after 10ns MD simulation. The backbone hydrogen bond with Ala317 still remains stable after the simulation.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/f3e71fca88a9e2ba8d5ffec2.png"},{"id":50269707,"identity":"adfb379e-2a34-4846-930d-03e52a0e1a6d","added_by":"auto","created_at":"2024-01-28 15:44:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1514637,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3859053/v1/9a5a7bdb-d4f3-4003-9252-cd95233d0a1b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anthelmintic Activity of Pineapple: In Silico Molecular docking and Molecular Dynamics Simulation","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eDiseases due to parasitic nematodes (also referred to as roundworms) have been associated with a wide variety of clinical complications in both animal and human perdurable and long-term morbidity. Helminthic infections (Tape worms, hook worms, round worms) are also acquainted as Neglected Tropical Diseases (NTDs) that mostly invaded in less developed countries owing to their faulty sanitation scheme and unavailability of cognitive knowledge (Ranjan et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Of those, infection in the gastrointestinal tract (GIT) and lungs are the most frequent and the most hazardous for humans and animals (Zaj\u0026iacute;čkov\u0026aacute; et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHelminths differ a lot from many other parasites; these organisms multiply within the definitive host. For survival, they develop anthelmintic resistance in turn through distinctive biochemical and gene expression processes. Although their potential to evade host immune defenses is not completely comprehended yet (Jayaraj et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to these nematode\u0026rsquo;s artful evasion of host immune response, fact that is more alarming is their resistance to conventionally prescribed drugs. Conventional synthetic drugs such as mebendazole, pyrantel, oxamniquine, praziquantel, tetrahydropyrimidines have been reported to less responsive due to their poor bioavailability and extensive application (Ullah et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This reduced activity can be attributed to the helminths\u0026rsquo; evolutionary heritable changes or these compounds\u0026rsquo; lack of ability to perform on a populace of parasites. Plant can play an important role in this context; about 25% of the conventional drugs consist of plant-derived compounds (Rates \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2001\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinding new drug compound has become lot easier with the advent of computational drug screening tools that involves molecular docking, molecular dynamics simulation and many other molecular attributes. This modern technique is further associated with adequate morphological and chemical information on parasites and plant products which is also corroborated by numerous plant-derived essential oils\u0026rsquo; and metabolites\u0026rsquo; exhibiting anti-parasitic activity (Chy et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; David et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nayak et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; van Vuuren et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In this regard, molecular docking is a feasible computational tool for structural molecular biology and computer-aided drug design (CADD) which widely use to predict two molecule interactions (compound-target enzymes) in three-dimensional space (Soureshjani et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Furthermore, this drug-protein receptor complex subjected to molecular dynamics (MD) simulation to predict their interactions on the basis of molecular motions including vibration, bond stretching, angle bonding, and bond formation (Ru et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which actually a force-field based process and utilized in the CADD more thoroughly for the simulation of interacting drug-receptor proteins complex (Pai et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDue to the presence of various secondary metabolites, like- alkaloids and flavonoids, pineapple is able to exert inhibitory effect against many pathogens. Pineapple (\u003cem\u003eAnanas comosus\u003c/em\u003e (L.) Merr.) is herbaceous, perennial (monocotyledonous) of the liliopsidae family, cultivated at wide ranges of latitude 30˚N and 33˚58ˈS in northern and southern hemisphere respectively, that grows to 1\u0026ndash;2 m high and 1\u0026ndash;2 m wide (Mahomoodally et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Raimundo et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) In addition to ample supply of vitamins and minerals, pineapple has also been reported to have many physiologically crucial constituents such as alkaloids, phytate, oxalate, tannins, cardenolides, dienolides, cardiac glycosides, flavonoids, Sulphur containing esters, isoflavones, catechins, anthocyanins, and other phenolic compounds, and the fruit extract can act substrate for the production of ethanol, methane, citric acid, and antioxidant agents (Corzo et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Dabesor et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hossain and Rahman \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Marlesa and Farnsworthb \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Nor et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Studies have shown a wide variety of biological activities such as anti-inflammatory, anthelmintic, antioxidative, anti-browning, anti-diarrhea, digestive aid, and injury healer, with some of this mode of action contributed by the bromelain enzyme complex (Agyare et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bahmani et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Behnke et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gurib-fakim \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis research was intended to evaluate the anthelmintic activity of various compounds identified in Pineapple as well as identify the molecular interactions existing between various phytoconstituents with the target receptors involved in anthelmintic activity of host.\u003c/p\u003e"},{"header":"2. MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Phytochemical mining\u003c/h2\u003e \u003cp\u003eA wide range of phytochemicals; 35 compounds(Adedeji et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1991\u003c/span\u003e) to be exact present in \u003cem\u003eA. comosus\u003c/em\u003e were obtained from various literature that reported to isolate from or identify them in the plant extract. The SMILE ID of those compounds were retrieved from PubChem (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to study their pharmacokinetic properties in the next step.