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

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 science...

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Bibliographic Details
Main Authors: Elias Dahdouh, Lisa Allander, Linda Falgenhauer, Bogdan I. Iorga, Stefano Lorenzetti, Íñigo Marcos-Alcalde, Nathaniel I. Martin, Luis Martínez-Martínez, Jesús Mingorance, Thierry Naas, Joseph E. Rubin, Francesca Spyrakis, Thomas Tängdén, Paulino Gómez-Puertas
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:International Journal of Molecular Sciences
Subjects:
Online Access:https://www.mdpi.com/1422-0067/23/17/9746
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Summary: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.
ISSN:1661-6596
1422-0067