The model structure of HES (ID: 10621) was downloaded from PubChem database.1 The model structures of α-Lactalbumin (α-LA) and β-lactoglobulin (β-LG) named as PDB ID: 1F6S and 1BEB, respectively, were downloaded from the RCSB database2 and then used to carry out the molecular docking simulations, since α-LA and β-LG are the most abundant constituents in WP. Before being imported into the AutoDock Vina Program (AutoDock 1.5.6), the original water molecules and ligands in the α-LA and β-LG 3D structure were deleted using PyMOL tools. In addition, hydrogen atoms and charges were added to the protein molecule structures prior to carrying out the simulations. HES and α-LA/β-LG were set as the ligand and receptor, respectively. The interaction between HES and α-LA/β-LG was then modeled using the AutoDock Vina Program. The docking was performed taking the center of the HES as the grid center (β-LG: −4.5, 4, 16. α-LA: 35, 50, 10) and docking boxes of size was 50Å × 40 Å × 55Å (β-LG) and 120Å × 160 Å × 72Å (α-LA), respectively. Top 10 poses of the docking results were saved, and the one that showed the lowest interaction energy was regarded as the optimized result. The interactions between HES and α-LA/β-LG were visualized using the Discovery Studio 2016 program.
Vina program
Manufactured by AutoDock
AutoDock Vina is a molecular docking software program. It is designed to predict the binding affinity and conformation of small molecules to target proteins. The program uses a scoring function to evaluate the interactions between the ligand and the receptor, and then generates a set of possible binding modes. AutoDock Vina is a free, open-source software available for academic and non-commercial use.
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11 protocols using vina program
1
Molecular Docking of HES with α-LA and β-LG
2
Molecular Docking for SARS-CoV-2 Therapeutic Targets
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For docking studies the crystal structure of DNA, ACE-2, COVID-19 main protease apo- and holo-forms, spike glycoprotein, α5β1 and αııbβ3 integrins and HSA were obtained from the protein data bank (PDB IDs: 1bna ; 6m0j ; 6m03 ; 6lu7 ; 6vxx ; 4wk0 ; 3zdx ; 5z0b, respectively) [[41] (link), [42] (link), [43] (link), [44] (link), [45] (link), [46] (link), [47] (link)]. Molecular docking simulations were performed by the Autodock Vina program [48 (link)] and binding affinities were calculated. The binding free energies of the most stable ligand-DNA and ligand-protein systems, determined by molecular docking analysis, were calculated by the programs developed by Ref. [49 (link)] and the ACFIS 2.0 [[50] (link), [51] (link), [52] (link), [53] (link)].
The active sites of receptors were screened by using the CAVER program [54 (link)].
The active sites of receptors were screened by using the CAVER program [54 (link)].
3
Identifying SARS-CoV-2 Main Protease Inhibitors
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Out of 1,275 similar compounds of boceprevir available in PubChem database [13] (link), we retrieved a total of 180 compounds having molecular weight less than 519.68 g/mol with available 3D conformers. Compounds having a Tanimoto score of 0.9 or greater were considered as similar compounds based on 2D similarity[14] (link). The Mpro structure at room temperature (PDB ID: 6WQF) [9] (link) was selected for docking since it had the suggested protonation states of histidine residues, and the structure was solved at room temperature. It has been suggested that this structure solved at room temperature is more appropriate for molecular docking studies as it provides more relevant information at physiological temperatures [9] (link). The compounds were energy minimized with the steepest descent algorithm prior to docking using UCSF Chimera [15] (link). The selected compounds, along with boceprevir as control were docked by centering the grid box centered on the substrate-binding site of Mpro (x, y and z center coordinates :36.56, 46.43 and 56.04) with the AutoDock vina program [16] (link). The screening was performed with a exhaustiveness value of 8 and ten runs for each compound, and the best pose was selected based on the lowest binding free energy (kcal/mol). The 2D ligand interactions were visualized with the Discovery studio visualizer [17] .
4
Homology Modeling and Molecular Docking of PKCδ
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Since the structure of human PKCδ has not been characterized, homology modeling was performed to generate the human PKCδ protein structure for molecular docking simulations [23 (link)]. The structures of each of the six iridoid compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov/ accessed on 7 January 2021) and determined using the Marvin program (https://www.chemaxon.com accessed on 10 January 2021). As previously described, the docking simulation between PKCδ and each compound was performed using the Autodock Vina program (http://vina.scripps.edu accessed on 6 February 2021), as presented in Table S1 and Supplementary Figure S5 [23 (link)].
