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131 results for “molecular docking”
Molecular Dynamics Simulation and Docking Studies Reveals Inhibition of NF-kB signaling as a Promising Therapeutic Drug Target for reduction in Cytokines Storms
<p><span>The complexes of the top identified molecules with NF-kB-kB site, as well as all the designed molecules used in the screening process. </span></p>
Interaction of N-3-oxododecanoyl homoserine lactone with transcriptional regulator LasR of Pseudomonas aeruginosa: Insights from molecular docking and dynamics simulations
<p>Dataset and supplementary files of the research: Interaction of N-3-oxododecanoyl homoserine lactone with transcriptional regulator LasR of Pseudomonas aeruginosa: Insights from molecular docking and dynamics simulations (https://doi.org/10.1101/121681)</p> <p>- Supporting Information</p> <p>- Input: Parameters and initial structures</p> <p>- Output: Trajectories, Docking poses</p> <p>Gromacs (multi-core with CUDA) was used for the simulations.</p> <p>Autodock Vina, FlexAid and rDock were used for molecular docking.</p>
Identification of Potential JNK3 Inhibitors Through Virtual Screening, Molecular Docking And Molecular Dynamics Simulation as Therapeutics for Alzheimer's Disease
<p>Alzheimer's disease (AD) is a complex neurological disorder without effective treatment. One factor in its development is c-Jun N-terminal kinases (JNKs), a type of protein related to brain function. JNK3, found mainly in the brain, contributes to AD by promoting brain abnormalities. Current research aims to create new JNK3 inhibitors for AD treatment using a virtual screening method. A database of compounds was filtered, and five potential compounds were identified with better scores than a reference. These compounds underwent simulations and energy calculations, showing stability and potential as JNK3 inhibitors.</p>
Data from: Benzyl alcohol synergistic effect with deltamethrin against Musca domestica with molecular docking of potential modes of action
Open the record for dataset details and reuse information.
Data from: Synthesis, antimicrobial evaluation, ADMET prediction, molecular docking and dynamics studies of pyridine and thiophene moieties containing chalcones
Open the record for dataset details and reuse information.
Inputs for Galaxy tutorial on molecular docking on SARS-CoV-2 MPro
<p>Inputs for Galaxy tutorial on molecular docking on SARS-CoV-2 main protease.</p>
Data from: Molecular docking and dynamics studies to identify novel active compounds targeting potential breast cancer receptor proteins from an indigenous herb Euphorbia thymifolia Linn
<p>Breast cancer has become most prevalent disease and their incidence has doubled in Indian scenario. Targeted therapy with the novel compounds derived from plants could be the promising approach for the development of drugs. <em>Euphorbia thymifolia</em> L is a widely growing tropical herb which has been reported for its various ethnopharmacological properties, including anticancer properties. The aim of the present study was to identify the active phytocompounds present in the methanolic extract using an <em>I</em><em>n-silico</em> approach. The methanolic extract of <em>E. thymifolia</em> (ME.ET) was subjected to GC-MS analysis and the identified compounds were docked with potential protein targets implicated in breast cancer such as ERK1, AKT, EGFR/HER2, ER, MELK, PLK1, PTK6. Compounds with good docking score were further subjected to dynamics study to understand the protein ligand binding stability, ligand pathway calculation, molecular mechanics energies combined with Poisson-Boltzmann (MM/PBSA) calculation using Schrodinger suite. Out of 219 unique phytocompounds subjected to docking, two compounds namely, 3,6,9,12-tetraoxatetradecane-1,14-diyl dibenzoate (TTDB) and succinic acid, 2-(dimethylamino)ethyl 4-isopropylphenyl ester (SADPE) showed good docking score. Molecular dynamics study showed high affinity and low binding energy for TTDB with HER2, ERK1 and SADPE with ER. Hence this is the first study to identify and report active compounds from <em>E.thymifolia</em> linn. Further <em>invitro</em> and <em>invivo</em> anticancer studies can be performed to confirm these results and understand the molecular mechanism by which TTDB and SADPE exhibit anticancer activity against breast cancer.</p>
Molecular docking and quantum-chemical characterization of inhibitory activity of procyanidins and flavonol glucosides from Graptopetalum paraguayense E. Walther against nonstructural proteins of SARS-Cov-2
<p>The dataset includes:</p> <ol> <li><span>Optimized geometries of all ligands, NSPs and their complexes in gas phase</span></li> <li><span>Total energies (a.u.) and interaction energies (a.u. and kcal mol-1) of the complexes, ligands and NSPs in gas phase and in argon</span></li> <li><span>Mass spectra (full ms) and product ion spectra (ms2) of standards and identified components from GP. </span></li> <li><span>Output files from quantum-chemical calculations.</span></li> <li><span>pdb files of NSPs</span></li> <li><span>mol files of all complexes</span></li> </ol>
Molecular docking analysis was performed to assess the affinity of onalespib for their targets LOX, elucidating binding poses, protein interactions, and associated binding energies.