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Determination of pharmacokinetic properties\u003c/h2\u003e \u003cp\u003eDrug-like properties or pharmacokinetics of compounds derived through literature review was evaluated by SwissADME (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swissadme.ch/\u003c/span\u003e\u003cspan address=\"http://www.swissadme.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), an online resource following Lipinski\u0026rsquo;s rule of five. According to that, any chemical constituent should act as a drug when it does not infringe upwards of one of the following criteria: (i) Molecular weight not exceeding 500; (ii) acceptors of H-bonds\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;10; (iii) donors of H-bonds\u0026thinsp;\u003cem\u003e\u0026le;\u003c/em\u003e\u0026thinsp;5; (iv) lipophilicity (LogP)\u0026thinsp;\u0026lt;\u0026thinsp;5; and (v) molar refractivity between 40 and 130. Lipinski\u0026rsquo;s rule of five evaluates drug likeness and determine whether a chemical compound when ingested can likely being active as drug in humans.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Ligand preparation\u003c/h2\u003e \u003cp\u003eThe key prolific and active substances contained in \u003cem\u003eA. comosus\u003c/em\u003e species (tracked out by literature review) have been subjected to rigorous molecular docking analysis to evaluate the anthelmintic activities. The concerned phytocompound\u0026rsquo;s configurations were obtained from NCBI PubChem database, a public molecular information repository. All such phytocompounds were ready through using subsystem LigPrep of the Schr\u0026ouml;dinger suite (LigPrep, version 42013, Schr\u0026ouml;dinger). The minimization process was done by using OPLS3 force field. All feasible ionic states were formed with target pH of 7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2 using Epik 2.2. For each ligand plausible stereo isomers of lesser energy ring conformations were also devised, one per ligand.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Receptor preparation\u003c/h2\u003e \u003cp\u003eTubulin-colchicine enzyme (PDB: 1SA0) (Ravelli et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) was elected as a target receptor protein and downloaded in Maetsro v11.2 from RCSB Protein Data Bank (Berman et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The structures were also formulated employing protein preparation wizard of the Schr\u0026ouml;dinger. At first, concerning receptor had been pre-processed by assigning bond orders, adding hydrogen, filling empty side chains and loops with PRIME and eventually removing all water in the crystal structures. After optimization of these crystal structures, restrain minimization with root mean square deviation (RMSD) 0.3 \u0026Aring; was carried out applying OPLS3 force field.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Grid generation and molecular docking\u003c/h2\u003e \u003cp\u003eUsing the \"Receptor Grid Generation\" panel, the minimized protein structures were then used for grid generation. For each protein, a grid implementing the consequent default parameters was set up- Van Der Waals scaling factor 1.00 and charging cut-off value 0.25, according to the force field of OPLS3. A cubic receptor grid box was centroid with a 14 \u0026Aring; \u003cem\u003e\u0026times;\u003c/em\u003e 14 \u0026Aring; \u003cem\u003e\u0026times;\u003c/em\u003e 14 \u0026Aring; size from the center of the selected co-crystallized ligand. The Standard Precision (SP) scoring method of Glide was using for molecular docking assay that was embedded into Schr\u0026ouml;dinger suite-Maestro version 11.2 (Friesner et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Friesner et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Prime MM-GBSA (molecular mechanics-generalized born surface area) calculation\u003c/h2\u003e \u003cp\u003eAs a post docking validation tool, Molecular mechanics-generalized Born surface area (MMGBSA) method was utilized by exerting default parameters of Prime MM-GBSA modules embedded in Schrodinger software to calculate the free energies of binding (Jacobson et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Vijayakumar et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For calculation purposes Prime MM-GBSA employs optimized potential for liquid simulations (OPLS) force field in conjunction with molecular mechanics energies (EMM), a model for polar solvation based on the VSGB (GSGB), and a solvation term that isn't polar (GNP) (Kar et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Each protein-ligand complex's absolute free energy of binding was calculated as follows:\u003c/p\u003e \u003cp\u003e∆G\u003csub\u003ebind\u003c/sub\u003e = ∆G\u003csub\u003ecomplex\u003c/sub\u003e \u0026ndash; (∆G\u003csub\u003eprotein\u003c/sub\u003e + ∆G\u003csub\u003eligand\u003c/sub\u003e)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Molecular dynamics simulation\u003c/h2\u003e \u003cp\u003eSimulation of molecular dynamics was conducted to check the structural stability of the best docking scored protein-ligand complex over water molecules and ions. The simulation was performed with YASARA Dynamics v.19.9.17 (Krieger and Vriend \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) using the default Amber14 (Shao and Zhu \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) force field, and trajectories have been analyzed over 10 ns duration. The specific MD simulation model has been obtained from the syringaldehyde docked complex with receptor tubulin beta chain (PDB code: 1SA0, chain B). The complex was kept in cell length (X\u0026thinsp;=\u0026thinsp;88.9, Y\u0026thinsp;=\u0026thinsp;88.9, Z\u0026thinsp;=\u0026thinsp;88.9) along with the TIP3 cubic simulation water box with periodic boundary condition and PME (Darden et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1993a\u003c/span\u003e) algorithm to assign a charge. At pH 7.4 and 298 K, the water density was set to 0.997 g/cmᶾ, and sodium and chloride ions are included (NaCl 0.9%) to neutralize the charge of the system. The system had undergone energy minimization, and simulated annealing refinement and charge to amino acid were assigned using Particle Mesh Ewald algorithm (Darden et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1993b\u003c/span\u003e) with cutoff radius 8 \u0026Aring;. The production of MD simulation was subsequently performed for 10 ns time scale using step size of 2.5 fs separately for each complex system and snapshot have been recorded at 100 picoseconds up to 10ns which have been used in the analysis, as done in (John R.Giudicessi, BA.Michael J.Ackerman. 2008) to determine receptor interaction with ligands, root mean square deviation (RMSD) and root mean square fluctuation (RMSF).