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5 results for “dissociation rate”
Functionally dissociable influences on learning rate in a dynamic environment
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G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations
<p>Data and Python scripts used for generation and analysis of RAMD dissociation trajectories for several GPCR complexes (including example showing generation of the Protein-Ligand Interaction Fingerprints, IFP, for several representative RAMD trajectories),</p> <p>reported in the manuscript</p> <p>"G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tRAMD Simulations" "G-Protein Coupled Receptor-Ligand Dissociation Rates and Mechanisms from tauRAMD Simulations"</p> <p>by Daria B. Kokh, Rebecca C. Wade</p> <p>submitted to the Journal of Chemical Theory and Computation</p> <p> </p> <p>1. <strong>README.txt </strong>- instruction for script usage</p> <p>2. <strong>PDBs.zip</strong> - PDB structures of complexes in water box used in the analysis, ligand PDB and mol2 structures</p> <p>3. <strong>tauRAMD_v2.py </strong>- Python sctipt for estimation relative residence times from Gromacs-RAMD output </p> <p>4. <strong>IFP_preprocess_Gromacs.py</strong> and <strong>IFP_SL-B2AR-WB-EX.py - </strong>Python scripts for preprocessing of RAMD trajectories and generation of IFPs</p> <p>5. <strong>Scripts.zip</strong> - additional python functions </p> <p>6. <strong>IXO-CHL.zip, IXO-ALO-CHL.zip, ACh-CHL.zip, b2AR.zip</strong> - Protein-Ligand Interaction Fingerprints (PL IFPs) generated from RAMD trajectories for <em>mAChR M2 with iperoxo</em>, <em>mAChR M2 </em><em> with iperoxo and PAM, mAChR M2 with ACh, and </em>β<em>2AR with alprenolol </em><em>.</em> </p> <p>7. <strong>Topology.zip</strong> - Gromacs topology, index.ndx, and coordinate gro files for all four systems</p> <p>8. <strong>Example_b2AR-alprenolol.zip </strong>- a set of data for a test example showing how IFP can be generated from RAMD trajectories (including several representative trajectories)</p> <p>9. <strong>Example_b2AR-alprenolol.tar </strong>- almost the same set of data as above (compressed in Windows) but for Linux users. The only difference between tar and zip archive: a short equilibration trajectory that is missing in the zip set but is included in the tar archive.</p> <p>10.<strong> Gromacs-IFP-GPCR.ipynb</strong> - Jupyter Notebook for analysis of trajectories using generated IFP data</p> <p>11. <strong>Auxi-Plots-GPCR.ipynb - </strong>Jupyter Notebook for generation additional plots from the paper</p> <p>12. <strong>Waters.zip</strong> - number of water molecules in the binding pocket in dissociation trajectories of the <em> </em>β<em>2AR - alprenolol system</em></p> <p>13. <strong>GPCR.yml</strong> - JN environment file</p> <p> </p>
Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD
<p>Set of data and scripts for the analysis of RAMD dissociation trajectories generated for BN-NS and BT/BCT-BPTI mutants, reported in the manuscript:</p> <p><br>"Computational screening of the effects of mutations on protein-protein off-rates and dissociation mechanisms by τRAMD"</p> <p>by Giulia D'Arrigo, Daria B. Kokh, Ariane Nunes-Alves and Rebecca C. Wade</p> <p> </p> <ol> <li>RAMD movies of WT Bn-Bs and D35Abn mutant dissociation pathway (WT-diss.mp4 and D35Abn-diss.mp4)</li> <li>Protein-Protein.zip contains:</li> </ol> <ul> <li>README - set of instructions to go through files and for the use of the scripts</li> <li>Jupyter notebooks: tauRAMD_PP_Residence_time.ipynb and tauRAMD_PP_Unbinding_pathways.ipynb</li> <li>Scripts used for analysis and postprocessing RAMD simulations - for the correct usage of the scripts check the corresponding file header</li> <li>System input files in BN-BS/ and BT_BCT-BPTI/</li> <li>Experimental data used</li> <li>2 RAMD movies (.mp4) showing dissociation of WT Bn-Bs and D35Abn mutant</li> </ul>
Dissociation rate compensation mechanism for budding yeast pioneer transcription factors
<p>Single molecule data sets related to "Dissociation rate compensation mechanism for budding yeast pioneer transcription factors."</p>
Rates of LDL entry and retention in mouse aorta are dissociated and predict the course of atherogenesis
GEO Series GSE210096. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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