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543 results for “RNA dynamics”
How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study
<p>The data necessary to independently reproduce the MD simulations and the first part of the simulation trajectories reported in the paper "<strong>How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study</strong>", by Lemmens et al.</p> <p>Due to Zenodo data deposition limits, every 10th frame of the MD simulation trajectories is included. Due to Zenodo deposition limits, MD trajectory files for this paper are also available at 10.5281/zenodo.14260246.</p>
Molecular dynamics simulations of an Ago2-RNA complex in different force fields
<p>This set of simulations contains 2us of Ago2-RNA complex in Amber ff14SB + OL3, ff19SB + OL3 and Desmond OPLS4 force fields. The polarizable force field AMOEBA has two simulation sets of 10*10ns and 2*100ns. The trajectories have been wrapped in the periodic box, centered around the protein atoms and the water molecules have been stripped out to conserve space using cpptraj. The trajectories are presented in Gromacs xtc-format which can be opened with the corresponding pdb file in multiple software tools such as VMD, PyMol or CaverAnalyst. The simulations are based on the crystal structure PDB ID 4W5O, where the missing loops were modeled using the Schrödinger Suite and missing nucleotides added manually. </p>
Data for: Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes
<p><span>Proper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis in <em>Drosophila</em> starting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study (Li et al., 2022). With over 44,000 nuclei and 6,000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers, <em>in situ</em> hybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for function <em>in vivo</em>.</span></p>
Data for: Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes
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Raw data for the manuscript under the title "Mitochondrial RNA granules are fluid condensates, positioned by membrane dynamics".
<p><strong>This is the data-repository</strong> to contain all relevant raw-data used and referred to in the manuscript entitled:<br> "Mitochondrial RNA granules are fluid condensates, positioned by membrane dynamics"<br> [manuscript under revision, and thus not citable as published article]</p> <p>The repository is structured analogous to the manuscript. Find a more detailed description in the README.</p>
Supporting data for "Dynamics of RNA polymerase II and elongation factor Spt4/5 recruitment during activator-dependent transcription"
<p>Supporting data for</p> <p><strong>Dynamics of RNA polymerase II and elongation factor Spt4/5 recruitment</strong></p> <p><strong>during activator-dependent transcription </strong></p> <p>Grace A. Rosen<sup>a,1</sup>, Inwha Baek<sup>b,1</sup>, Larry J. Friedman<sup>a</sup>, Yoo Jin Joo<sup>b</sup>, Stephen Buratowski<sup>b,2</sup>, Jeff Gelles<sup>a,2</sup></p> <p><sup>a</sup>Department of Biochemistry, Brandeis University, Waltham, Massachusetts 02454, USA.</p> <p><sup>b</sup>Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, Massachusetts 02115, USA.</p> <p><sup>1</sup>Equal contributions</p> <p><sup>2</sup>Corresponding authors: <a href="mailto:steveb@hms.harvard.edu">steveb@hms.harvard.edu</a>; +1 (617) 432-0696 (S.B.) and <a href="mailto:gelles@brandeis.edu">gelles@brandeis.edu</a>; +1 (781) 736-2377 (J.G.)</p> <p>See <strong>Source data index.pdf</strong> for description of files.</p>
How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study - Second part
<p>Second part of the data deposition for the paper "<strong>How Binding Site Flexibility Promotes RNA Scanning in TbRGG2 RRM: A Molecular Dynamics Simulation Study</strong>", by Lemmens et al. Part one is availible via <a href="https://doi.org/10.5281/zenodo.13929049">10.5281/zenodo.13929049</a></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>
Raw data for "Condensates in RNA repeat sequences are heterogeneously organized and exhibit reptation dynamics"
<p>This is the raw data for the paper "Condensates in RNA repeat sequences are heterogeneously organized and exhibit reptation dynamics".</p> <p>There are 5 directories. Three correspond to the CAG repeats with different length (20, 31 and 47). The "scramble47" directory stores data for the scrambled sequence. "Electrostatics" has data for the electrostatics run (see details in Extended Data Fig. 9).</p> <p>Each directory of CAG contains multiple sub-directories corresponding to different concentrations.</p> <p> </p>
Molecular dynamics simulations with grand-canonical reweighting suggest cooperativity effects in RNA structure probing experiments
<p>Molecular dynamics simulations of an RNA GAAA tetraloop interacting with SHAPE reagent 1-Methyl-7-nitroisatoic anhydride (1m7) in different numer of copies (1 to 19). See also https://arxiv.org/abs/2209.12640 and https://github.com/bussilab/paper-shapemd.</p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.