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULT","content":"\u003cp\u003e\u003cstrong\u003e3.1 Pharmacokinetic properties\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePharmacokinetic properties of 34 chemical compounds screened through literature survey was determined using Swiss ADME tool, out of which all of them were found to be pharmacologically pertinent. Following the Lipinski\u0026rsquo;s rule of five, we did find all of the selected molecules passed through this step of screening as no single compound violated more than one rule \u003cstrong\u003e(Table 1)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eADME/T properties of the isolated compounds of Ananas comosus by SwissADME.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"622\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e\u003cstrong\u003eName of molecules\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e\u003cstrong\u003ePubchem ID\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e\u003cstrong\u003eMolecular weight\u003csup\u003e1\u003c/sup\u003e (g/mol)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\u003cstrong\u003eHydrogen bond acceptor\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\u003cstrong\u003eHydrogen bond donor\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e\u003cstrong\u003eLog P\u003csup\u003e4\u003c/sup\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e\u003cstrong\u003eMolar refractivity\u003csup\u003e5\u003c/sup\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e2-butoxyethanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e8133\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e118.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.02\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e33.30\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e2-Pentanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e22386\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e88.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e27.31\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e2-Pentanone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7895\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e201.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.96\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e59.08\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e2-phenylethanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e6054\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e122.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.64\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e37.38\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e3-Hydroxyphenethyl alcohol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e83404\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e138.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e39.40\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e3-methylbutanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e31260\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e88.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e27.31\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e4-Allyl-2,6 dimethoxyphenol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e226486\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e194.23\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.29\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e55.55\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eAcetic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e176\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e60.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e-0.09\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e13.50\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eBenzaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e240\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e106.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e31.83\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eDelta-Hexalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e13204\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e114.14\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e30.13\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eDelta-Octanolactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e12777\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e142.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e39.74\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eDimethyl malonate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7943\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e132.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e0.18\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e28.72\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eEthyl 4-acetoxyhexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e529297\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e202.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e52.75\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eEthyl 4-acetoxyoctanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e529298\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e230.30\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e62.37\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eEthyl acetate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e8857\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e88.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e0.75\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e22.63\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eEthyl hexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e31265\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e144.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e41.85\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eEthyl propenoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e8821\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e100.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.07\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e26.96\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eGamma -valerolactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7921\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e100.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e0.91\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e25.32\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eGamma-Decalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e12813\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e170.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.61\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e49.35\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eGamma-Hexalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e12756\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e114.14\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.19\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e30.13\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eGamma-nonalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7710\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e156.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e44.55\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eGamma-octalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7704\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e142.