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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Published inInternational 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
LanguageEnglish
Published Basel MDPI AG 01.09.2022
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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.
AbstractList 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.
Author Dahdouh, Elias
Martínez-Martínez, Luis
Rubin, Joseph E
Falgenhauer, Linda
Martin, Nathaniel I
Spyrakis, Francesca
Iorga, Bogdan I
Allander, Lisa
Naas, Thierry
Lorenzetti, Stefano
Mingorance, Jesús
Gómez-Puertas, Paulino
Tängdén, Thomas
Marcos-Alcalde, Íñigo
AuthorAffiliation 1 Clinical Microbiology and Parasitology Department, Instituto de Investigación Sanitaria del Hospital, Universitario La Paz (IdiPAZ), 28046 Madrid, Spain
7 Biological Chemistry Group, Institute of Biology Leiden (IBL), Leiden University, Sylviusweg 72, 2333 BE Leiden, The Netherlands
3 Institute of Hygiene and Environmental Medicine, Justus Liebig University Giessen, 35392 Giessen, Germany
11 Department of Veterinary Microbiology, University of Saskatchewan at Saskatoon, Saskatoon, SK S7N 5A2, Canada
6 Molecular Modeling Group, Centro de Biología Molecular Severo Ochoa (CBMSO, CSIC-UAM), 28049 Madrid, Spain
5 Department of Food Safety, Nutrition and Veterinary Public Health, Istituto Superiore di Sanità (ISS), 00161 Rome, Italy
8 Unit of Microbiology, University Hospital Reina Sofía, 14004 Córdoba, Spain
10 Department of Microbiology, Hôpital de Bicêtre, Université Paris-Saclay, 91190 Gif-sur-Yvette, France
9 Department of Agricultural Chemistry, Edaphology and Microbiology, Maimonides Biomed
AuthorAffiliation_xml – name: 4 Institut de Chimie des Substances Naturelles (ICSN), CNRS UPR 2301, Université Paris-Saclay, 91190 Gif-sur-Yvette, France
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2022 by the authors. 2022
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SubjectTerms 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
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Title Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network
URI https://www.proquest.com/docview/2711445046/abstract/
https://search.proquest.com/docview/2712856441
https://hal.science/hal-03779962
https://pubmed.ncbi.nlm.nih.gov/PMC9456441
https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-485343
https://doaj.org/article/5a1cf8dde3184d1bada38a6ebc146bfa
Volume 23
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