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156 results for “molecular interactions”
Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations
<p>MD simulations used in the studies of the publication "<strong>Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations</strong>"</p>
Exploring the interaction of a curcumin azobioisostere with Abeta42 dimers using replica exchange molecular dynamics simulations
<p>Structural data and parameters relative to the evaluation of the interaction of an anti aggregating azobioisostere compound with the full-length Aβ42 peptide by replica-exchange molecular dynamics (REMD) simulations. Two different force fields (Amber and CHARMM) were used to simulate the azobioisostere-Abeta42 (AZ-Ab42) complex in a monomeric and dimeric assembly.</p> <p>A brief description of the shared output data is reported below:</p> <p><strong>1. Amber and CHARMM-adapted parameters for the simulated azobioisostere (AZ) compound.</strong></p> <p><strong>2. Modified version of the CHARMM36m FF - (CHARMM36mW)</strong></p> <p><strong>3. Starting (equilibrated) structures (first 5 T-replicas) for REMD on each of the following three systems (PDB): </strong></p> <ul> <li>Amber: AZ-Ab42 (monomeric ensemble): <strong>Repl.0 </strong>(315.0 K), <strong>Repl.1</strong> (316.7 K), <strong>Repl.2</strong> (318.4 K), <strong>Repl.3</strong> (320.1 K), <strong>Repl.4</strong> (321.8 K) </li> <li>Amber: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3</strong> (318.0 K), <strong>Repl.4</strong> (319.1 K) </li> <li>CHARMM: AZ-Ab42 (dimeric ensemble): <strong>Repl.0</strong> (315.0 K), <strong>Repl.1</strong> (316.0 K), <strong>Repl.2</strong> (317.0 K), <strong>Repl.3 </strong>(318.0 K), <strong>Repl.4</strong> (319.1 K)</li> </ul> <p><strong>4. Most populated clusters for the three simulated systems (PDB):</strong></p> <ul> <li>Amber AZ-Ab42 (monomeric ensemble): <strong>7</strong> clusters (<strong>Cl.0</strong>: 12.4%, <strong>Cl.1</strong>: 10.1%, <strong>Cl.2</strong>: 9.8%, <strong>Cl.3</strong>: 5.4%, <strong>Cl.4</strong>: 3.7%,<strong> Cl.5</strong>: 3.6%, <strong>Cl.6</strong>: 2.0%) </li> <li>Amber AZ-Ab42 (dimeric ensemble): <strong>5</strong> clusters (<strong>Cl.0</strong>: 7.1%, <strong>Cl.1</strong>: 4.3%, <strong>Cl.2</strong>: 3.5%,<strong> Cl.3</strong>: 3.2%, <strong>Cl.4</strong>: 2.4%) </li> <li>CHARMM: AZ-Ab42 (dimeric ensemble): <strong>3</strong> clusters (<strong>Cl.0</strong>: 4.7%, <strong>Cl.1</strong>: 4.6%, <strong>Cl.2</strong>: 2.5%) </li> </ul>
Interactive Molecular Dynamics Simulation Movie using MDsrv - BioGem
<p>The protein structure and molecular dynamics simulation trajectories used to make interactive movie using MDsrv and NGL Viewer.</p> <p>https://www.youtube.com/watch?v=m62lg6ZInAI</p>
Interaction of biomolecules with anatase, rutile and amorphous TiO2 surfaces: A molecular dynamics study / supplement
<ul> <li>S1 File - Short videos representing the interaction of the 6 different biomolecules (KGD, KRSR, LGD, LRSR, RGD and RSR) with the 3 different TiO<sub>2</sub> surface (anatase, amorphous and rutile).</li> <li>S2 File - A representative trajectory file of the LRSR peptide and amorphous TiO<sub>2</sub> surface MD simulation without the ions and water molecules.</li> <li>S3 File - Force-distance curve data for the binding energy calculations.</li> </ul>
Alliance of Genome Resources Molecular Interactions