<p>This repository contains the representative structures of the 20 clusters obtained, which constitute the “MD-adapted structure ensemble”: i.e., sets of atomic coordinates that capture the flexibility and the pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n7x.pdb?versionId=310a80f6-aa64-445d-8641-45faf9f1ac03">ensemble_MD_2n7x.pdb</a>) and Rbfox/pre-miR20b (<a href="https://zenodo.org/api/files/ee12021f-4398-465a-9ff6-ddb7be32765f/ensemble_MD_2n82.pdb?versionId=82d7afcb-8a92-4daa-8150-789dbd7b2474">ensemble_MD_2n82.pdb</a>) conformers suggested by MD simulations while still retaining the highest possible level of agreement with the primary NMR data.</p>
Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study.-PART 8
<p>Simulations of the miR20b RNA with the Case vdW modification to amber force field and OPC water molecules.</p>
Molecular dynamics simulations of RNA Pol I closed complex in WT and with modifications to DNA base pairs -27 and -28
<p><span>The starting structure for the modelling was cryo-EM based structure of <em>S. cerevisiae</em> pre-initiation complex, showing Pol I, RRN3 and CF bound on a rDNA promoter at 2.90 Å resolution. This structure (‘RNA Polymerase I closed conformation 2’; accession code: 6RQL) was downloaded from the PDB database and prepared using the Protein Preparation Workflow of Maestro with default settings. This included filling in missing sidechains, optimizing hydrogen bonds and protonation using PROPKA at pH 7.4, deleting water molecules >5Å from the heteroatoms and a short energy minimization using OPLS4 force field</span><span>. The initial structures for the complexes with DNA mutations were constructed from this pre-processed structure by manually mutating the base pairs at position -28 or -27 of the rDNA promoter from C</span><span>·</span><span>G to A</span><span>·</span><span>T (</span><span>tDNA·ntDNA)</span><span> and from A</span><span>·</span><span>T to C</span><span>·</span><span>G, respectively. </span><span></span><span>MD simulations (3*80 ns/system) were conducted with Desmond using default parameters from Schrödinger Suite version 2024-1 on the CSC (IT Center for Science, Finland) supercomputer Puhti. </span></p>
Apical Localization of RNA Polymerases Modulate Transcription Dynamics and Supercoiling Domains Revealed by Cryo-ET
<p>Supplementary materials include all particle raw tilts, 3D reconstructions, models, FSC evaluations, statistical data analyses, gel images, and oxDNA molecular dynamics simulations for the manuscript titled "<strong>Apical Localization of RNA Polymerases Modulate Transcription Dynamics and Supercoiling Domains Revealed by Cryo-ET</strong>".</p>
A histone methyltransferase-independent function of PRC2 controls small RNA dynamics during programmed DNA elimination in Paramecium
<p><span lang="EN-US">To limit transposable element (TE) mobilization, most eukaryotes have evolved small RNAs to silence TE activity via homology-dependent mechanisms. Small RNAs, 20-30 nucleotides in length, bind to PIWI proteins and guide them to nascent transcripts by sequence complementarity, triggering the recruitment of histone methyltransferase enzymes on chromatin to repress the transcriptional activity of TEs and other repeats. In<span> the ciliate <em>Paramecium tetraurelia</em>,</span> 25-nt scnRNAs corresponding to TEs recruit Polycomb Repressive Complex 2 (PRC2), and trigger their elimination during the formation of the somatic nucleus. Here, we sequenced sRNAs during the entire sexual cycle with unprecedented resolution. Our data confirmed that scnRNAs are produced from the entire germline genome, from TEs and non-TE sequences, during meiosis. Non-TE scnRNAs are selectively degraded, which results in the specific selection of TE-scnRNAs. We demonstrate that PRC2 is essential for the selective degradation of non-TE-scnRNAs, independently of its histone methyltransferase activity. We further show that the PRC2 cofactor Rf4 mediates the physical interaction between the scnRNA-binding protein Ptiwi09 and the zinc finger protein Gtsf1, pointing to an architectural role of PRC2 in scnRNA degradation.</span></p>
