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27 results for “Contact map”
Noncanonical electromechanical coupling paths in cardiac hERG potassium channel (semi-binary contact maps)
<p>Matrices of the semi-binary contact maps of the following open and closed systems: WT, A527L, A614G, L524R, L529H, L532H, T425L, T618L, W563L.</p> <p>The residue numbering is not the official one because the first residues (397) of hERG (PAS domain) were not included in our simulations so that each subunit comprizes 466 residues. Moreover, the four subunits were numbered consecutively. The official numbering of a residue can be easily recovered. The general rule is:</p> <p>official residue - 397 = our residue</p> <p>For example, the official T425 corresponds to T28 in the first subunit (425-397), T494 in the second subunit (425-397+466), T960 in the third subunit (425-397+466+466), and T1426 in the fourth subunit (425-397+466+466+466).</p>
All atom simulations snapshots and contact maps analysis scripts for SARS-CoV-2002 and SARS-CoV-2 spike proteins with and without ACE2 enzyme
<p><strong>The dataset contains a total of 40 snapshots of the four trajectories (10 snapshots each system = two per replica x 5 replicas/system):</strong></p> <ol> <li>SARS-CoV-2002 spike protein without ACE2</li> <li>SARS-CoV-2 spike protein without ACE2</li> <li>SARS-CoV-2002 spike protein with ACE2</li> <li>SARS-CoV-2 spike protein with ACE2</li> </ol> <p>Molecular dynamics simulation trajectories (320ns each) have been performed using the Amber ff14SB force field running with the Amber18 package at the the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Under the following simulation methodology:</p> <p><em>All-atom simulations were carried out with Amber18 (<a href="https://slack-redir.net/link?url=http%3A%2F%2Fambermd.org">ambermd.org</a>), and system components (protein, ions, water) were modeled with the included FF14SB and TIP3P parameter sets. Energy minimization used CPU pmemd, while later simulation stages used GPU pmemd. CoV2 and CoV1 systems with one RBD up (with/without ACE2) were solvated in 12 angstrom water shells. Cysteine residues identified in the initial models as having a disulfide bond (DB) were bonded using tLeap. All simulations used 0.150 M NaCl. Hydrogen mass repartitioning was applied only to the protein to enable a 4 fs timestep (<a href="https://slack-redir.net/link?url=https%3A%2F%2Fpubs.acs.org%2Fdoi%2Fabs%2F10.1021%2Fct5010406">https://pubs.acs.org/doi/abs/10.1021/ct5010406</a>). The SHAKE algorithm was applied to hydrogens, and a real-space cutoff of 8 angstroms was used. Periodic boundary conditions were applied and PME was used for long-range electrostatics. Minimization was by steepest descent (2000 steps) followed by conjugate gradient (3000 steps). Heating used two stages: (1) NVT heating from 0 K to 100 K (50 ps), and (2) NPT heating from 100 K to 300 K (100 ps). Restraints of 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> were applied during minimization and heating to C-alpha atoms. During 6 ns of equilibration at 300 K C-alpha restraints were gradually reduced from 10 kcal mol<sup>-1</sup> angstrom<sup>-2</sup> to 0.1 kcal mol<sup>-1</sup> angstrom<sup>-2</sup>. Finally, restraints were released and 320 ns unrestrained production simulations were carried out for CoV2 and CoV1 systems. Production simulations began from the final equilibrated snapshots, and five copies of each system were simulated. As unrestrained systems can freely rotate we monitored simulations for any close contacts and found that in one copy of the CoV1 simulation without ACE2 and one RBD up that a few contacts close to 8 angstrom occur near the end of the 320 ns between the RBD and a different subdomain of the spike complex in a periodic image. However this did not influence analyzed structural properties which is verified by comparing results across simulations. The Monte Carlo barostat was used to maintain pressure (1 atm), and the Langevin thermostat was used to maintain 300 K temperature (collision frequency 1 ps<sup>-1</sup>), as implemented in Amber18. In aggregate, nearly 7 microseconds of simulation of systems ranging from 396,147 to 879,100 atoms was carried out for this work.