Molecular docking was performed between the core proteins and their associated components of YT to further explain the potential mechanism and material basis of YT in the treatment of diarrhea. The 3D structures of target proteins were downloaded from the RCSB Protein Data Bank (PDB, http://www.rcsb.org ) and saved in pdb format. PyMOL (https://pymol.org ) was used to isolate the macromolecules and their protoligands, and the structures of the macromolecules were then optimized using AutoDock Tools 1.5.6. It removed water molecules, added hydrogen atoms, repaired the charges by adding a Gasteiger charge, and was saved in pdbqt format. The structure information of small molecule compounds of YT was obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/ ) and then kept in mol2 format. AutoDockTools 1.5.6 was used to count the number of rotatable chemical bonds, and the compounds were saved in pdbqt format. The macromolecule grid box was defined according to the protoligand site using AutoDockTools 1.5.6. Furthermore, an accurate docking with the components of YT and target proteins was performed using AutoDock vina 1.1.2, setting the energy range = 5 and exhaustiveness = 100, and the best docking conformation was analyzed with PyMOL and LigPlot+ v.2.2.
Tools 1
Manufactured by AutoDock
Sourced in United States
AutoDock Tools 1.5.6 is a molecular docking software package. It allows users to perform automated docking of ligands (small molecules) to protein receptors. The software provides a graphical user interface for preparing input files, running docking calculations, and analyzing the results.
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Lab products found in correlation
Vina 1, by AutoDock (175 mentions)
Tools, by AutoDock (41 mentions)
Chembiodraw ultra 14, by Revvity Signals Software (20 mentions)
Vina software, by AutoDock (17 mentions)
Chembiodraw ultra 17, by Revvity Signals Software (8 mentions)
Tools v1, by AutoDock (4 mentions)
Vina 4, by AutoDock (4 mentions)
Vina v1, by AutoDock (4 mentions)
Discovery studio 2019, by Dassault Systèmes (3 mentions)
Maestro, by Schrödinger (3 mentions)
Pymol molecular graphics system, by Schrödinger (3 mentions)
Autodocktools software, by AutoDock (2 mentions)
Autodock4version 4, by AutoDock (2 mentions)
Vina30, by AutoDock (2 mentions)
Chem3d, by PerkinElmer (2 mentions)
Discovery studio visualiser, by Dassault Systèmes (2 mentions)
Dock 6, by AutoDock (2 mentions)
Discovery studio visualizer 2020, by Dassault Systèmes (2 mentions)
Chembiodraw ultra 12, by Revvity Signals Software (2 mentions)
Pymol 2, by Schrödinger (2 mentions)
754 protocols using tools 1
1
Molecular Docking for YT Treatment Mechanism
2
Molecular Docking of Acarbose and Araloside A with α-Glucosidase
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Molecular docking was applied to determine the possible binding site(s) between acarbose, araloside A and α-glucosidase. The structure of α-glucosidase was determined through homology modelling (PDB ID: 3A4A). After removing extraneous small molecules from protein molecules using PyMOL 2.3 software, protein molecules were imported into AutoDock Tools-1.5.6 software to remove water molecules, hydrogen atoms were added, and the structures were saved as pdbqt files. Small-molecule compounds were imported into AutoDock Tools-1.5.6 software, water molecules were removed, atomic charges were added, atom types were assigned, all flexible bonds were made rotatable by default, and the files were saved as pdbqt files. All docking experiments were performed using AutoDock Tools-1.5.6 software. During the calculations, an 80x80x70 dot matrix module with 0.375 intervals and centre settings (−15.640, −35.005, −3.958) was used. Molecular docking calculations were performed using the Lamarckian genetic algorithm with the following parameters: a population of 150, a maximum of 25 million energy evaluations, a maximum number of 2000, a crossover rate of 0.8, a mutation rate of 0.02, 50 independent docking runs and an evaluation of the final docking structure based on the binding free energy. Docking results were visualized using PyMOL 2.3 software.
3
Molecular Docking Analysis of Protein-Drug Interactions
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The three-dimensional structure of the proteins were downloaded from the RCSB protein database (www.rcsb.org ). The proteins used (PDB ID: 1lgp, 2xp0, and 2e19) were opened in Autodock Tools 1.5.6. By adding all hydrogen atoms, the Gasteiger particle size was calculated and the non-polarity was combined. After hydrogen, we define it as a receptor and save it as a pdbqt file. Small-molecule drugs were downloaded from the National Library of Medicine (https://pubchem.ncbi.nlm.nih.gov/ ). The drugs used (PubChem CID: 444732, 5311) were opened in Autodock Tools 1.5.6. The molecular docking simulation has been performed by Autodock 4.2 package, and the corresponding Autodock Tools 1.5.6 has been used to prepare all necessary input files and analyze the docking results.
4
Molecular Docking of IRAK4 Inhibitors
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The target protein IRAK4 protein data bank identity [(PDB ID): 6thx] was obtained by searching the PDB structure database (https://www.rcsb.org/ ), and it was imported into PyMOL to remove the water molecules as well as the original ligands, and then imported into the AutoDock Tools 1.5.6, hydrogenated, set as receptor, and saved as pdbqt format. The sdf 3D structures of QUE and the above target protein inhibitors (IRAK4-IN-4, CHIR-98014, Selisistat) were obtained from the PubChem database, and minimum energy optimization was performed with an MM2 force field of Chem3D, and the results were saved in mol 2 format. AutoDock Tools1.5.6 hydrogenates small molecules, set them as ligands, detected and set torsional bonds, and finally saved them in pdbqt format. The docking parameters of AutoDock Vina software were set with AutoDock Tools 1.5.6, with a docking count of “num_modes = 20”, a docking box size of the whole protein, and other defaults. The minimum binding energy conformation was exported as a pdb file, and the ligand-protein complex was generated with PyMOL, and then imported into Discovery studio software, hydrogenated to show the interactions, and finally visualized.
