Publication:
Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network.

dc.contributor.authorDahdouh, Elias
dc.contributor.authorAllander, Lisa
dc.contributor.authorFalgenhauer, Linda
dc.contributor.authorIorga, Bogdan I
dc.contributor.authorLorenzetti, Stefano
dc.contributor.authorMarcos-Alcalde, Íñigo
dc.contributor.authorMartin, Nathaniel I
dc.contributor.authorMartinez-Martinez, Luis
dc.contributor.authorMingorance, Jesus
dc.contributor.authorNaas, Thierry
dc.contributor.authorRubin, Joseph E
dc.contributor.authorSpyrakis, Francesca
dc.contributor.authorTängden, Thomas
dc.contributor.authorGomez-Puertas, Paulino
dc.contributor.funderInstituto de Salud Carlos III
dc.contributor.funderEuropean Regional Development Fund, ERDF
dc.date.accessioned2023-05-03T14:02:54Z
dc.date.available2023-05-03T14:02:54Z
dc.date.issued2022-08-27
dc.description.abstractThe EPIC consortium brings together experts from a wide range of fields that include clinical, molecular and basic microbiology, infectious diseases, computational biology and chemistry, drug discovery and design, bioinformatics, biochemistry, biophysics, pharmacology, toxicology, veterinary sciences, environmental sciences, and epidemiology. The main question to be answered by the EPIC alliance is the following: "What is the best approach for data mining on carbapenemase inhibitors and how to translate this data into experiments?" From this forum, we propose that the scientific community think up new strategies to be followed for the discovery of new carbapenemase inhibitors, so that this process is efficient and capable of providing results in the shortest possible time and within acceptable time and economic costs.
dc.description.versionSi
dc.identifier.citationDahdouh E, Allander L, Falgenhauer L, Iorga BI, Lorenzetti S, Marcos-Alcalde Í, et al. Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network. Int J Mol Sci. 2022 Aug 28;23(17):9746
dc.identifier.doi10.3390/ijms23179746
dc.identifier.essn1422-0067
dc.identifier.pmcPMC9456441
dc.identifier.pmid36077146
dc.identifier.pubmedURLhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9456441/pdf
dc.identifier.unpaywallURLhttps://www.mdpi.com/1422-0067/23/17/9746/pdf?version=1661758322
dc.identifier.urihttp://hdl.handle.net/10668/21191
dc.issue.number17
dc.journal.titleInternational journal of molecular sciences
dc.journal.titleabbreviationInt J Mol Sci
dc.language.isoen
dc.organizationHospital Universitario Reina Sofía
dc.organizationInstituto Maimónides de Investigación Biomédica de Córdoba-IMIBIC
dc.page.number6
dc.publisherMDPI
dc.pubmedtypeJournal Article
dc.relation.projectIDAC20/00012
dc.relation.publisherversionhttps://www.mdpi.com/1422-0067/23/17/9746
dc.rightsAttribution 4.0 International
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectApproach rationalization
dc.subjectInhibitors of carbapenemases
dc.subjectVirtual screening
dc.subject.decsBiología computacional
dc.subject.decsProteínas bacterianas
dc.subject.decsSimulación por computador
dc.subject.decsbeta-lactamasas
dc.subject.meshBacterial proteins
dc.subject.meshComputational biology
dc.subject.meshComputer simulation
dc.subject.meshbeta-lactamases
dc.titleComputational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network.
dc.typeresearch article
dc.type.hasVersionVoR
dc.volume.number23
dspace.entity.typePublication

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