Publication: Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network.
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Identifiers
Date
2022-08-27
Authors
Dahdouh, Elias
Allander, Lisa
Falgenhauer, Linda
Iorga, Bogdan I
Lorenzetti, Stefano
Marcos-Alcalde, Íñigo
Martin, Nathaniel I
Martinez-Martinez, Luis
Mingorance, Jesus
Naas, Thierry
Advisors
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
The 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.
Description
MeSH Terms
Bacterial proteins
Computational biology
Computer simulation
beta-lactamases
Computational biology
Computer simulation
beta-lactamases
DeCS Terms
Biología computacional
Proteínas bacterianas
Simulación por computador
beta-lactamasas
Proteínas bacterianas
Simulación por computador
beta-lactamasas
CIE Terms
Keywords
Approach rationalization, Inhibitors of carbapenemases, Virtual screening
Citation
Dahdouh 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