Cargando…

In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis

Severe acute respiratory syndrome has relapsed recently as novel coronavirus causing a life threat to the entire world in the absence of an effective therapy. To hamper the replication of the deadly SARS CoV-2 inside the host cells, systematic in silico virtual screening of total 267,324 ligands fro...

Descripción completa

Detalles Bibliográficos
Autores principales: Nagar, Prinsa R., Gajjar, Normi D., Dhameliya, Tejas M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313085/
https://www.ncbi.nlm.nih.gov/pubmed/34334813
http://dx.doi.org/10.1016/j.molstruc.2021.131190
_version_ 1783729267158286336
author Nagar, Prinsa R.
Gajjar, Normi D.
Dhameliya, Tejas M.
author_facet Nagar, Prinsa R.
Gajjar, Normi D.
Dhameliya, Tejas M.
author_sort Nagar, Prinsa R.
collection PubMed
description Severe acute respiratory syndrome has relapsed recently as novel coronavirus causing a life threat to the entire world in the absence of an effective therapy. To hamper the replication of the deadly SARS CoV-2 inside the host cells, systematic in silico virtual screening of total 267,324 ligands from Asinex EliteSynergy and BioDesign libraries has been performed using AutoDock Vina against RdRp. The molecular modeling studies revealed the identification of twenty-one macrocyclic hits (2–22) with better binding energy than remdesivir (1), marketed SARS CoV-2 inhibitor. Further, the analysis using rules for drug-likeness and their ADMET profile revealed the candidature of these hits due to superior oral bioavailability and druggability. Further, the MD simulation studies of top two hits (2 and 3) performed using GROMACS 2020.1 for 10 ns revealed their stability into the docked complexes. These results provide an important breakthrough in the design of macrocyclic hits as SARS CoV-2 RNA replicase inhibitor.
format Online
Article
Text
id pubmed-8313085
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Elsevier B.V.
record_format MEDLINE/PubMed
spelling pubmed-83130852021-07-26 In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis Nagar, Prinsa R. Gajjar, Normi D. Dhameliya, Tejas M. J Mol Struct Article Severe acute respiratory syndrome has relapsed recently as novel coronavirus causing a life threat to the entire world in the absence of an effective therapy. To hamper the replication of the deadly SARS CoV-2 inside the host cells, systematic in silico virtual screening of total 267,324 ligands from Asinex EliteSynergy and BioDesign libraries has been performed using AutoDock Vina against RdRp. The molecular modeling studies revealed the identification of twenty-one macrocyclic hits (2–22) with better binding energy than remdesivir (1), marketed SARS CoV-2 inhibitor. Further, the analysis using rules for drug-likeness and their ADMET profile revealed the candidature of these hits due to superior oral bioavailability and druggability. Further, the MD simulation studies of top two hits (2 and 3) performed using GROMACS 2020.1 for 10 ns revealed their stability into the docked complexes. These results provide an important breakthrough in the design of macrocyclic hits as SARS CoV-2 RNA replicase inhibitor. Elsevier B.V. 2021-12-15 2021-07-26 /pmc/articles/PMC8313085/ /pubmed/34334813 http://dx.doi.org/10.1016/j.molstruc.2021.131190 Text en © 2021 Elsevier B.V. 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 Article
Nagar, Prinsa R.
Gajjar, Normi D.
Dhameliya, Tejas M.
In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title_full In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title_fullStr In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title_full_unstemmed In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title_short In search of SARS CoV-2 replication inhibitors: Virtual screening, molecular dynamics simulations and ADMET analysis
title_sort in search of sars cov-2 replication inhibitors: virtual screening, molecular dynamics simulations and admet analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8313085/
https://www.ncbi.nlm.nih.gov/pubmed/34334813
http://dx.doi.org/10.1016/j.molstruc.2021.131190
work_keys_str_mv AT nagarprinsar insearchofsarscov2replicationinhibitorsvirtualscreeningmoleculardynamicssimulationsandadmetanalysis
AT gajjarnormid insearchofsarscov2replicationinhibitorsvirtualscreeningmoleculardynamicssimulationsandadmetanalysis
AT dhameliyatejasm insearchofsarscov2replicationinhibitorsvirtualscreeningmoleculardynamicssimulationsandadmetanalysis