</em><br> For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).</p> <p><strong>Regarding the contact map analysis scripts (contactMaps_Analysis.tar.gz), they contain the following workflow:</strong></p> <p>contactmap --> source files from contact_map executable<br> process_nc.sh --> convert raw data from all-atom simulation to numbered PDB files and get the contact maps<br> frequency.lua --> read a set of PDB files and output the frequency count for each contact<br> consensus.fasta --> align sequence of Covid19 and SARS from Chimera<br> consensus.lua --> read data previously generated and compute the frequency per residue, among other things.<br> consensus.sh --> input information to consensus.lua<br> consensus.gp --> gnuplot script to plot figures</p> <p>This dataset and the code is part of tripartite collaboration between:</p> <ul> <li>The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)</li> <li>Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).</li> <li>Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).</li> </ul>
Snapshots, frequency contact maps analysis, Poisson Boltzmann calculations, and data scripts for characterization of structural and energetic differences between conformations of the SARS-CoV-2 spike protein
<p><strong>Molecular dynamics simulation</strong> trajectories, which have been performed using the Amber ff14SB force field running with the Amber18 package at the NSF-funded (OAC-1826915, OAC-1828163) ELSA high performance computing cluster at The College of New Jersey. Simulation methodology and further details are described in [1] and [2]. For further details on the trajectories, please contact Joseph Baker (bakerj@tcnj.edu).</p> <p>The <strong>Poisson Boltzmann </strong>energy calculations have been achieved by using the input_files.tar.xz found here and solving the Poisson Boltzmann equation with pygbe. A more detailed example and tutorial can be found at [4]. For further details contact Horacio V Guzman.</p> <p><strong>The dataset contains </strong></p> <ul> <li><strong>A total of 30 snapshots of the three trajectories (10 snapshots each system = two per replica x 5 replicas/system):</strong></li> </ul> <ol> <li>SARS-CoV-2002 spike protein with three RBD in the down positions: "COV2-DDD/PDB/" .</li> <li>SARS-CoV-2002 spike protein with one RBD in the up and two RBD in the down positions: "COV2-UDD/PDB/".</li> <li>SARS-CoV-2002 spike protein with two RBD in the up and one RBD in the down positions: "COV2-DUU/PDB/".</li> </ol> <ul> <li><strong>Input files for Poisson-Boltzmann analysis</strong>:</li> </ul> <ol> <li>PoissonBoltzmann/input_files.tar.xz</li> </ol> <ul> <li><strong>Data for the frequency contact map and processing scripts</strong>:</li> </ul> <ol> <li>cov2-ddd.pdb, cov2-udd.pdb, cov2-duu.pdb reference PDB files.</li> <li>Contact maps [3] at "COV2-DDD/CONTACT_MAP/", "COV2-UDD/CONTACT_MAP/", "COV2-DUU/CONTACT_MAP/".</li> <li>frequency.lua: get frequency of contacts from a set of contacts map files.</li> <li>diff_frequency.lua: get differential frequency of contacts from a set of frequency files.</li> <li>Frequency of contacts listed in frequency.data files at "COV2-DDD/", "COV2-UDD/" and "COV2-DUU/" directories.</li> </ol> <p>Read the "INFO" files for further informations.</p> <p>This dataset and the code is part of a collaboration between:</p> <ul> <li>The Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland (supported by the National Science Centre, Poland, under grant No. 2017/26/D/NZ1/0046)</li> <li>Department of Chemistry, The College of New Jersey, New Jersey, United States (supported by National Science Foundation under grant numbers OAC-1826915 and OAC-1828163).</li> <li>Jozef Stefan Institute, Ljubljana, Slovenia (supported by the Slovenian Research Agency (Funding No. P1-0055)).</li> <li>School of engineering in bioinformatics, University of Talca, Talca, Chile.