Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
691
datasets available to search
ShareScore release 0.7.1
Dataset results
691 results for “Molecular dynamics”
Figure 1 from: Musfiroh I, Megawati G, Diah Herawati DM, Nama Putra O, Sylvia Nurrasjid E (2023) Molecular dynamic of omega-3 compounds as an anti-obesity agent into GPR-120 receptor. Pharmacia 70(4): 1541-1548. https://doi.org/10.3897/pharmacia.70.e115501
Figure 1 A. Neurotensin receptor (4GRV) and B. Overlay of the docked pose of Neurotensin 8–13 with the co-crystallized ligand 4GRV.
Figure 4 from: Musfiroh I, Megawati G, Diah Herawati DM, Nama Putra O, Sylvia Nurrasjid E (2023) Molecular dynamic of omega-3 compounds as an anti-obesity agent into GPR-120 receptor. Pharmacia 70(4): 1541-1548. https://doi.org/10.3897/pharmacia.70.e115501
Figure 4 RMSD (a) and RMSF (b) value of docosahexaenoic acid (blue), eicosapentaenoic acid (maroon), and heneicosapentaenoic acid (green).
Figure 5 from: Musfiroh I, Megawati G, Diah Herawati DM, Nama Putra O, Sylvia Nurrasjid E (2023) Molecular dynamic of omega-3 compounds as an anti-obesity agent into GPR-120 receptor. Pharmacia 70(4): 1541-1548. https://doi.org/10.3897/pharmacia.70.e115501
Figure 5 SASA plot of docosahexaenoic acid (blue), eicosapentaenoic acid (maroon), and heneicosapentaenoic acid (green).
Dynamic profiling and binding affinity prediction of NBTI antibacte-rials against DNA gyrase enzyme by multidimensional machine learning and molecular dynamics simulations
<p>The chemical libraries used in this study comprised of 199 and 133 structurally diverse novel bacterial topoisomerase inhibitors (<em>alias</em> NBTIs), with experimentally determined <em>in vitro</em> antibacterial potencies against <em>Staphylococcus aureus</em> DNA gyrase (IC<sub>50</sub>=0.007-50 µM) and <em>Escherichia coli</em> DNA gyrase (IC<sub>50</sub>=0.020-100 µM), respectively (named as NBTI<em><sub>SA</sub></em> and NBTI<em><sub>EC</sub></em>), were compiled from the literature as *.sdf file format. The chemical structures comprising both NBTI libraries were initially sketched by using ChemDraw Professional 20.1.1 suite and subsequently energetically minimized utilizing Discovery Studio’s integrated Merck Molecular Force Field (MMFF) module. Moreover 4D ligands ensembles of both libraries ready to be used for multidimensional QSAR modeling are available, as well.</p>
Figure 4 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 4 Number of HBs and RMSD between N1-H274Y-oseltamivir protein (PDB ID: 3CL0) with three flavones 428, 581, and 864 (Fig. A–C, respectively) during dynamic simulation time 500 ns.
Figure 5 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 5 The proposed semi-synthesis of compound 864. (i) Column chromatography (70% EtOH: 18.64 mg.g−1) (ii) ClCH2COCl, K2CO3, DCM, rt, 8–24h; (iii) K2CO3/KI, acetone, reflux, 25–30 h.
Figure 2 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 2 2D interaction diagrams and 3D molecular docking of N1-H274Y-oseltamivir protein (PDB ID: 3CL0) with four flavones 428, 581, 864, and 948 (A–D, respectively) and two flavonols 162 and 218, (E, F, respectively).
Figure 3 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 3 3D molecular docking of bifunctional N inhibitor (compound 864) binding into the sialic acid binding cavity and the 430-cavity through the unique arginine triad Arg118-Arg292-Arg371 of N1-H274Y-oseltamivir protein (PDB ID: 3CL0).
