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dc.contributor.authorCatalina-Hernández, Èric
dc.contributor.authorLópez-Martín, Mario
dc.contributor.authorMasnou-Sánchez, David
dc.contributor.authorMartins, Marco
dc.contributor.authorLorenz Fonfria, Victor A.
dc.contributor.authorJiménez-Altayó, Francesc
dc.contributor.authorHellmich, Ute A.
dc.contributor.authorInada, Hitoshi
dc.contributor.authorAlcaraz, Antonio
dc.contributor.authorFurutani, Yuji
dc.contributor.authorNonell-Canals, Alfons
dc.contributor.authorVázquez-ibar, José Luis
dc.contributor.authorDomene, Carmen
dc.contributor.authorGaudet, Rachelle
dc.contributor.authorPerálvarez-Marín, Alex
dc.date.accessioned2024-05-15T12:12:41Z
dc.date.available2024-05-15T12:12:41Z
dc.date.issued2023-12-29
dc.identifier.citationCATALINA-HERNÁNDEZ, Èric, et al. Experimental and computational biophysics to identify vasodilator drugs targeted at TRPV2 using agonists based on the probenecid scaffold. Computational and Structural Biotechnology Journal, 2024, vol. 23, p. 473-482.ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/207350
dc.description.abstractTRP channels are important pharmacological targets in physiopathology. TRPV2 plays distinct roles in cardiac and neuromuscular function, immunity, and metabolism, and is associated with pathologies like muscular dystrophy and cancer. However, TRPV2 pharmacology is unspecific and scarce at best. Using in silico similarity-based chemoinformatics we obtained a set of 270 potential hits for TRPV2 categorized into families based on chemical nature and similarity. Docking the compounds on available rat TRPV2 structures allowed the clustering of drug families in specific ligand binding sites. Starting from a probenecid docking pose in the piperlongumine binding site and using a Gaussian accelerated molecular dynamics approach we have assigned a putative probenecid binding site. In parallel, we measured the EC50 of 7 probenecid derivatives on TRPV2 expressed in Pichia pastoris using a novel medium-throughput Ca2+ influx assay in yeast membranes together with an unbiased and unsupervised data analysis method. We found that 4-(piperidine-1-sulfonyl)-benzoic acid had a better EC50 than probenecid, which is one of the most specific TRPV2 agonists to date. Exploring the TRPV2-dependent anti-hypertensive potential in vivo, we found that 4-(piperidine-1-sulfonyl)-benzoic acid shows a sex-biased vasodilator effect producing larger vascular relaxations in female mice. Overall, this study expands the pharmacological toolbox for TRPV2, a widely expressed membrane protein and orphan drug target.ca_CA
dc.format.extent10 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherElsevierca_CA
dc.relationMembrane-associated Protein Assemblies, Machineries, and Supercomplexesca_CA
dc.rights© 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.ca_CA
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/ca_CA
dc.subjection channelsca_CA
dc.subjectTRP channelsca_CA
dc.subjectTRPV2ca_CA
dc.subjectdrug discoveryca_CA
dc.subjectmembrane proteinsca_CA
dc.subjectbiophysicsca_CA
dc.subjectdockingca_CA
dc.subjectcardiovascularca_CA
dc.subjectcomputational biologyca_CA
dc.subjectstructural biologyca_CA
dc.subjectpharmacologyca_CA
dc.titleExperimental and computational biophysics to identify vasodilator drugs targeted at TRPV2 using agonists based on the probenecid scaffoldca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1016/j.csbj.2023.12.028
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA
project.funder.identifierID 390713860ca_CA
project.funder.nameMCIN/AEI/10.13039/501100011033ca_CA
project.funder.nameMinisterio de Ciencia, Innovación y Universidades. Margarita Salas Awardca_CA
project.funder.nameUniversitat Autònoma De Barcelonaca_CA
project.funder.nameRoyal Society of Chemistryca_CA
project.funder.nameDeutsche Forschungsgemeinschaft (DFG, German Research Foundation)ca_CA
project.funder.nameCluster of Excellence “Balance of the Microverse” EXC 2051ca_CA
oaire.awardNumberPID2020–120222GB-I00ca_CA
oaire.awardNumberMGSD2021-10ca_CA
oaire.awardNumberB21P0033ca_CA
oaire.awardNumberIES\R3\193089ca_CA
oaire.awardNumberID 450648163ca_CA


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© 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
Excepto si se señala otra cosa, la licencia del ítem se describe como: © 2024 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.