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

• Published in: International journal of molecular sciences Vol. 23; no. 17; p. 9746
• Main Authors: Dahdouh, Elias, Allander, Lisa, Falgenhauer, Linda, Iorga, Bogdan I., Lorenzetti, Stefano, Marcos-Alcalde, Íñigo, Martin, Nathaniel I., Martínez-Martínez, Luis, Mingorance, Jesús, Naas, Thierry, Rubin, Joseph E., Spyrakis, Francesca, Tängdén, Thomas, Gómez-Puertas, Paulino
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2022; MDPI
• Subjects: Algorithms; Antibiotics; Antimicrobial agents; approach rationalization; Bacterial infections; Bacteriology; Binding sites; Bioinformatics; Biophysics; Carbapenemase; Computer applications; Drug development; Economic impact; Enzymes; Epidemiology; Infections; Infectious diseases; Inhibitors; inhibitors of carbapenemases; Life Sciences; Microbiology; Microbiology and Parasitology; Pharmacology; Proteins; Toxicology; virtual screening
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms23179746

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.