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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...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9456441/ https://www.ncbi.nlm.nih.gov/pubmed/36077146 http://dx.doi.org/10.3390/ijms23179746 |
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author | 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 |
author_facet | 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 |
author_sort | Dahdouh, Elias |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9456441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94564412022-09-09 Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network 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 Int J Mol Sci Commentary 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. MDPI 2022-08-28 /pmc/articles/PMC9456441/ /pubmed/36077146 http://dx.doi.org/10.3390/ijms23179746 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Commentary 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 Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title | Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title_full | Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title_fullStr | Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title_full_unstemmed | Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title_short | Computational Modeling and Design of New Inhibitors of Carbapenemases: A Discussion from the EPIC Alliance Network |
title_sort | computational modeling and design of new inhibitors of carbapenemases: a discussion from the epic alliance network |
topic | Commentary |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9456441/ https://www.ncbi.nlm.nih.gov/pubmed/36077146 http://dx.doi.org/10.3390/ijms23179746 |
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