The dynamics of protein-RNA interfaces using all-atom molecular dynamics simulations
<p>We investigated to characterize the dynamics of protein-RNA complexes and their interfaces at molecular level by performing a more systematic analysis. To get insights on the dynamics of protein-RNA complexes, all-atom MD simulations were generated for the manuscript "The dynamics of protein-RNA interfaces using all-atom molecular dynamics simulations". Nine protein-RNA complexes are studied in this work: 1ASY (an aspartyl-tRNA synthase/tRNA), 1JBS (a ribotoxin restrictocin/SRD RNA), 1MMS (a ribosomal protein L11/23S), 1OOA (a nuclear factor NF-kappaB p105 subunit/RNA aptamer), 1RKJ (a nucleolin/pre-rRNA), 2R8S (a FAB/P4-P6 RNA ribozyme domain), 2VPL (a 50S ribosomal protein/mRNA), 2ZM5 (a tRNA delta(2)-isopentenylpyrophosphate transferase/tRNA), 3IEV (a GTP-binding protein era/3' end of 16S rRNA). </p><p>Each folder for a complex is organised as followed:</p><ul><li>in <strong>complex</strong> there are the dry MD simulations for the complex protein-RNA with the starting structure</li><li>in <strong>protein</strong> there are the dry MD simulations for the unbound protein with the starting structure</li><li>in <strong>rna</strong> there are the dry MD simulations for the unbound RNA with the starting structure</li></ul><p>In each folder, all the trajectory files are named : <strong>md_(times of simulations).xtc</strong> and the starting structure called : <strong>start.gro</strong>.</p>
Structural dynamics of SARS-CoV-2 nucleocapsid protein induced by RNA binding
<p>This dataset contains files of the molecular dynamics simulations performed in "Structural dynamics of SARS-CoV-2 nucleocapsid protein induced by RNA binding" study. Further information in presented in README.md file and the abstract of the study is presented below:</p> <p>"The nucleocapsid (N) protein of the SARS-CoV-2 virus, the causal agent of COVID-19, is a multifunction phosphoprotein that plays critical roles in the virus life cycle, including transcription and packaging of the viral RNA. To play such diverse roles, the N protein has two globular RNA-binding modules, the N- (NTD) and C-terminal (CTD) domains, which are connected by an intrinsically disordered region. Despite the wealth of structural data available for the isolated NTD and CTD, how these domains are arranged in the full-length protein and how the oligomerization of N influences its RNA-binding activity remains largely unclear. Herein, using experimental data from electron microscopy and biochemical/biophysical techniques combined with molecular modeling and molecular dynamics simulations, we showed that, in the absence of RNA, the N protein formed structurally dynamic dimers, with the NTD and CTD arranged in extended conformations. However, in the presence of RNA, the N protein assumed a more compact conformation where the NTD and CTD are packed together. We also provided an octameric model for the full-length N bound to RNA that was consistent with electron microscopy images of the N protein in the presence of RNA. Together, our results shed new light on the dynamics and higher-order oligomeric structure of this versatile protein."</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 tables for 'The dynamic landscape of competing endogenous RNA (ceRNA) network in Early-Onset Preeclampsia under hypoxia condition '
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Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study- Part 3
<p>Trajectories and input files for the simulations of the Rbfox·pre-miR20b complex.</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.
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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.