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.88\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e39.74\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eHexanal\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e6184\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e100.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.66\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e31.16\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eHexanoic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e8892\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e116.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.47\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e32.73\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eMethyl 4-methylpentanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e17008\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e130.18\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.79\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e37.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eMethyl 5-acetoxyhexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e526152\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e188.22\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.53\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e47.95\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eMethyl butanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e12180\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e102.13\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e27.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eMethyl octanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e8091\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e158.24\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e2.70\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e46.66\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eMethyl pentanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e12206\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e116.16\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.57\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e32.24\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003e4- hydroxybenzaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e126\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e122.12\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e33.85\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003ePhenol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e996\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e94.11\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.41\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e28.46\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003ePropyl acetate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e7997\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e102.13\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.14\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e27.43\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eSyringaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e529894\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e182.17\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e0.93\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e46.84\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.484751203852326%\"\u003eVanillin\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.359550561797754%\"\u003e1183\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.162118780096309%\"\u003e152.15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.951845906902086%\"\u003e1.20\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.92776886035313%\"\u003e40.34\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"7\"\u003eNotes: \u003csup\u003e1\u003c/sup\u003eMolecular weight (acceptable range: \u0026lt;500); \u003csup\u003e2\u003c/sup\u003eHydrogen bond donor (acceptable range: \u0026le;5); \u003csup\u003e3\u003c/sup\u003eHydrogen bond acceptor (acceptable range: \u0026le;10); \u003csup\u003e4\u003c/sup\u003eHigh lipophilicity (expressed as LogP, acceptable range: \u0026lt;5);\u0026nbsp;\u003csup\u003e5\u003c/sup\u003eMolar refractivity should be between 40 and 130.\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Molecular docking analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere in investigation of anthelmintic activity, the 34 molecules stated above docked for anthelmintic action against crystalline structure of the tubulin-colchicine enzyme (PDB: 1SA0). In reference to tubulin-colchicine receptor enzyme; syringaldehyde and ethyl 4-acetoxyoctanoate generated a great and poor binding affinity score in the range of -6.519 kcal / mol to -0.363 kcal/mol than any other compound (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eDocking results of selected compounds from Ananas comosus with 1SA0.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"588\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003eCompound Name\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e\u003cstrong\u003eCompound ID\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003eDocking Score\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e2-butoxyethanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e8133\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-1.127\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e2-pentanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e22386\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.991\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e2-pentanone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7895\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.847\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e2-phenylethanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e6054\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.535\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e3-Hydroxyphenethyl alcohol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e83404\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.922\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e3-methylbutanol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e31260\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.968\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e4-Allyl-2,6-dimethoxyphenol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e226486\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eAcetate acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e176\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.453\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003eBenzaldehyde\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e240\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003e-5.432\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eDelta-Hexalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e13204\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.754\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eDelta-Octanolactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e12777\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.184\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eDimethyl