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Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies
Though significant efforts are in progress for developing drugs and vaccines against COVID-19, limited therapeutic agents are available currently. Thus, it is essential to undertake COVID-19 research and to identify therapeutic interventions in which computational modeling and virtual screening of l...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954774/ https://www.ncbi.nlm.nih.gov/pubmed/33751995 http://dx.doi.org/10.1016/j.compbiomed.2021.104325 |
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author | Skariyachan, Sinosh Gopal, Dharshini Muddebihalkar, Aditi G. Uttarkar, Akshay Niranjan, Vidya |
author_facet | Skariyachan, Sinosh Gopal, Dharshini Muddebihalkar, Aditi G. Uttarkar, Akshay Niranjan, Vidya |
author_sort | Skariyachan, Sinosh |
collection | PubMed |
description | Though significant efforts are in progress for developing drugs and vaccines against COVID-19, limited therapeutic agents are available currently. Thus, it is essential to undertake COVID-19 research and to identify therapeutic interventions in which computational modeling and virtual screening of lead molecules provide significant insights. The present study aimed to predict the interaction potential of natural lead molecules against prospective protein targets of SARS-CoV-2 by molecular modeling, docking, and dynamic simulation. Based on the literature survey and database search, fourteen molecular targets were selected and the three targets which lack the native structures were computationally modeled. The drug-likeliness and pharmacokinetic features of ninety-two natural molecules were predicted. Four lead molecules with ideal drug-likeliness and pharmacokinetic properties were selected and docked against fourteen targets, and their binding energies were compared with the binding energy of the interaction between Chloroquine and Hydroxychloroquine to their usual targets. The stabilities of selected docked complexes were confirmed by MD simulation and energy calculations. Four natural molecules demonstrated profound binding to most of the prioritized targets, especially, Hyoscyamine and Tamaridone to spike glycoprotein and Rotiorinol-C and Scutifoliamide-A to replicase polyprotein-1ab main protease of SARS-CoV-2 showed better binding energy, conformational and dynamic stabilities compared to the binding energy of Chloroquine and its usual target glutathione-S-transferase. The aforementioned lead molecules can be used to develop novel therapeutic agents towards the protein targets of SARS-CoV-2, and the study provides significant insight for structure-based drug development against COVID-19. |
format | Online Article Text |
id | pubmed-7954774 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-79547742021-03-15 Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies Skariyachan, Sinosh Gopal, Dharshini Muddebihalkar, Aditi G. Uttarkar, Akshay Niranjan, Vidya Comput Biol Med Article Though significant efforts are in progress for developing drugs and vaccines against COVID-19, limited therapeutic agents are available currently. Thus, it is essential to undertake COVID-19 research and to identify therapeutic interventions in which computational modeling and virtual screening of lead molecules provide significant insights. The present study aimed to predict the interaction potential of natural lead molecules against prospective protein targets of SARS-CoV-2 by molecular modeling, docking, and dynamic simulation. Based on the literature survey and database search, fourteen molecular targets were selected and the three targets which lack the native structures were computationally modeled. The drug-likeliness and pharmacokinetic features of ninety-two natural molecules were predicted. Four lead molecules with ideal drug-likeliness and pharmacokinetic properties were selected and docked against fourteen targets, and their binding energies were compared with the binding energy of the interaction between Chloroquine and Hydroxychloroquine to their usual targets. The stabilities of selected docked complexes were confirmed by MD simulation and energy calculations. Four natural molecules demonstrated profound binding to most of the prioritized targets, especially, Hyoscyamine and Tamaridone to spike glycoprotein and Rotiorinol-C and Scutifoliamide-A to replicase polyprotein-1ab main protease of SARS-CoV-2 showed better binding energy, conformational and dynamic stabilities compared to the binding energy of Chloroquine and its usual target glutathione-S-transferase. The aforementioned lead molecules can be used to develop novel therapeutic agents towards the protein targets of SARS-CoV-2, and the study provides significant insight for structure-based drug development against COVID-19. Elsevier Ltd. 2021-05 2021-03-13 /pmc/articles/PMC7954774/ /pubmed/33751995 http://dx.doi.org/10.1016/j.compbiomed.2021.104325 Text en © 2021 Elsevier Ltd. 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 Skariyachan, Sinosh Gopal, Dharshini Muddebihalkar, Aditi G. Uttarkar, Akshay Niranjan, Vidya Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title | Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title_full | Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title_fullStr | Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title_full_unstemmed | Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title_short | Structural insights on the interaction potential of natural leads against major protein targets of SARS-CoV-2: Molecular modelling, docking and dynamic simulation studies |
title_sort | structural insights on the interaction potential of natural leads against major protein targets of sars-cov-2: molecular modelling, docking and dynamic simulation studies |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954774/ https://www.ncbi.nlm.nih.gov/pubmed/33751995 http://dx.doi.org/10.1016/j.compbiomed.2021.104325 |
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