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Toward Autonomous Antibiotic Discovery
Machines hold the potential to replace humans in many societal endeavors, and drug discovery is no exception. Antibiotic innovation has been stalled for decades, which has coincided with an alarming increase in multidrug-resistant bacteria. Since the beginning of the antibiotic era, the natural worl...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584881/ https://www.ncbi.nlm.nih.gov/pubmed/31186311 http://dx.doi.org/10.1128/mSystems.00151-19 |
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author | de la Fuente-Nunez, Cesar |
author_facet | de la Fuente-Nunez, Cesar |
author_sort | de la Fuente-Nunez, Cesar |
collection | PubMed |
description | Machines hold the potential to replace humans in many societal endeavors, and drug discovery is no exception. Antibiotic innovation has been stalled for decades, which has coincided with an alarming increase in multidrug-resistant bacteria. Since the beginning of the antibiotic era, the natural world has been our greatest innovator, giving rise to nearly all antibiotics available today. As mere observers of the vast molecular diversity produced by Earth’s organisms, we have perfected the art of isolating novel chemistries with life-saving antimicrobial properties. However, today we are at a crossroads, as no new molecular scaffolds have been discovered for decades. We may need to look beyond the natural world into the virtual dimension for solutions and harness present-day computational power to help solve the grand global health challenge of antibiotic resistance. Computer-made drugs may enable the discovery of unprecedented functions in biological systems and help replenish our arsenal of effective antibiotics. |
format | Online Article Text |
id | pubmed-6584881 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-65848812019-07-03 Toward Autonomous Antibiotic Discovery de la Fuente-Nunez, Cesar mSystems Perspective Machines hold the potential to replace humans in many societal endeavors, and drug discovery is no exception. Antibiotic innovation has been stalled for decades, which has coincided with an alarming increase in multidrug-resistant bacteria. Since the beginning of the antibiotic era, the natural world has been our greatest innovator, giving rise to nearly all antibiotics available today. As mere observers of the vast molecular diversity produced by Earth’s organisms, we have perfected the art of isolating novel chemistries with life-saving antimicrobial properties. However, today we are at a crossroads, as no new molecular scaffolds have been discovered for decades. We may need to look beyond the natural world into the virtual dimension for solutions and harness present-day computational power to help solve the grand global health challenge of antibiotic resistance. Computer-made drugs may enable the discovery of unprecedented functions in biological systems and help replenish our arsenal of effective antibiotics. American Society for Microbiology 2019-06-11 /pmc/articles/PMC6584881/ /pubmed/31186311 http://dx.doi.org/10.1128/mSystems.00151-19 Text en Copyright © 2019 de la Fuente-Nunez. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Perspective de la Fuente-Nunez, Cesar Toward Autonomous Antibiotic Discovery |
title | Toward Autonomous Antibiotic Discovery |
title_full | Toward Autonomous Antibiotic Discovery |
title_fullStr | Toward Autonomous Antibiotic Discovery |
title_full_unstemmed | Toward Autonomous Antibiotic Discovery |
title_short | Toward Autonomous Antibiotic Discovery |
title_sort | toward autonomous antibiotic discovery |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584881/ https://www.ncbi.nlm.nih.gov/pubmed/31186311 http://dx.doi.org/10.1128/mSystems.00151-19 |
work_keys_str_mv | AT delafuentenunezcesar towardautonomousantibioticdiscovery |