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Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets

Covalent drugs have been intensively studied in some very important fields such as anti-tumor and anti-virus, including the currently global-spread SARS-CoV-2. However, these drugs may interact with a variety of biological macromolecules and cause serious toxicology, so how to reactivate the inhibit...

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Autores principales: Wei, Zhao, Yang, Jie, Liu, Yanqin, Nie, Huifang, Yao, Lin, Yang, Jun, Guo, Lei, Zheng, Zhibing, Ouyang, Qin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Masson SAS. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877871/
https://www.ncbi.nlm.nih.gov/pubmed/33611189
http://dx.doi.org/10.1016/j.ejmech.2021.113286
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author Wei, Zhao
Yang, Jie
Liu, Yanqin
Nie, Huifang
Yao, Lin
Yang, Jun
Guo, Lei
Zheng, Zhibing
Ouyang, Qin
author_facet Wei, Zhao
Yang, Jie
Liu, Yanqin
Nie, Huifang
Yao, Lin
Yang, Jun
Guo, Lei
Zheng, Zhibing
Ouyang, Qin
author_sort Wei, Zhao
collection PubMed
description Covalent drugs have been intensively studied in some very important fields such as anti-tumor and anti-virus, including the currently global-spread SARS-CoV-2. However, these drugs may interact with a variety of biological macromolecules and cause serious toxicology, so how to reactivate the inhibited targets seems to be imperative in the near future. Organophosphate was an extreme example, which could form a covalent bound easily with acetylcholinesterase and irreversibly inhibited the enzyme, causing high toxicology. Some nucleophilic oxime reactivators for organophosphate poisoned acetylcholinesterase had been developed, but the reactivation process was still less understanding. Herein, we proposed there should be a pre-reactivated pose during the reactivating process and compounds whose binding pose was easy to transfer to the pre-reactivated pose might be efficient reactivators. Then we refined the previous reactivators based on the molecular dynamic simulation results, the resulting compounds L7R3 and L7R5 were proven as much more efficient reactivators for organophosphate inhibited acetylcholinesterase than currently used oximes. This work might provide some insights for constructing reactivators of covalently inhibited targets by using computational methods.
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spelling pubmed-78778712021-02-16 Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets Wei, Zhao Yang, Jie Liu, Yanqin Nie, Huifang Yao, Lin Yang, Jun Guo, Lei Zheng, Zhibing Ouyang, Qin Eur J Med Chem Research Paper Covalent drugs have been intensively studied in some very important fields such as anti-tumor and anti-virus, including the currently global-spread SARS-CoV-2. However, these drugs may interact with a variety of biological macromolecules and cause serious toxicology, so how to reactivate the inhibited targets seems to be imperative in the near future. Organophosphate was an extreme example, which could form a covalent bound easily with acetylcholinesterase and irreversibly inhibited the enzyme, causing high toxicology. Some nucleophilic oxime reactivators for organophosphate poisoned acetylcholinesterase had been developed, but the reactivation process was still less understanding. Herein, we proposed there should be a pre-reactivated pose during the reactivating process and compounds whose binding pose was easy to transfer to the pre-reactivated pose might be efficient reactivators. Then we refined the previous reactivators based on the molecular dynamic simulation results, the resulting compounds L7R3 and L7R5 were proven as much more efficient reactivators for organophosphate inhibited acetylcholinesterase than currently used oximes. This work might provide some insights for constructing reactivators of covalently inhibited targets by using computational methods. Elsevier Masson SAS. 2021-04-05 2021-02-11 /pmc/articles/PMC7877871/ /pubmed/33611189 http://dx.doi.org/10.1016/j.ejmech.2021.113286 Text en © 2021 Elsevier Masson SAS. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Paper
Wei, Zhao
Yang, Jie
Liu, Yanqin
Nie, Huifang
Yao, Lin
Yang, Jun
Guo, Lei
Zheng, Zhibing
Ouyang, Qin
Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title_full Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title_fullStr Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title_full_unstemmed Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title_short Molecular modeling-guided optimization of acetylcholinesterase reactivators: A proof for reactivation of covalently inhibited targets
title_sort molecular modeling-guided optimization of acetylcholinesterase reactivators: a proof for reactivation of covalently inhibited targets
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877871/
https://www.ncbi.nlm.nih.gov/pubmed/33611189
http://dx.doi.org/10.1016/j.ejmech.2021.113286
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