<p>To analyze the binding affinities and interaction modes between the drug candidates and their targets, we employed the Autodock Vina software [21]. Molecular structures of the candidate drugs and targets of hub genes were retrieved from Pubchem (https://pubchem.ncbi.nlm.nih.gov/) and Protein Data Bank database (http://www.rcsb.org/), respectively. <span>In the analysis of docking, the files for all proteins and molecules were converted to PDBQT format. Water molecules were removed and polar hydrogen atoms were added. The grid box was positioned at the center to encompass the protein domain, allowing for unrestricted movement of molecules.</span></p>
Supporting Information for Cholinergic Selectivity of FDA-approved and Metabolite Compounds Examined with Molecular Docking-based Virtual Screening
<p><span>Typical docking configurations, detailed docking and visualization results for representative ligands and proteins. </span></p>
Data Sets for Article: Exploration on Learning Molecular Docking with Deep Learning Models
<p>The MOL2 and CSV file of the clustered compounds from ChemDiv are available in <strong>Additional file 2</strong></p> <p>Docking scores of training set1 and the following traing set2 for each target were saved as csv files and provided in <strong>Additional file 3.</strong></p> <p>The SMILES, MOL2, SDF of DUD-E compounds and PDB of receptors used for validation are provided in <strong>Additional file 4</strong>.</p> <p>The SMILES of 500,000 compounds randomly selected from the ChEMBL database are provided in <strong>Additional file 5</strong></p> <p>The SMILES of compounds with activities from the ChEMBL database for each target are provided in <strong>Additional file 6</strong></p>
Tabulation Result of Molecular Docking Simulation
<p>Tabulation Result of Molecular Docking Simulation</p>
Figures S1–S10 from: Shoman ME, Abd El-Hafeez AA, Khobrani M, Assiri AA, Al Thagfan SS, Othman EM, Ibrahim ARN (2022) Molecular docking and dynamic simulations study for repurposing of multitarget coumarins against SARS-CoV-2 main protease, papain-like protease and RNA-dependent RNA polymerase. Pharmacia 69(1): 211-226. https://doi.org/10.3897/pharmacia.69.e77021
Molecular docking and Dynamic simulations study for repurposing of multitarget Coumarins against SARS-CoV-2 main protease, papain like protease and RNA-Dependent RNA polymerase.
Supplementary Table of Mechanism Unravelling of Sodium-glucose Cotransporter-2 Inhibitors against Diabetic Nephropathy via Network Pharma-cology and Molecular Docking
<p>This is the supplementary tables of article named"Mechanism Unravelling of Sodium-glucose Cotransporter-2 Inhibitors against Diabetic Nephropathy via Network Pharmacology and Molecular Docking"</p>
Molecular Docking - AutoDock tool
<p>Docking studies will help in appropriate consideration of the protein’s active site and its interaction with the ligand. The interaction between a small molecule and a protein may result in inhibition of the protein. Molecular docking program Autodock 4.2 was used in this study.</p>
Raw Data for the Manuscript Titled "Can Current Molecular Docking Methods Accurately Predict RNA Inhibitors?"
<p>This is the additional data for the manuscript titled "Can Current Molecular Docking Methods Accurately Predict RNA Inhibitors?". These files include <strong>(a) </strong>The docked scores for scoring potential analysis, <strong>(b)</strong> The docked scores for ranking potential analysis, <strong>(c)</strong> The top five docked poses from each docking method (AutoDock Vina, HADDOCK, HDOCK and RLDOCK) and <strong>(d) </strong>The Molecular Dynamics (MD) simulation parameter and topology files used for pose refinment.</p>
Supplementary Data for "Molecular Docking, ADMET, Synthesis and Evaluation of New Indomethacin Hydrazide Derivatives as Antibacterial Agents"
<p>This supplementary data file contains additional information supporting the findings presented in the research article "<strong>Molecular Docking, ADMET, Synthesis and Evaluation of New Indomethacin Hydrazide Derivatives as Antibacterial Agents</strong>". The data includes:</p> <ul> <li>Infrared (IR) spectra of the synthesized compounds</li> <li>Proton nuclear magnetic resonance (H NMR) spectra of the synthesized compounds</li> <li>Minimum inhibitory concentration (MIC) and zone of inhibition (ZOI) data for the synthesized compounds against tested microorganisms</li> </ul>
Molecular dynamics simulations of 20 complexes from the Protein-Protein Docking Benchmark
<p>We selected 20 complexes from the Protein-Protein Docking Benchmark 5.0 dataset based on structure resolution and parameterization difficulty. For each complex, we conducted a standard 1 µs-long molecular dynamics (MD) simulation in the NPT ensemble (at 1 atm and 300 K, following a 2 ns NVT equilibration) for the bound receptor, unbound receptor, bound ligand and unbound ligand. We set up all systems using Amber ff14SB<sup> </sup>and its recommended TIP3P water model, running MD simulations with Amber 16. For the 80 (single chain structure) MD, we sampled 500 frames for each simulation and computed the average prediction confidence.</p>
Molecular dynamics simulation data of the manuscript "KnowVolution of an efficient polyamidase through molecular dynamics simulations of incrementally docked oligomeric substrates"
<p>This repository provides the simulation data as well as the input and parameters files to reproduce our findings.</p> <p><strong>Acknowledgments</strong></p> <p>The authors gratefully acknowledge the computing time provided by RWTH Aachen University. Computations were performed with computing resources granted by RWTH Aachen University under project rwth1584.</p>
Dataset for "Advances in Docking Protocols for PPIs: Insights from AlphaFold2 and Molecular Dynamics Refinement"
<p>Dataset files used in 'Advances in Docking Protocols for PPIs: Insights from AlphaFold2 and Molecular Dynamics Refinement' (https://github.com/SysBioUAB/docking_benchmark)</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.