Figure 1 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Figure 1 Procedure of molecular docking screening and molecular dynamics of flavones and flavonols from COCONUT database.
Supplementary material 1 from: Ha T-K-Q, Pham-Khanh N-H, Nguyen T-K (2024) Molecular docking screening, dynamics simulations, ADMET, and semi-synthesis prediction of flavones and flavonols from the COCONUT database as potent bifunctional neuraminidase inhibitors. Pharmacia 71: 1-10. https://doi.org/10.3897/pharmacia.71.e114967
Supporting data
Structuran and NMR Characterization of Hexamer and Octamer Foldamers in Chloroform and Water: A Molecular Dynamics and Quantum Mechanics Approach
Open the record for dataset details and reuse information.
Exploring Conformational Landscapes and Binding Mechanisms of Convergent Evolition for the SARS-CoV-2 Spike Omicron Variant Complexes with the ACE2 Receptor Using AlphaFold2-Based Structural Ensembles and Molecular Dynamics Simulations
Open the record for dataset details and reuse information.
Multiresolution molecular dynamics simulations reveal the interplay between conformational variability and functional interactions in membrane-bound cytochrome 2B4
<p>This dataset contains coordinate files, scripts and input parameters to run and analyse molecular dynamics simulations of membrane bound CYP 2B4.</p> <p> </p> <p>The associated study is described in: </p> <p>data - containes input data & last simulation frames for all of the described MD simulations and analyses described in the manuscript</p> <p>Structures_used_for_figures - contains .pdb and .pse files of all protein structures depicted in the manuscript</p>
source data for "Dissecting the role of hydroxyl moiety at C14 in (+)-opioid based TLR4 antagonists via wet-lab experiments and molecular dynamics simulations"
Open the record for dataset details and reuse information.
In silico molecular docking and molecular dynamic simulation of agarwood compounds with molecular targets of Alzheimer's disease
<p>We added Supplementary Figure 8a.</p>
Alchemical Free Energy Estimators and Molecular Dynamics Engines: Accuracy, Precision and Reproducibility - Dataset
<p>This zip contains all input structures for paper the: Alchemical Free<br> Energy Estimators and Molecular Dynamics<br> Engines: Accuracy, Precision and Reproducibility</p> <p>Authors: Alexander D. Wade, Agastya P. Bhati, Shunzhou Wan, Peter V.Coveney</p> <p>The structures of the folders are protein/ligand_transformation/alchemical_leg/input/files</p> <p>The ligand transformation are derived from previous work by wang et al. (https://pubs.acs.org/doi/10.1021/ja512751q)</p> <p>There are two files for the solvent alchemical leg: complex.pdb and complex.prmtop</p> <p>complex.pdb is structure file that also denotes the alchemical atoms in the pdb beta column. complex.prmtop is an AMBER parameter/topology file</p> <p>For the complex alchemical leg there is an additional file constraints.pdb that contains the constraint information in the pdb beta column.</p> <p>These files can be used with TIES_MD (https://ucl-ccs.github.io/TIES_MD/) or other molecular dynamics engines that take AMBER input.</p>
Figure 7 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
Figure 7 2D poses of (A) Mesuol; (B) Isomesuol; (C) suksdorphin; (D) Calanolide; docked into the active site of SARS-CoV-2 main protease (PDB: 5rh4).
Figure 6 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
Figure 6 (A) surface map (B) 2D poses showing ligand interactions of Coumermycin docked into the active site of SARS-CoV-2 main protease (PDB: 5rh4).
Figure 12 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
Figure 12 The time frame of evolution against the radius of gyration (Rg) of Coumermycin complexes with SARS-CoV-2 (A) Mpro (B) PLpro (C) RdRp, during 50 ns MD simulation.
Figure 11 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
Figure 11 The RMSF plot of Coumermycin complex with SARS-CoV-2 (A) Mpro (B) PLpro (C) RdRp, at 50 ns simulation.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.