5
Molecular Docking of Active Compounds
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AutoDockTools 1.5.6 was used to accomplish molecular docking. The critical target’s atomic coordinates were collected from the Protein Data Bank (PDB) and generated in AutoDockTools-1.5.6 by eliminating water molecules, adding charge, and parameterizing. Downloaded from the TCMSP Database, the 3D structures of active components were built in AutoDockTools by calculating atomic partial charges and parameterizing. The docking site was positioned in the middle of the original ligand inside a cuboid box, and a grid map of each atom type within the box was calculated. Molecular docking of possible targets and components was simulated using the AutoDockTools-1.5.6 program. Each compound’s highest-scoring conformer was examined and displayed using AutoDockTools-1.5.6 and PyMOL.
6
Molecular Docking of Phytochemicals
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Molecular docking was performed using AutodockTools-1.5.6. The atomic coordinates of the crucial target were retrieved from the Protein Data Bank (PDB) (www.rcsb.org ) and prepared in AutodockTools-1.5.6 by removing water molecules, adding charge, and parameterizing. The 3D structures of active ingredients were downloaded from the TCMSP Database and prepared in AutoDockTools by computing atomic partial charges and parameterizing. The docking site was set in a cubic box in the center of the initial ligand, and a grid map of each atom type in the box was computed. The AutodockTools-1.5.6 software was used to simulate the molecular docking of potential targets and components. The best scoring conformer of each compound was analyzed and visualized in AutodockTools-1.5.6 and PYMOL.
7
Molecular Docking Analysis of Active Ingredients
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Molecular docking analysis was performed to validate whether the key active ingredients could bind to the core targets.[36 ] First, the 2D structures of the key active ingredients were downloaded from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/ ).[37 (link)] The structures were imported into AutoDockTools-1.5.6 software to add charges and display rotatable bonds, and were then saved in pdbqt format. Second, the crystal structures of the proteins corresponding to the core targets were downloaded from the Protein Data Bank (PDB, https://www.rcsb.org/ ).[38 (link)] Then, these structures were imported into PyMOL software to remove water molecules and heteromolecules, and imported into AutoDockTools-1.5.6 to add hydrogen atoms and charges and saved in pdbqt format. Finally, the 3D grid box for molecular docking simulation was created using AutoDockTools-1.5.6 and visualized with AutoDock Vina 1.1.2.[39 (link)] The results were analyzed and visualized using PyMOL and Ligplot software.
8
Biochanin A Molecular Docking Analysis
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Biochanin A’s structure SDF format was obtained from the PubChem database and converted into PDB format using Openbabel. This structure was opened by using AutoDockTools1.5.6 [29 (link)] and supplemented with hydrogen and charge as ligands. The PDB format of the 3D structures of key target proteins, such as AKT1, TNF-α, nitric oxide synthase 3 (NOS3), VCAM1, and ICAM1, which were screened based on the PPI network, was obtained from the RCSB protein database. The protein structure was separated from water molecules by using the PyMol software [30 (link)]. This structure was also opened by using the AutoDockTools1.5.6 software, and hydrogen and charge were added as the receptor. To determine the optional configuration, the AutoDockTools1.5.6 was also used for docking. Binding energy’s lowest conformation was analyzed, and the binding mode was obtained. For the visual operation, PyMol software was utilized.
9
Molecular Docking for Target Identification
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Based on the results of the PPI network and drug–compound–target gene network, we selected the top 3 ranked targets and components for molecular docking. The PubChem database (https://pubchem.ncbi.nlm.nih.gov/ ) provides components’ names, 2D structures, molecular formulas, and molecular weight. The top 3 ligands (2D format) were downloaded from the database, then the structures of ligands were optimized using the Chem 3D software and Auto Dock Tools 1.5.7 software, and then prepared for molecular docking. Protein Sequence Database (https://www.rcsb.org ) provides proteins’ 3D structure, the structures of the core targets were downloaded, and then, excess chains, ions, and water molecules were removed by the PyMOL software. The Auto Dock Tools 1.5.7 software was utilized to add hydrogen atoms and convert their format for docking. Afterwards, the ligands and receptors were imported in sequence in the AutoDock Tools 1.5.7 software, grid box parameters were configured and saved, and molecular docking was accomplished through the AutoDock Vina software. Finally, the PyMOL software was utilized to display the molecular docking results. It is generally accepted that a docking score less than or equal to -5.0 kcal/mol indicates a strong affinity between the docked compound and the target.[19 (link)]
10
Diosgenin-IGF-1R Binding Affinity
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The IGF-1R protein crystal structures were obtained from the RCSB Protein Data Bank (http://www.rcsb.org/pdb/ ) (Goodsell et al., 2020 (link)) and saved in pdb format. Diosgenin structures were downloaded through PubChem converted to. pdb format files via Open Babel (O'Boyle et al., 2011 (link)). Auto Dock Tools 1.5.6 software (Cosconati et al., 2010 (link)) was used to remove water molecules, to add nonpolar hydrogen bonds, to calibrate the Gasteiger charge and to save them as pdbqt format files. Diosgenin was performed with energy minimization, assigned the ligand atom type, calculated the charge, and saved in pdbqt format. Then, Auto Dock Tools 1.5.6 software was used to calculate the docking score to evaluate the matching degree and docking activity between a target and its ligand. A docking score < −4.25 can be considered as having binding activity; a score < −5.0 can be considered as having better binding activity; and a score < −7 can be considered as representing a strong docking activity between the ligand and the target. The binding model was visualized using PyMol2.3.0 software (Seeliger and de Groot, 2010 (link)).
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