malonate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7943\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.01\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eEthyl 4-acetoxyhexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e529297\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.638\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eEthyl 4-acetoxyoctanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e529298\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-0.363\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003eEthyl acetate\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e8857\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003e-5.011\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eEthyl hexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e31265\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-1.82\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eEthyl propenoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e8821\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.403\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eGamma -valerolactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7921\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.872\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eGamma-Decalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e12813\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.444\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eGamma-Hexalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e12756\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-4.186\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eGamma-nonalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7710\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.487\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eGamma-octalactone\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7704\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.995\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eHexanal\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e6184\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.28\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eHexanoic acid\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e8892\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.271\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMethyl 4-methylpentanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e4275592\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.652\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMethyl 5-acetoxyhexanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e526152\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.442\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMethyl butanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e12180\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.412\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMethyl octanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e8091\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-1.36\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMethyl pentanoate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e12206\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-2.494\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003ep- hydroxybenzaldehyde\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e126\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003e-5.608\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003ePhenol\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e996\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003e-5.233\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003ePropyl acetate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e7997\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-3.715\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003e\u003cstrong\u003eSyringaldehyde\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e529894\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e\u003cstrong\u003e-6.519\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003evanillin\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e-\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eAlbendazole\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e83969\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-5.586\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eLevamisole\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e26879\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-6.267\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.666666666666664%\"\u003eMebendazole\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.06122448979592%\"\u003e4030\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.272108843537413%\"\u003e-5.285\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eContrariwise standard drug albendazole, levamisole and mebendazole attained -5.586 kcal/mol, -6.267 kcal/mol and -5.285 kcal/mol against same receptor protein. The top five compounds according to docking score against this receptor was as follows: syringaldehyde (\u0026gt;albendazole, levamisole, mebendazole) \u0026gt; p-hydroxybenzaldehyde (\u0026gt;albendazole, aebendazole) \u0026gt; benzaldehyde (\u0026gt;mebendazole) \u0026gt; phenol (Almost nearest to mebendazole) \u0026gt; ethyl acetate (almost nearest to mebendazole). From alluded above categorized classification order of docking score, A number of hydrogen and hydrophobic bonds were identified between the ligand and active site residue of the tubulin-colchichine enzyme (1SA0). The details binding mode of those complexes demonstrated in Figure 1.\u003c/p\u003e\n\u003cp\u003e3.3 Prime MM-GBSA analysis\u003c/p\u003e\n\u003cp\u003eThe compound syringaldehyde,\u0026nbsp;p-hydroxybenzaldehyde, benzaldehyde, phenol,\u0026nbsp;and ethyl acetate all had worthy binding scores of \u0026lt;\u0026nbsp;-5.00 kcal/mol towards tubulin-colchichine enzyme receptor (1SA0) is further subjected to estimate binding free energies\u0026nbsp;(∆G\u003csub\u003ebind\u003c/sub\u003e)\u0026nbsp;of the concerned receptor-ligand complexes through applying molecular mechanics-generalized born surface area (MM-GBSA) method in order to evaluate their binding capacity with respective proteins. It has been formulated that MM-GBSA delivers precise measurements of binding free energies of protein-ligand complexes, with a lower value indicating greater binding (Aamir et al. 2018). Beside this, those compounds were assessed for their coulomb interaction energies, van der waals interaction energies, lipophilic energy of the complex, solvation energy of the complex, and ligand strain energy. According to the\u0026nbsp;∆G\u003csub\u003ebind\u003c/sub\u003e MMGBSA scores of Syringaldehyde with the tubulin-colchichine enzyme receptor, this compound had a greater binding potential with the selected tubulin-colchichine enzyme proteins followed by ethyl acetate (-29.334 kcal/mol), benzaldehyde (-25.283 kcal/mol), p-hydroxybenzaldehyde (-24.585 kcal/mol), and phenol (-18.056 kcal/mol) as evidenced by the ∆G\u003csub\u003ebind\u003c/sub\u003e MMGBSA scores of syringaldehyde (-35.639 kcal/mol) with the tubulin-colchichine proteins \u003cstrong\u003e(Table 3)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003ePrime MM-GBSA calculation of the top five docked complexes.