<p>This file provides a set of annotations of molecular interactions for genes and gene products for human, rat, mouse, zebrafish, fruit fly, nematode, yeast, African and Western clawed frogs, and SARS-CoV-2. The file is in the <a href="https://github.com/HUPO-PSI/miTab/blob/master/PSI-MITAB27Format.md">PSI-MI TAB 2.7 format</a>, a tab-delimited format established by the <a href="http://www.psidev.info">HUPO Proteomics Standards Initiative</a> Molecular Interactions (PSI-MI) working group. The interaction data is sourced from Alliance members WormBase and FlyBase, as well as the <a href="http://www.imexconsortium.org">IMEx consortium</a> and the <a href="https://thebiogrid.org">BioGRID database</a>.</p> <p>The file contains molecular interaction annotations for the following organisms:</p> <ul> <li>Homo sapiens (human; NCBI:txid 9606)</li> <li>Caenorhabditis elegans (nematode; NCBI:txid 6239)</li> <li>Danio rerio (zebrafish;NCBI:txid 7955)</li> <li>Drosophila melanogaster (fruit fly; NCBI:txid 7227)</li> <li>Mus musculus (mouse; NCBI:txid10090)</li> <li>Rattus norvegicus (rat; NCBI:txid 10116)</li> <li>Saccharomyces cerevisiae (yeast; NCBI:txid 559292)</li> <li>Xenopus laevis (African clawed frog; NCBI:txid 8355)</li> <li>Xenopus tropicalis (Western clawed frog; NCBI:txid 8364)</li> <li>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; NCBI:txid2697049)</li> </ul>
Molecular modeling of Momordica cochinchinensis asparagine endopeptidase 2 and its interaction with MCoTI-II peptide
<p>Cyclotides are a large family of plant defense peptides, which display a cyclic backbone. The enzymes responsible for the backbone cyclization of these peptides are called asparagine endopeptidases, and the three-dimensional crystallographic structure of one of these cyclization enzyme has recently been described. The group of David Craik has recently discovered another cyclization enzyme, this time from the plant <em>Momordica cochinchinensis</em>, which is selective for cyclotides belonging to the trypsin inhibitor cyclotide family I have carried out molecular dynamics simulations of this new enzyme in an apo state and in an intermediate state when covalently linked with a substrate peptide. This dataset provides the necessary files to reproduce these molecular dynamics simulations carried out with the software pmemd from the Amber 18 simulation package.</p>
pLMMoRF: A web server that accurately predicts membrane-interacting molecular recognition features by employing a protein language model
<p>pLMMMoRF predictor scrips and MemMoRF prediction of the human proteome.</p>
Data for the paper titled 'Dynamic Molecular Atlas for Cardiac Fibrosis at Single-Cell and Spatial Resolution: CD248 in Orchestrating Fibroblast-Immune Interaction'
<p>The deposited data were employed to generate the figures concerning single-cell RNA (scRNA) and spatial transcriptomic analyses in the paper titled 'Dynamic Molecular Atlas for Cardiac Fibrosis at Single-Cell and Spatial Resolution: CD248 in Orchestrating Fibroblast-Immune Interaction'.</p>
Insights into the DNA and RNA Interactions of Human Topoisomerase III Beta Using Molecular Dynamics Simulations
<p>hTOP3 simulations for both covalently and non-covalently bound DNA and RNA substrates. Simulation times = 300ns, with 1/ns per frame = 300 frames each.</p>
All-atom simulations elucidate the molecular mechanism underlying RNA-membrane interactions
