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142 protocols using AutoDock Vina software

Docking of HVGGSSV to TIP1 was performed by using Autodock Vina software [17 (link)]. Peptide structures were prepared by using online software Probuilder (http://159.149.85.2/probuilder.htm). The output file that we generated was pdb2.2, secondary structure was alpha helix, phi -1350C, Psi- 1350C and omega 1800C. Peptide structure was minimized and hydrogens added by chimera software. The high-resolution crystal structure of TIP1 in complex with beta-catenin (PDB ID: 3DIW) was obtained from the RCSB protein data bank (http://www.pdb.org). The waters and ligand were removed from the original crystal structure. Protein structure was minimized, and hydrogen was added by chimera software. For minimization, the steepest descent step was 100 and step size 0.02Å. The incomplete side chains were replaced using Dunbrack rotamer library [18 (link)]. Energy-minimized TIP1 was docked with energy-minimized HVGGSSV using Autodock Vina software. The overall quality of the minimized model was evaluated to ensure the model quality by utilizing PROCHECK [19 (link)] for evaluation of Ramachandran plot quality. The structure of HVGGSSV in complex with TIP1 was generated by Pymol software (Schrodinger Inc.). Ligplot was used to identify the hydrogen bonds and to perform hydrophobic interaction analysis [20 (link)].
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The crystal structure of TLR4 came from the Protein Data Bank (PDB code: 2Z66). The ligands and water molecules were removed from the crystal structure via Pymol (https://pymol.org/2/). The structure of bergenin, chlorogenic acid, and ammonium glycyrrhizate (ammonium removed) was obtained from PubChem database (https://pubchem.ncbi.nlm.nih.gov/) and hydrogen atoms were added by using AutoDock Vina software. The rigid target-site docking procedures were performed using AutoDock Vina software with a genetic algorithm.15 (link) Hydrogen bonds and bond lengthanalysis and visualization were performed using Pymol.
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To better understand the relationship between anticipated epitopes and their respective alleles, AutoDock Vina software was used to perform molecular docking. It helps us to interpret the synergy between antigenic sites and their corresponding alleles (Trott and Olson 2010 (link)). One of the prerequisites before performing docking is certain modifications both in ligand as well as the receptor, which was performed by AutoDock MGL tools. HLA alleles were selected as receptors viz., DRB1_0101, DRB1_0701, and DRB1_1301. 4AH2, 3C5J, and 6CQL are the crystal structure of these receptors and were retrieved from the Research Collaboratory for Structural Bioinformatics (RCSB) protein data bank. Molecules of water were removed from these receptors and polar hydrogen as well Kollman charges were added to the structure. After modification, the molecule was saved in pdbqt format. Changes were also performed in all 20 ligands and were saved in pdbqt files. All these alterations were performed by AutoDock MGL tools. To perform molecular docking in AutoDock Vina software, 40, 40, 40 were taken as grid box dimensions and energy was calculated at 0 Å. The docking result can be analyzed by a visualization tool called PyMol. 4 epitopes were selected for succeeding rounds of analysis based on negative binding energies where Low binding energy implies good stability.
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To reveal the binding patterns between the active compounds and the targets, AutoDock Vina software, Discovery Studio 4.5 Client and PyMOL software were used. The 3D structures of the central targets (receptors) were obtained from the RCSB PDB11 database and saved into PDB format. The obtained 3D structures (in PDB format) were further processed using PyMOL software (version 2.2.0) to remove water molecules (“solvent removal” command) and small ligands (“organics removal” command). The active compounds in 2D structures in SDF format were downloaded from PubChem website (see footnote 3). The files were then converted into PDB format using the Open Babel software (version 2.4.1). Hydrogen and Gasteiger charges were added to the above receptors and ligands using AutoDock Vina software, and then saved into PDBQT format. The AutoGrid tool of AutoDock Vina software was used to set the interfacing frame parameters, including the grid box that contained the entire system. The parameter was set to Lamarck Genetic Algorithm (LGA), which generated 10 docking results for each ligand and corresponding receptor. All the docking results were visualized by PyMOL software. Finally, the optimal docked structure could be obtained based on the docking scores of all the possible docked structures.
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5