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"642\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.21875%\" rowspan=\"2\"\u003e\u003cstrong\u003eProtein\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.78125%\" rowspan=\"2\"\u003e\u003cstrong\u003eCompound\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.6875%\" rowspan=\"2\"\u003e\u003cstrong\u003eDocking Score\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\" rowspan=\"2\"\u003e\u003cstrong\u003e∆G\u003csub\u003ebind\u003c/sub\u003e (kcal/mol)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.75%\" rowspan=\"2\"\u003e\u003cstrong\u003e∆G\u003csub\u003ecoul\u003c/sub\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\" rowspan=\"2\"\u003e\u003cstrong\u003e∆G\u003csub\u003evdw\u003c/sub\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\" rowspan=\"2\"\u003e\u003cstrong\u003e∆G\u003csub\u003elipo\u003c/sub\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\" rowspan=\"2\"\u003e\u003cstrong\u003eSolv GB\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.75%\" rowspan=\"2\"\u003e\u003cstrong\u003eLigand Strain Energy\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.8125%\" rowspan=\"2\"\u003e\u003cstrong\u003eInteracting Residues\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.125%\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.21875%\" rowspan=\"5\"\u003e1SA0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.78125%\"\u003eSyringaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.6875%\"\u003e-6.519\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\"\u003e-35.63\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.75%\"\u003e-16.835\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\"\u003e-24.98\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\"\u003e-15.34\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.96875%\"\u003e18.502\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.75%\"\u003e1.884\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.8125%\"\u003eVAL 238, CYS 241, LEU 248, ALA 316, ALA 317, ALA 354\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.876075731497417%\"\u003eEthyl Acetate\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.671256454388985%\"\u003e-5.011\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-29.33\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e-6.935\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-13.99\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-16.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e7.795\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e0.705\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.113597246127366%\"\u003eTYR 202, VAL 238, CYS 241, LEU 242, LEU 255\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.876075731497417%\"\u003eBenzaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.671256454388985%\"\u003e-5.432\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-25.28\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e-3.06\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-20.25\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-8.722\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e8.687\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e0.308\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.113597246127366%\"\u003eVAL 315, LYS 352\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.876075731497417%\"\u003ep-hydroxybenzaldehyde\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.671256454388985%\"\u003e-5.608\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-24.58\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e-7.166\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-18.21\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-12.31\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e12.847\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e0.373\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.113597246127366%\"\u003eVAL 238, CYS 241, ALA 250, LEU 255\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.876075731497417%\"\u003ePhenol\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"10.671256454388985%\"\u003e-5.233\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-18.05\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e-4.439\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-15.99\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e-9.613\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.777969018932874%\"\u003e13.649\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.63855421686747%\"\u003e0.209\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.113597246127366%\"\u003eMET 259, VAL 315, ALA 316, ASN 350, LYS 352\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTherefore, that compound exhibited considerable amount of coulomb interaction energies (-16.835 kcal/mol), van der waals interaction energies (-24.980 kcal/mol), lipophilic energy of the complex (-15.340 kcal/mol), solvation energy of the complex (18.502 kcal/mol) than others with 1.884 kcal/mol of ligand strain energy which is per lower than standard penalty energy of 3 kcal/mol (Perola and Charifson 2004). As a result, for Molecular Dynamics Simulation, we considered Syringaldehyde-1SA0 complex for furthermore validation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Molecular dynamics simulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn MD simulation, the complex had an average RMSD and RMSF of 2.008\u0026Aring; and 1.324\u0026Aring;, respectively \u003cstrong\u003e(Figures 2-4)\u003c/strong\u003e, which shows the stability of the complex even after the stimulation period.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe complex exhibited one backbone hydrogen bond with Ala317 \u003cstrong\u003e(Figure 5)\u003c/strong\u003e and ten hydrophobic interactions (Ala316, Ala354, Val318, Val238, Ile378, Leu242, Cys241, Leu255, Leu248, and Ala250).