</li> </ul> <p>[1] Rodrigo A. Moreira, Mateusz Chwastyk, Joseph L. Baker, Horacio V Guzman, & Adolfo B. Poma. (2020). All-atom simulations snapshots and contact maps analysis scripts for SARS-CoV-2002 and SARS-CoV-2 spike proteins with and without ACE2 enzyme (Version 0.1) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3817447</p> <p>[2] Chad W. Hopkins, Scott Le Grand, Ross C. Walker, and Adrian E. Roitberg. Long-Time-Step Molecular Dynamics through Hydrogen Mass Repartitioning. Journal of Chemical Theory and Computation 2015 11 (4), 1864-1874. http://doi.org/10.1021/ct5010406</p> <p>[3] Rodrigo A. Moreira, Mateusz Chwastyk, Joseph L. Baker, Horacio V Guzman, & Adolfo B. Poma. Quantitative determination of mechanical stability in the novel coronavirus spike protein. Nanoscale, 2020,12, 16409-16413. <a href="https://doi.org/10.1039/D0NR03969A">https://doi.org/10.1039/D0NR03969A</a></p> <p>[4] https://github.com/pyF4all</p>
Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes
<p>ATAC-seq peaks are in narrowPeak format. RNA-seq results are organized according to cell type. The normalized RPKM is reported for each gene in GENCODE 19. All data was mapped to hg19.</p>
Twins: A deep learning method for replicate-based conformation contact map analysis.
GEO Series GSE233377. Mus musculus. 0 samples. Type: Third-party reanalysis; Other.
Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes
GEO Series GSE208602. Mus musculus. 20 samples. Type: Expression profiling by high throughput sequencing; Other.
Global mapping of RNA-chromatin contacts reveals a proximity-dominated connectivity model for ncRNA-gene interactions
GEO Series GSE240435. Homo sapiens. 22 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Cut-and-Run in situ factor profiling maps DNA binding and 3D contact sites at high resolution
GEO Series GSE84474. Saccharomyces cerevisiae; Homo sapiens. 126 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Genome wide mapping of polyadenylation sites in proliferating and contact-inhibited cells and cells with knockdown of cleavage and polyadenylation factors
GEO Series GSE117033. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes
GEO Series GSE113483. Homo sapiens. 39 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing; Other.
Global mapping of polyadenylation site use in proliferating and quiescent (contact-inhibited and serum-starved) cells
GEO Series GSE117337. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
ChromaFold predicts the 3D contact map from single-cell chromatin accessibility
GEO Series GSE246859. Homo sapiens; Mus musculus. 3 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing.
Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes [Hi-C]
GEO Series GSE208600. Mus musculus. 16 samples. Type: Other.
Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts
GEO Series GSE97131. Drosophila melanogaster. 5 samples. Type: Other.
A Compendium of Chromatin Contact Maps Reveal Spatially Active Regions in the Human Genome
GEO Series GSE87112. Mus musculus; Homo sapiens. 19 samples. Type: Other; Expression profiling by high throughput sequencing; Third-party reanalysis.
Genome-wide chromatin interaction maps of enhancer-promoter and promoter-promoter contacts in 5 leiomyoma (MED12 G44 mutant) and 5 matched normal myometrium (WT) patient tissue samples.
GEO Series GSE128234. Homo sapiens. 10 samples. Type: Other.
Feasibility of Contact Force Catheter Mapping and Ablation in Epicardial and Endocardial Ventricular Tachycardias
ClinicalTrials.gov study NCT01847378. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes [PCHiC]
GEO Series GSE113481. Homo sapiens. 12 samples. Type: Other.
Mapping cis-regulatory chromatin contacts in neural cells links neuropsychiatric disorder risk variants to target genes [RNA-Seq]
GEO Series GSE113482. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Hi-C contact map of the Jurkat T cell genome
GEO Series GSE122958. Homo sapiens. 2 samples. Type: Other.
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International Brain Laboratory public data
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OpenNeuro
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