RT Journal Article
T1 Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network.
A1 Dahdouh, Elias
A1 Allander, Lisa
A1 Falgenhauer, Linda
A1 Iorga, Bogdan I
A1 Lorenzetti, Stefano
A1 Marcos-Alcalde, Íñigo
A1 Martin, Nathaniel I
A1 Martinez-Martinez, Luis
A1 Mingorance, Jesus
A1 Naas, Thierry
A1 Rubin, Joseph E
A1 Spyrakis, Francesca
A1 Tängden, Thomas
A1 Gomez-Puertas, Paulino
K1 Approach rationalization
K1 Inhibitors of carbapenemases
K1 Virtual screening
AB 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.
PB MDPI
YR 2022
FD 2022-08-27
LK http://hdl.handle.net/10668/21191
UL http://hdl.handle.net/10668/21191
LA en
NO 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
DS RISalud
RD Apr 18, 2025