<p>Topology files and frames extracted from the minimum of the free energy profile F(d_z) (or F(d_min) for single-stranded RNAs), within 2.5kBT. These files can be used to reproduce the hydrogen bond analyses in the manuscript.</p> <p>Scripts which were used to extract hydrogen bond information are available on <a href="https://github.com/salvatoredimarco/rna-membrane">https://github.com/salvatoredimarco/rna-membrane</a></p> <p><strong>Systems:</strong></p> <p>4xN: nucleosides</p> <p>4xN2: dinucleotides</p> <p>4xN3: trinucleotides</p> <p>4xN_OPC: nucleosides simulated with OPC water model. Energy threshold is here 1.0*kBT, because of weaker binding.</p> <p>1xGA, 1xGU, 1xGC, 1xCU</p> <p>1xGGC, 1xGCG</p> <p>1xquadruplex: G-quadruplex</p> <p>1xstrand: 19-mer RNA strand</p> <p>1xhairpin: 16-mer folded hairpin</p> <p>1x16mer_elong: 16-mer unfolded, restrained</p> <p>2x16mer_loose1/2: 16-mer unfolded, unrestrained</p>
GeoMx DSP dataset of "Integrated multi-omics reveals cellular and molecular interactions governing the invasive niche of basal cell carcinoma"
<p>This data set is linked to the paper "Integrated multi-omics reveals cellular and molecular interactions governing the invasive niche of basal cell carcinoma". It contains datasets and images from GeoMx DSP analysis. </p>
Interaction of Surface Glycoprotein of SARS-CoV-2 Variants of Concern with Potential Drug Candidates: A Molecular Docking Study
<p>This dataset contains additional docking images of SARS-CoV-2 Variants of Concern with drugs under study. It also contains a spreadsheet containing binding residues with different types of bonds. Further it includes the raw spike protein sequences, 3D model of spike proteins of VOCs (variant of concern) and potential drugs used in this study. </p>
Donors, Acceptors and a Bit of Aromatics: Electronic Interactions of Molecular Adsorbates on hBN and MoS2 Monolayers
<p>The design of low-dimensional organic-inorganic hybrid interfaces for the next generation of optoelectronic applications requires an in-depth understanding of the microscopic mechanisms ruling the electronic interactions in these systems. In this work, we present a first-principles study based on density-functional theory inspecting the structural, energetic, and electronic properties of five molecular donors and acceptors adsorbed on freestanding hexagonal boron nitride (hBN) and molibdenum disulfide (MoS2) monolayers. All considered heterostructures are stable, due to the crucial contribution of dispersion interactions, which are maximed by the overall flat arrangement of the physisorbed molecules on both substrates. The level alignment of the hybrid systems depends on the characteristics of the constituents. On hBN, both type-I and type-II heterostructures may form, depending on the relative energies of the frontier orbitals with respect to the vacuum level. On the other hand, all MoS2-based hybrid systems exhibit a type-II level alignment, with the molecular frontier orbitals positioned across the energy gap of the semiconductor. The electronic structure of the hybrid materials is further determined by the formation of interfacial dipole moments and by the wave-function hybridization between the organic and inorganic constituents. These results provide important indications for the design of novel low-dimensional hybrid materials with suitable characteristics for optoelectronics.</p>
Data supporting: "Interaction of MRI Contrast Agent [Gd(DOTA)]− with Lipid Membranes: A Molecular Dynamics Study"
Open the record for dataset details and reuse information.