5
Antibacterial and Molecular Docking
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The antibacterial activities of isoliquiritigenin, biochanin A, and isorhamnetin were evaluated by filter paper diffusion (5 mg/mL). On the basis of antibacterial activity, the UCSF Chimera software was used for the molecular docking of filamenting temperature-sensitive mutant Z (FtsZ: 4XSG) protein with isoliquiritigenin to predict its interaction force. First, FtsZ protein and isoliquiritigenin were pretreated, which included removing water molecules, adding hydrogen atoms, adding electrons, and minimizing energy. Second, the molecular docking of FtsZ and isoliquiritigenin was performed using the AutoDock Vina program to predict their affinity. The grid box with dimensions of 50 points × 55 points × 55 points was centered on the active site of the protein. Finally, the stability of FtsZ–isoliquiritigenin binding was evaluated with reference to the binding energy. A low score corresponded to high stability.
6
Molecular Docking of Cofactor and Substrate
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To estimate the binding mode of the cofactor with the substrate, molecular docking studies were performed using the Autodock Vina program (51 (link)). The cofactor (PQQ) and substrate (l -fucose:α-l -fucopyranose) were built and minimized with Gasteiger charges in the UCSF Chimera system (52 (link)). Further, minimized cofactor and substrate structures were prepared for docking studies by applying the standard ligand docking protocol. The structure of TrAA12 solved with the active calcium was chosen as the protein model. For protein preparation, all hydrogen atoms added and nonpolar hydrogens were also merged. The Kollman united atom charge and atom type parameters were added. The calcium ion present in the active site was assigned a +2 charge. For the cofactor and substrate, two separate docking sites were set in such way that included the cofactor binding site and the active site. Thirty dock poses were generated for each ligand. The dock conformation with the lowest docking energy, the lowest metal ion distance, and the best superimposition on the reported homologue complex structure (PDB accession number 1CQ1 ) from the bacterium Acinetobacter calcoaceticus was chosen (12 (link)). Further, the interactions of the protein-ligand complex, the hydrogen bonds, and the hydrogen bond length were analyzed in the UCSF Chimera system (52 (link)).
7
Computational Docking of c-MYC G4 Ligands
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The NMR structure of a mutated c-MYC G-quadruplex (PDB 2MGN) was used to perform docking study on ligands 2 and 3 . The three-dimensional structure of small molecules was sketched with DS viewer 3.5. Autodock Tools (version 1.5.6) was used for converting structure files to pdbqt format (49 (link)). The docking study was carried out by using AutoDock Vina program (50 (link)). The dimensions of the active site box were chosen to be large enough to encompass the entire G4 structures. An exhaustiveness of 100 was used and other parameters were left as default.
8
Molecular Docking of 15-LOX-2 Interactions
9
Molecular Docking of HNK with DCLK1
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The docking study was done using AutoDock Vina Program [31 (link)] to predict the interaction of HNK with DCLK1. The kinase domain of DCLK1 PDB ID (5JZN.pdb) protein was downloaded from the Protein Data Bank (RCSB PDB) online database on 22 January 2021 (www.rcsb.org/pdb ). The ligand molecules in the active site were removed and the 3-D grid box was created with grid center coordinates and 60 × 60 × 60-point size covering all of the active site residues. The studies used default parameters of the Autodock Tools. Before docking, the protein was prepared by adding hydrogens, total Kollman, and Gasteiger charges. To obtain the best confirmations, Lamarckian GA was utilized. About 10 conformations for HNK docked in the DCLK1 kinase domain were generated, of which the most stable conformation was selected based on the predicted lowest binding energy and the number of hydrogen bonds. The DCLK1-HNK docking conformation was visualized on 22 January 2021 with PyMOL 2.5 (https://pymol.org/2/ ) software [32 (link)].
10
Molecular Docking for Network Pharmacology Validation
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In this study, molecular docking method was preliminarily utilized to validate the results of network pharmacology. Through the RCSB Protein Data Bank (PDB, http://www.rcsb.org/pdb ), protein receptors of hub genes were selected according to the following criteria: (1) the structure of protein receptors was identified by X-ray diffraction, (2) X-ray resolution < 3 as the first choice, and (3) protein structures containing original ligands (e.g., inhibitors) were preferred. By using AutoDockTools1.5.6 (http://autodock.scripps.edu ), the original ligands (if any), excess protein chains, and water molecules of the protein receptor were removed, then hydrogen was added to the protein receptors, and possible docking coordinates were searched. The structure (“mol2” format) of the corresponding bioactive ingredients of the target protein was obtained by TCMSP database. Subsequently, the file format of protein receptor or bioactive ingredient was converted to “PDBQT” using AutoDockTools, and molecular docking was performed using AutoDock Vina program (http://vina.scripps.edu/ ). Finally, the results were analyzed and visualized using PyMOL (http://www.pymol.org/ ) and Discovery Studio 2016.
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