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Tools version 4

Manufactured by AutoDock
About the product

AutoDock Tools version 4.2 is a molecular docking software package used for predicting the interaction between a small molecule and a target protein. It provides a graphical user interface for preparing input files, running docking simulations, and analyzing the results.

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10 protocols using «tools version 4»

1

Docking of Synthetic Compounds Against Bacterial Gyrase

2025
The docking computation of the synthesized compounds 16(a–u) was performed with AutoDock Tools version 4.2. The protein data bank (https://www.rcsb.org/) provided the crystal structures of the bacterial DNA gyrase proteins from E. coli and S. aureus. ChemDraw Ultra 12.0 was used to create the 3D structures of the synthesised ligands. During the molecular docking process, polar H-bonds were initially added, while confined ligands containing water molecules were removed, and the other default parameters were used. The docked complex of the ligand–receptor was visualised in two dimensions using PyMOL (https://www.pymol.org/) and BIOVIA Discovery Studio R2 2017. The best docking score was then chosen for additional evaluation of its antibacterial activities.29 (link)
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2

Molecular Docking of Curcumin with Keap1-Kelch Protein

2023
The 3D structure of Keap1-Kelch protein complex (ID no. 3WN7) was retrieved from the Research Collaboratory for Structural Bioinformatics Protein Data Bank database (https://www.rcsb.org/). Autodock Tools version 4.2.6 (https://autodock.scripps.edu/) was used to preprocess initial protein structure, which involved removing water molecules, adding hydrogen atoms and exporting the structure to a pdbqt file for docking. The 2D structure of CUR was obtained from the PubChem database (pubchem.ncbi.nlm.nih.gov/) and converted into a Mol2 file using OpenBabel 2.3.1 (http://openbabel.org/wiki/Main_Page) software. Subsequently, hydrogen atoms were added, the charge was self-distributed and torsional construction detection was performed on the CUR structure. Docking was performed using Autodock Tools and the results were optimized using the PyMOL Molecular Graphics System software 2.4 (pymol.org/2/).
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3

Molecular Docking Analysis of Tualang Honey Compounds

The molecular docking approach was employed to analyze the interactions between the bioactive compounds of Tualang honey and the hub genes identified in the study. This computational method is commonly utilized in drug discovery as it enables predictions of binding modes and affinities between receptors and ligands. The crystal structures of the six hub genes—SRC (PDB ID: 1O43), PIK3R1 (PDB ID: 315R), PIK3CA (PDB ID: 6PYS), EGFR (PDB ID: 8A27), PTPN11 (PDB ID: 3B40), and AKT1 (PDB ID: IUNQ) were obtained from the RCSB Protein Data Bank (https://www.rcsb.org/, accessed on 13 February 2023) [38 (link)]. The 3D structure of the Tualang honey compounds (catechin, ethyl oleate, fisetin, hesperitin, kaempferol, and luteolin) was retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/, accessed on 14 February 2023) [39 (link)]. The compounds served as the ligands and the hub genes as the receptors. The receptors were prepared in Biovia Discovery Studio 2021 [40 ] by removing water molecules and existing ligand. The binding conformation between the ligand and receptor was predicted by AutoDockTools Version 4.2 (http://autodock.scripps.edu/, accessed on 16 February 2023) [41 (link)], and the binding energy, which is an outcome of molecular docking, was used to assess the potential of the ligand–receptor binding (typically, ≤−5 kcal/mol). Finally, the visualization of molecular interactions between the proteins and ligands was performed using Discovery Studio Visualizer 2021.
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4

Molecular Docking of Bioactive Compounds in E. tapos Yogurt

2023
The study used a molecular docking approach to examine the interactions between the specific bioactive compounds found in E. tapos yogurt and the identified hub genes to understand the binding modes and affinities between the receptors and ligands by predicting their binding interactions. The crystal structures of eight hub genes (PIK3R1, HRAS, MAPK1, STAT3, EGFR, LYN, PTPN11, and SRC) were obtained from the RCSB Protein Data Bank (https://www.rcsb.org/, accessed on 20 June 2023) [30 (link)], while the 3D structures of the selected bioactive compounds (Flazin, Medicagol, and Scropolioside A) from E. tapos yogurt were retrieved from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/, accessed on 20 June 2023) [31 (link)]. The compounds served as ligands, and the hub genes acted as receptors. The receptor structures were prepared by removing the water molecules and existing ligands using Biovia Discovery Studio 2021. The binding conformation between the ligands and receptors was predicted using AutoDockTools Version 4.2 (http://autodock.scripps.edu/, accessed on 21 June 2023) [32 (link)], and the resulting binding energy, a measure of the molecular docking outcome, was used to evaluate the potential of the ligand–receptor binding (typically ≤ −5 kcal/mol). Finally, the Discovery Studio Visualizer 2021 was used to visualize the molecular interactions between the proteins and ligands. The summarized Table 1 below presents the selection of PDB IDs refined for the homo sapiens species.
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5

Molecular Docking of Ligands to GPCR Receptors

2022
EC and molecules of interest were downloaded as “mol2” from the ChemSpider online molecular database (http://www.chemspider.com, accessed on 20 October 2020), and converted to “PDB” in PyMol and then processed using AutoDock Tools 4.0 [56 (link)], where polar hydrogens and Gasteiger charges were added. Potential receptors in their active and inactive conformations were downloaded from the online GPCR database (https://gpcrdb.org, accessed on 20 October 2020), and then processed in AutoDock Tools version 4.0 to add polar hydrogens and Kollman charge. The grid box for a blind docking assay was placed in the receptor center with coordinates at x = 24.096, y = 62.263, and z = 11.917; dimensions of x = 50, y = 60, and z = 50 were obtained based on the center of the protein. Following this, 1000 independent replicates were performed with the Vina software [57 (link)] using a previously described script written in Shell [58 (link)] to facilitate the work with each ligand. Then, based on the ligand coordinates, the receptor-binding site was calculated, and the most frequent interaction site was defined and established as the most favorable conformation.
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