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>
Molecular dynamics simulations of the interaction of mutant human CYP2J2 (R111A) with arachidonic acid (POSES 1-3)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the R111A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p> <p>005.md : Production stage</p> <p>006.analysis : Basic energy graphs</p> <p>007.cpptraj: Contains only the file strip.md.nc (Amber trajectories stripped of water in netCDF format)</p>
Molecular dynamics simulations of the interaction of the double mutant human CYP2J2 (R117A and R111A) with arachidonic acid (POSES 4-6)
<p><strong>Description of files in this dataset:</strong></p> <p><strong>MD_mutR111A_R117A_CYP2J2_AA_StateX_repeatY.zip</strong> : Series of zipped directories for molecular dynamics simulations of arachidonic acid in the active site of the double R111A + R117A mutant CYP2J2. X is the docking pose number that constitutes the starting point of the simulation (the 6 lowest-energy poses from docking were selected as the starting points of the simulations - this dataset is State(pose) 1). Y is the repeat (each simulation was repeated 3 times, hence there are 3 repeats per pose). </p> <p>Each directory contains the following sub-directories:</p> <p>001.leap : Amber parameter and coordinate files; PDBs; ligands; leap commands</p> <p>002.min : Minimisation stage</p> <p>003.heat : Heating stage</p> <p>004.equil: Equilibration stage</p>
Developing and Benchmarking Sulfate and Sulfamate Force Field Parameters via Ab Initio Molecular Dynamics Simulations to Accurately Model Glycosaminoglycan Electrostatic Interactions
<p>To cite and for more details: Riopedre-Fernandez et al. <em>J. Chem. Inf. Model.</em> <strong>2024</strong>, 64 (18), 7122–7134. DOI: <a href="https://doi.org/10.1021/acs.jcim.4c00981">https://doi.org/10.1021/acs.jcim.4c00981</a></p> <p>The dataset includes molecular dynamics simulations of sulfated saccharides and their sulfated analogs in the presence of calcium cations in aqueous solution. Several force field parameter sets were compared (CHARMM36, GLYCAM06, AMOEBA, Drude) and new have been developed (prosECCo75 and GLYCAM-ECC75).</p> <p>The uploaded files contain the following simulation input files or/and simulation trajectories:</p> <p>1) Sulfated_Molecules_Umbrella_Sampling_AIMD: Umbrella sampling ab initio molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>2) Sulfated_Molecules_Umbrella_Sampling_FFMD: Umbrella sampling force field molecular dynamics simulations of calcium-methylsufate and calcium N-methylsulfamate ion pairs in water.</p> <p>3) Sulfated_Molecules_AWH_FFMD: Accelerated weight histogram force field molecular dynamics simulations of calcium interacting with both methylsufate and N-methylsulfamate in water.</p> <p>4) Disaccharides_FFMD: Unbiased force field molecular dynamics simulations of calcium-sulfated disaccharide aqueous solutions.</p> <p>UPD. Version 2.0 has updated one of the disaccharide-containing simulations (GLYCAM06, N-sulfation) due to incorrect calcium LJ parameters in the original upload.</p>
Interactive effects of ZnO nanoparticles and temperature on molecular and cellular stress responses of the blue mussel Mytilus edulis
<p>We investigate the molecular and cellular stress responses of tissues (gills and digestive glands) in the mussels <em>Mytilus edulis </em>exposed for 21 days to either ambient (10 °C in winter and 15 °C in summer) or elevated (by 5 °C) temperature combined with different concentrations (0, 10, 100 µg l<sup>-1</sup>) of ZnO nanoparticles or dissolved zinc. In this data set, we used a biomarker-based approach focusing on oxidative stress indicators ( lipid peroxidation and protein carbonyls) and transcription pattern of marker genes in the pathways related to cell survival and proliferation (caspase 3, Bcl-2, p53, p38 and JNK) and inflammation (COX, NF-κB, and TGF-β) of <em>M. edulis</em>. </p>
Data for: Optimal inference of molecular interaction dynamics in FRET microscopy
<p>Intensity-based time-lapse fluorescence resonance energy transfer (FRET) microscopy has been a major tool for investigating cellular processes, converting otherwise unobservable molecular interactions into fluorescence time series. However, inferring the molecular interaction dynamics from the observables remains a challenging inverse problem, particularly when measurement noise and photobleaching are nonnegligible—a common situation in single-cell analysis. The conventional approach is to process the time-series data algebraically, but such methods inevitably accumulate the measurement noise and reduce the signal-to-noise ratio (SNR), limiting the scope of FRET microscopy. Here, we introduce an alternative probabilistic approach, B-FRET, generally applicable to standard 3-cube FRET-imaging data. Based on filtering theory, B-FRET implements a statistically optimal way to infer molecular interactions and thus drastically improves the SNR. We validate B-FRET using simulated data and then apply it to real data, including the notoriously noisy in vivo FRET time series from individual bacterial cells to reveal signaling dynamics otherwise hidden in the noise.</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.