Molecular Docking Analysis of Ferulic Acid Interactions

To verify the core targets in protein levels, molecular docking technology was used to better characterize the interaction activities between ferulic acid and TBI‐related core proteins. Regarding in silico procedures, the protein molecular structure of core targets was downloaded from the Protein Data Bank database (Zardecki et al., 2022 (link)). Chem Bio Office 2010 was used for 3D structure optimization with ChemBio3D Draw. Data were verified using Autodock Vina software. For binding assessment, the molecular docking setting was configured. To characterize the biological conformations in respective poses, the docking active center was scored for the binding energy between ligands and proteins. The optimal binding poses in every molecule were determined accordingly, and the molecular certification of the binding poses was assayed via Autodock Vina software by using a grid box setting (Forli et al., 2016 (link)). The docked parameters were scored and detailed for in silico visualization (Forli et al., 2016 (link); Zardecki et al., 2022 (link)).
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Three-dimensional (3D) structure of α-synuclein (SNCA; PDB ID: 3Q29), nitric oxide synthase 1 (NOS1; PDB ID: 6PNA) and muscarinic acetylcholine receptor M1 (CHRM1; PDB ID: 6WJC) was retrieved from RCSB PDB database.29 (link) Using Autodock Vina software,37 (link) water molecules were removed, proteins were separated, non-polar hydrogen was added, the Gasteiger charge of the structure was calculated, and saved as a PDBQT file. The two-dimensional (2D) and 3D structures of Ketamine (PubChem CID: 3821) were downloaded using the PubChem database.28 (link) The 2D structures were converted to PDB format by Chem3D processing and saved as docking ligands in Autodock Vina software in PDBQT format. According to visually inspected and docking score, SNCA, NOS1 and CHRM1 were used as receptors, and ketamine was used as ligand. The conformation with the best affinity was selected as the final docking conformation, and PyMOL was used to analyze the docking results. The higher the absolute value of the binding free energy, the greater the stability of a protein–ligand complex.
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Initial models for EcolC_1642 were generated by I‐TASSER server (https://zhanglab.ccmb.med.umich.edu/I‐TASSER/)
37 (link), using the PSIPRED program
38 (link) to help validate the secondary structure. Subsequently, the top‐scoring model was submitted to the GalaxyRefine server (http://galaxy.seoklab.org/index.html)
39 (link) for rebuilding and repacking the side chain as well as suffering an overall structure relaxation by molecular dynamics simulation. Molecular docking was performed using Autodock Vina software (v1.1.2)
40 (link). Ligand D‐xylose and D‐glucose structure were retrieved from the ZINC site (http://zinc.docking.org/)
41 (link). Proteins and ligand structures were prepared for docking by using Autodock Tools v1.5.4 (grid box was set to 20 × 20 × 20 Å). All of the structures were visualized and manipulated using UCSF Chimera (v1.13.1)
42 (link).
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In order to further analyse the molecular mechanism of the six small-molecule compounds in the treatment of COVID-19, we selected 3 targets (angiotensin-converting enzyme 2 (ACE2), viral main protease 3C-like protease (3CLpro) and Spike protein (Spike)) for molecular docking with them. Firstly, the MOL2 structures of the active components were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/, accessed on December 5, 2022) and energy minimization was performed via Chem 3D software (version 19.0.0.22). Then, high-resolution crystal structures of the targets were obtained through the Protein Data Bank (PDB, https://www.rcsb.org/, accessed on December 5, 2022) platform and imported into PyMOL software (version 1.7.2.1, https://pymol.org/2/, accessed on December 5, 2022) for structural optimization and saved in PDB format. Finally, AutoDock Vina software (version 1_1_2, https://vina.scripps.edu, accessed on December 5, 2022) was used to complete molecular docking between active components and candidate targets. PyMOL software (version 1.7.2.1) was used to generate graphs of the results of molecular docking.
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In this study, molecular docking experiments were conducted to investigate the interaction between resveratrol and the core target [30 ]. Initially, the protein structure that corresponds to the core target was procured from the PDB database. Following this, the Pymol software was employed to eliminate water and ligands from the receptor protein. Additionally, Autodock tools software was utilized for receptor protein modification through hydrogenation and charge balancing. The Grid Box command was employed to access the Grid Option tool, which facilitated the processing of the receptor protein and the determination of the ligand binding pocket dimensions. These dimensions were ascertained based on the lattice points quantity and the inter-point spacing in each direction, with appropriate adjustments made to the lattice points number, binding pocket center, and grid points spacing. To simulate the binding mode of resveratrol with the target protein, Autodock Vina software was employed, and the affinity was subsequently computed to appraise the ligand's binding efficacy to the receptor molecule, with a lower energy value indicating a superior binding effect.
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10

Molecular Docking of pBthTX-I Peptide to SARS-CoV-2 PLpro

AutoDock Vina software [61 (link)] was used to perform molecular docking. SARS-CoV-2 PLpro three-dimensional structure was retrieved from RCSB PDB [62 (link)] (PDB ID: 6WX4) [33 (link)]. The ligand bound to the catalytic site was used as a reference for the binding site definition. The 3D structure of the (pBthTX-I)2K peptide was prepared for docking by a minimization step, using Chem3D® from PerkinElmer Informatics (Waltham, MA, USA) (gradient norm less than 0.010). The partial charges assignment was computed with the Gasteiger charge method, using AutoDockTools-1.5.6 [63 (link)]. The grid calculation was set using default parameters and centered at X = 8.143, Y = −26.919, and Z = −31.882. The search box was defined according to the 6WX4 ligand binding site using AutoDockTools-1.5.6 and set as 26 Å × 26 Å × 36 Å. Exhaustiveness was set to 10, with a maximum number of binding modes set to 15. The binding affinities of the top (pBthTX-I)2K poses bound to SARS-CoV-2 PLpro were used to identify the binding mode that best correlated with the assessed inhibitory potency.
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