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6 results for “protein druggability”

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zenodo40/100

Data for the article: "Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2's Spike Protein" by Ilke Ugur and Antoine Marion

<p>This upload contains data related to the article<br> published as a preprint on ChemRxiv with DOI<br> https://doi.org/10.26434/chemrxiv.13292768</p> <p>&quot;Molecular Modelling Reveals Eight Novel Druggable Binding Sites in SARS-CoV-2&#39;s Spike Protein&quot;<br> by Ilke Ugur and Antoine Marion (2020)<br> Department of Chemistry, Middle East Technical University, Ankara, Turkey.</p> <p>For further information, please contact:<br> ilkeugur@metu.edu.tr ; amarion@metu.edu.tr</p> <p>The manuscript is currently under peer-review.</p> <p>Content:</p> <p>Library of molecules derived from DrugBank v 5.1.5:<br> - DrugBank_2020_5.1.5/ &nbsp; &nbsp; &nbsp; &nbsp;# All necessary files for the docking and refinement of the library of molecules.<br> -- DB_5.1.5_pH7.4_pdbqt/ &nbsp; &nbsp; &nbsp;## PDBQT readily usable for docking with AutoDock Vina.<br> -- DB_5.1.5_pH7.4_mol2amber/ &nbsp;## mol2 files containing assigned GAFF atom types and Gasteiger atomic charges.<br> -- DB_5.1.5_pH7.4_frcmod/ &nbsp; &nbsp; ## frcmod files containing missing molecular mechanics parameters<br> -- dbID_name.dat &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;## DrugBank ID to generic name dictionary</p> <p>Note: The files were prepared automatically via a series of operations handling openbabel and antechamber.<br> &nbsp; &nbsp; &nbsp; The protonation state of ionizable groups as well as Gasteiger atomic charges were assigned by openbabel for a pH of 7.4<br> &nbsp; &nbsp; &nbsp; mol2 and frcmod files can be used readily via the tleap module of AmberTools to produce topology files.</p> <p><br> Receptor structures:<br> - receptors/ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;# PDB files for the four structures of the spike protein considered in this work<br> -- CS00ns.pdb &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ## Closed state after the remodelling of missing loops (PDB ID 6vxx)<br> -- OS00ns.pdb &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ## Open &nbsp; state after the remodelling of missing loops (PDB ID 6vyb)<br> -- CS25ns.pdb &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ## Closed state after 25 ns of molecular dynamics in explicit water<br> -- OS25ns.pdb &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; ## Open &nbsp; state after 25 ns of molecular dynamics in explicit water</p> <p>Note: All structures are aligned to CS00ns.pdb and can be converted to pdbqt for docking with AutoDock Vina</p> <p><br> Docking grid centers:<br> - dockingCenters/ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # XYZ files containing the coordinates of each docking grid center considered in this work</p> <p>Note: The coordinates are given in the same frame as that of the four structures of the receptor.</p> <p><br> Binding sites:<br> - bindingSites/ &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # XYZ files with the coordinates of the representative atomic centres<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # of each binding site identified in this work (A-H).</p> <p>Note: These files can be used to get a clearer picture of the binding sites within the structures<br> &nbsp; &nbsp; &nbsp; of the spike protein shared in the receptors directory.</p> <p><br> Final modelling results:<br> - allData.txt &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # data for all molecules in the set (approved and investigational)<br> - appData.txt &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # data for approved molecules only<br> - data.xlsx &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # data for all molecules in the set (approved and investigational)<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # as a formatted excel spreadsheet</p> <p>Note: The columns are delimited with semi-colons &quot;;&quot;.<br> &nbsp; &nbsp; &nbsp; The files contain the results for the best pose of all approved molecules for which<br> &nbsp; &nbsp; &nbsp; molecular mechanics-based geometry optimization succeeded, regardless of their score.<br> &nbsp; &nbsp; &nbsp; For other molecules, the result of their best pose is reported only for those complexes<br> &nbsp; &nbsp; &nbsp; having MM interaction energy lower or equal to -22.00 kcal/mol.</p> <p><br> Visualization:<br> - bs.pse &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;# pymol session representing the binding sites within the<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # closed state structure of the spike protein (CS00ns)<br> - pt.pse &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;# pymol session representing the docking grid centres within<br> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; # closed statestructure of the spike protein (CS00ns)</p> <p>Note: the PSE files should be compatible with version 7.0 of pymol and later</p>

opencc-by-4.0Dec 2020View details →
dryad32/100

A hybrid structure determination approach to investigate the druggability of the nucleocapsid protein of SARS-CoV-2

<p><span>The ongoing pandemic caused by SARS-CoV-2 has called for concerted efforts to generate new insights into the biology of betacoronaviruses to inform drug screening and development. Here, we establish a workflow to determine the RNA recognition and druggability of the nucleocapsid N-protein of SARS-CoV-2, a highly abundant protein crucial for the viral life cycle. We use a synergistic method that combines NMR spectroscopy and protein-RNA cross-linking coupled to mass spectrometry to quickly determine the RNA binding of two RNA recognition domains of the N-protein. Finally, we explore the druggability of these domains by performing an NMR fragment screening. This workflow identified small molecule chemotypes that bind to RNA binding interfaces and that have promising properties for further drug development.</span></p> <p><span>This deposition contains the NMR data acquired to determine the structural features of RBDs- RNA recognition as well as selected relevant data regarding the characterization of promising molecular fragments to disrupt protein-RNA interaction.</span></p> <p><span>Furthermore, we included the molecular docking files used to obtain the reported structural model.</span></p>

opencc-zeroOct 2022View details →
dryad32/100

A hybrid structure determination approach to investigate the druggability of the nucleocapsid protein of SARS-CoV-2

Open the record for dataset details and reuse information.

publicFeb 2023View details →
zenodo28/100

Supervised molecular dynamics for exploring the druggability of the SARS-CoV-2 spike protein (Topology and .xtc files)

<p>ABSTRACT. The recent outbreak of the respiratory syndrome-related coronavirus (SARS-CoV-2) is stimulating an unprecedented scientific campaign to alleviate the burden of the coronavirus disease (COVID-19). One line of research has focused on targeting SARS-CoV-2 proteins fundamental for its replication by repurposing drugs approved for other diseases. The first interaction between the virus and the host cell is mediated by the spike protein on the virus surface and the human angiotensin-converting enzyme (ACE2). Small molecules able to bind the receptor-binding domain (RBD) of the spike protein and disrupt the binding to ACE2 would offer an important tool for slowing, or even preventing, the infection. Here, we screened 2421 approved small molecules<em> in </em>silico and validated the docking outcomes through extensive molecular dynamics simulations. Out of six drugs characterized as putative RBD binders, the cephalosporin antibiotic cefsulodin was further assessed for its effect on the binding between the RBD and ACE2, suggesting the importance of considering the dynamic formation of the heterodimer when judging any potential candidate.</p>

opencc-by-4.0Oct 2020View details →
geo24/100

Genome-scale CRISPR screening identifies cell cycle and protein ubiquitination processes as druggable targets for erlotinib-resistant lung cancer

GEO Series GSE142669. Homo sapiens. 10 samples. Type: Other.

openGEO-OpenNov 2020View details →
geo12/100

Protein Arginine Methyltransferase 5 (PRMT5) has prognostic relevance and is a druggable target in Multiple Myeloma

GEO Series GSE103966. Homo sapiens. 4 samples. Type: Expression profiling by array.

openGEO-OpenSep 2017View details →

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