\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThe widespread exposition of \u003cem\u003eTrichuris, Ascaris\u003c/em\u003e, and hookworms in third-world nations is making helminthiasis one of the biggest health issues that includes iron deficiency-like sickness, malnutrition, rectal prolapse, diarrhea, gastrointestinal system, dysentery, and respiratory issues (Hossain et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Because of the development of the parasitic gastroenteritis disease that causes paramphistomosis and the immune-suppressing effects of some parasites from the Platyhelminthes phylum and Paramhistomidae family, the morbidity and mortality rates are significantly increased. Patients may also become more susceptible to diseases like HIV, malaria, and tuberculosis (Brown \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Panyarachun et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The fact that current anthelmintic drugs\u0026rsquo; showing resistance to common nematodes have raised the necessity to discover new drug components to fight this issue (Kaminsky \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Kaplan and Vidyashankar \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Prichard \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). To counteract the fact, different plant\u0026rsquo;s anthelmintic activity inspired our search for a novel natural compound that can effectively bind and inhibit the activity of nematodes by synchronizing their historical effectiveness against helminths from antiquity (Eguale and Giday \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ibrahim \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Mamidou Kon\u0026eacute; et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Manoj A, Urmila A, Bhagyashri W, Meenakshi V, Akshaya W and NG 2008). Many studies up to now had reported the key role of colchicine binding domain of tubulin complex which led us to run our computational experiments targeting this protein in order to inhibit it\u0026rsquo;s activity (K\u0026ouml;hler \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Ranjan et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ranjan et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll the compounds screened through literature review had been found pharmacokinetically fit to be used as drug in human while assessed by SwissADME (Daina et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Each compound under consideration also complies to the acceptable range of the parameters that determine the drug likeness of natural products (Bade et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lipinski \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Tian et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). To demonstrate the pharmaceutical credibility, a drug administered orally should first comply with the Lipinski principle. The rule describes molecular properties important for drug pharmacokinetics in the human body, including its absorption, distribution, metabolism and excretion (ADME). Molecule weight of all the selected compound fall under the acceptable range of \u0026lt;\u0026thinsp;500 g/mol indicating easy mobility of the drug component throughout the body. Although some compounds violated the acceptable range of refractivity index, they could also be considered for further analysis as single violation of Lipinski\u0026rsquo;s rule is acceptable; more than that would question their bioavailability (Daisy et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hou et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the following step, molecular docking was performed to model the atomic interaction between the screened ligands and our target enzyme tubulin-colchicine (PDB ID: 1SA0). The Standard Precision (SP) scoring method of Glide was using for molecular docking assay that was embedded into Schr\u0026ouml;dinger suite-Maestro version 11.2 (Friesner et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Friesner et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This process allowed us to elucidate the binding behavior of our small ligands in the active site of target enzyme (McConkey et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Following the docking process syringaldehyde complex divulged signatory binding affinities over the standard drugs albendazole, levamisole and mebendazole complex binding score in contrast to other compounds p-hydroxybenzaldehyde, benzaldehyde, phenol and ethyl acetate complex. Syringaldehyde binding pattern may hinder the substrate accessibility as it was found to bind extensively with the tubulin-colchicine enzyme. The binding involves pocket constructed by a number of network interactions such as three hydrogen bond interaction of Val 238, Cys 241 and Ala 317; four hydrophobic interactions of Leu 248, Cys 241, Ala 316, and Ala 354 with attaining the prominent binding affinity of -6.519 kcal / mol. These binding properties shows even higher binding affinity than all three standard drugs. Whereas p-hydroxybenzaldehyde, benzaldehyde, ethyl acetate and phenols upon docking with the target protein 1SA0 disclosed comparative lower energy of hydrogen bond and hydrophobic like convenient associations (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Importantly this syringaldehyde is a intricate polyphenolics meanwhile literature statements about phenolic substances that could be the reason why plants have anthelmintic effects since they are protein coagulants, which can affect intestinal worms in a variety of ways (Waterman et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). As predicted by the docking tool, various interaction like hydrogen bonding, van-dar-waal and electrostatic interactions played vital role in the determination of binding free energy and stability of receptor-ligand complex. Thereafter, MM-GBSA process employed for the estimation of precise binding free energies of concerning ligand-receptor complex. Whereas in aligned with larger negative value implies better binding efficacy, Syringaldehyde-1SA0 complex attained lower binding energy of -35.639 kcal/mol relative to ethyl acetate, benzaldehyde, p-hydroxybenzaldehyd, and phenol complex (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Meanwhile, this syringaldehyde molecule, which had a higher docking score and ∆G\u003csub\u003ebind\u003c/sub\u003e MM-GBSA scores with 1SA0 proteins than other phytochemicals, was chosen for a Molecular Dynamics Simulation investigation. MD simulation is a latest computational approach used to analyze and predict the dynamic nature of ligand-receptor complex as a function of time or residue position (Chan \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Haile et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Hollingsworth and Dror \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). It has added a whole new dimension in the field of drug discovery by analyzing the dynamic nature of drug-receptor complex in host by simulating the force field as per requirement (Borhani and Shaw \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Durrant and McCammon \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; De Vivo et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In this study, structural parameters such as- RMSD and RMSF were used to evaluate the stability and dynamic behavior