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DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design

Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target protein...

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Detalles Bibliográficos
Autores principales: Liu, Yang, Gan, Jianhong, Wang, Rongqi, Yang, Xiaocong, Xiao, Zhixiong, Cao, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838031/
https://www.ncbi.nlm.nih.gov/pubmed/35163948
http://dx.doi.org/10.3390/molecules27030683
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author Liu, Yang
Gan, Jianhong
Wang, Rongqi
Yang, Xiaocong
Xiao, Zhixiong
Cao, Yang
author_facet Liu, Yang
Gan, Jianhong
Wang, Rongqi
Yang, Xiaocong
Xiao, Zhixiong
Cao, Yang
author_sort Liu, Yang
collection PubMed
description Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target proteins from 181 CADD publications. We performed unified docking simulations and neck-to-neck comparison with the solved co-crystal structures. We computed their chemical features and classified these compounds, aiming to provide insights for subsequent drug design. Through detailed analyses, we recommended a batch of compounds that are worth further study. Moreover, we organized all the abundant data and constructed a freely available database, DrugDevCovid19, to facilitate the development of COVID-19 therapeutics.
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spelling pubmed-88380312022-02-13 DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design Liu, Yang Gan, Jianhong Wang, Rongqi Yang, Xiaocong Xiao, Zhixiong Cao, Yang Molecules Article Since the outbreak of SARS-CoV-2, numerous compounds against COVID-19 have been derived by computer-aided drug design (CADD) studies. They are valuable resources for the development of COVID-19 therapeutics. In this work, we reviewed these studies and analyzed 779 compounds against 16 target proteins from 181 CADD publications. We performed unified docking simulations and neck-to-neck comparison with the solved co-crystal structures. We computed their chemical features and classified these compounds, aiming to provide insights for subsequent drug design. Through detailed analyses, we recommended a batch of compounds that are worth further study. Moreover, we organized all the abundant data and constructed a freely available database, DrugDevCovid19, to facilitate the development of COVID-19 therapeutics. MDPI 2022-01-21 /pmc/articles/PMC8838031/ /pubmed/35163948 http://dx.doi.org/10.3390/molecules27030683 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 Article
Liu, Yang
Gan, Jianhong
Wang, Rongqi
Yang, Xiaocong
Xiao, Zhixiong
Cao, Yang
DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title_full DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title_fullStr DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title_full_unstemmed DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title_short DrugDevCovid19: An Atlas of Anti-COVID-19 Compounds Derived by Computer-Aided Drug Design
title_sort drugdevcovid19: an atlas of anti-covid-19 compounds derived by computer-aided drug design
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838031/
https://www.ncbi.nlm.nih.gov/pubmed/35163948
http://dx.doi.org/10.3390/molecules27030683
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