of protein-drug complex. The complex between syringaldehyde and tubulin-colchicine showed quite promising RMSD value of 2.008 \u0026Aring;, which stayed stable over the whole simulation session. This indicates the stability of the complex in the biological system. On the other hand, despite having a lower mean RMSF value of 1.324\u0026Aring;, Leu216, Lys217, Leu218 showed higher mobility indicated by their larger RMSF value of 4.9, 4.8, and 5.1 \u0026Aring; respectively. Hence their impact on the final integrity on the protein-drug complex needs to be confirmed using Dictionary of Secondary Structure of Proteins (DSSP) algorithm. But as observed from the interaction of drug with the target site residues, most of the hydrophobic interaction (Ala317, Leu248, Leu255, Ala316, Ala354, Ala250, Cys241, Ile378 and Val318) and the backbone hydrogen bond with Ala317 remained unchanged even after the 10ns simulation. A similar interaction was observed for tubulin residue with different inhibitors; for instance, in one study(Hamed et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) compound, PMMB-317 interaction with tubulin also showed residue Ala316, Val318, and Leu255 near to the binding pocket. Furthermore, another study(Elmaaty et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Mukunthan et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) showed hydrogen bonding between compound 7 and Ala250 of tubulin as well as non-hydrogen bonding interaction with residue Ala316 highlighting the importance of this residue in the design of potential inhibitor. These data strongly suggest the high binding affinity of the drug with the target protein and their stability in the biological system.\u003c/p\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eThis is the first report describing an \u003cem\u003ein silico\u003c/em\u003e correlation between the predicted pharmacological activities of \u003cem\u003eA. comosus\u003c/em\u003e as per our knowledge. All the in-silico analysis including molecular docking and molecular dynamics simulation concludes that syringaldehyde can be the next promising anthelmintic drug. However, further studies remain necessary to elucidate the underlying mechanism. Thus, this study can offer some precursory evidence for the ethnomedical uses of \u003cem\u003eA. comosus\u003c/em\u003e and it reveals that this plant does contain some active agent that may be responsible for anthelmintic activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource of funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis case report has been reported in line with the Case Report (CARE) guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch registration number (UIN)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registry number\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, methodology, formal analysis, original draft preparation- A.P, M.M.K; software, investigation, data curation- T.D, M.H.U.C, M.M; manuscript review and editing- T.B.E; supervision, project administration- M.M.K\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatements and Declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have read and understood the policy on declaration of interests and have no relevant interests to declare. The responsibility for the content lies with the author and the views stated herein should not be taken to represent those of any organisations or groups with and for which he works.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAamir M, Singh VK, Dubey MK, Meena M, Kashyap SP, Katari SK, et al. In silico prediction, characterization, molecular docking, and dynamic studies on fungal SDRs as novel targets for searching potential fungicides against fusarium wilt in tomato. Front Pharmacol. 2018;9(OCT):1\u0026ndash;28.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAdedeji J, Ho CT, Hartman TG, Rosen RT. Free and Glycosidically Bound Aroma Compounds in Hog Plum (Spondias Mombins L.). J Agric Food Chem. 1991;39(8):1494\u0026ndash;7.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eAgyare C, Spiegler V, Sarkodie H, Asase A, Liebau E, Hensel A. 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Elsevier Ltd; 2020;25(2):430\u0026ndash;7. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ananas comosus, pineapple, SwissADME, computational analysis, molecular dynamics","lastPublishedDoi":"10.21203/rs.3.rs-3859053/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3859053/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHelminths are a major group of pathogens, responsible for a wide range of diseases in human and many other animals through their parasitic interaction with the host. At present a number of helminth species are posing serious threat due to their adroit evasion technique from the immune system and resistance to conventional anti-parasitic drugs. In order to find drug to cope with this challenge, a series of computational analysis was conducted on different compounds identified in Pineapple (\u003cem\u003eAnanas comosus\u003c/em\u003e (L.) Merr.). SwissADME tool predicted the drug likeness of the selected compound based on the Lipinski\u0026rsquo;s rule of five. Out of 33 molecules, five compounds- syringaldehyde, p-hydroxybenzaldehyde, benzaldehyde, phenol and ethyl acetate showed promising binding affinity ranging from \u0026minus;\u0026thinsp;5.011 to -6.519 as depicted from docking score against tubulin-colchicine, potential receptor site for drug designing against helminths. MM-GBSA analysis showed that Syringaldehyde-1SA0 complex attained lower binding energy of -35.639 kcal/mol relative to ethylacetate, benzaldehyde, p-hydroxybenzaldehyd, and phenol complex. Molecular dynamics simulation results further confirmed the potential anti-helminthic activity of syringaldehyde. The receptor-ligand complex showed promising RMSD and RMSF value of 2.008\u0026Aring; and 1.324\u0026Aring; respectively with the major hydrophobic interactions remaining unchanged even after 10 ns simulation. Thus, in this study, syringaldehyde was found to be a potential inhibitor of the tubulin-cholchicine receptor to prevent the progression of helminthic infection in the host cell. Performance of further clinical experiment with this compound, can reveal its true potential as a novel anti-helminthic drug in near future.\u003c/p\u003e","manuscriptTitle":"Anthelmintic Activity of Pineapple: In Silico Molecular docking and Molecular Dynamics Simulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-16 05:31:53","doi":"10.21203/rs.3.rs-3859053/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":"febb1081-aa2f-4346-bc4d-eb5d1421fd47","owner":[],"postedDate":"January 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-28T15:36:07+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-16 05:31:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3859053","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3859053","identity":"rs-3859053","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}