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Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study
In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833253/ https://www.ncbi.nlm.nih.gov/pubmed/33518858 http://dx.doi.org/10.1016/j.chemolab.2020.104172 |
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author | Masand, Vijay H. Akasapu, Siddhartha Gandhi, Ajaykumar Rastija, Vesna Patil, Meghshyam K. |
author_facet | Masand, Vijay H. Akasapu, Siddhartha Gandhi, Ajaykumar Rastija, Vesna Patil, Meghshyam K. |
author_sort | Masand, Vijay H. |
collection | PubMed |
description | In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that govern the MPro inhibitory activity of peptide-type compounds. The QSAR analysis is based on a dataset of sixty-two peptide-type compounds which resulted in the generation of statistically robust and highly predictive multiple models. All the developed models were validated extensively and satisfy the threshold values for many statistical parameters (for e.g. R(2) = 0.80–0.82, Q(2)(loo) = 0.74–0.77, Q(2)(LMO) = 0.66–0.67). The developed QSAR models identified number of sp(2) hybridized Oxygen atoms within seven bonds from aromatic Carbon atoms, the presence of Carbon and Nitrogen atoms at a topological distance of 3 and other interrelations of atom pairs as important pharmacophoric features. Hence, the present QSAR models have a good balance of Qualitative (Descriptive QSARs) and Quantitative (Predictive QSARs) approaches, therefore useful for future modifications of peptide-type compounds for anti- SARS-CoV activity. |
format | Online Article Text |
id | pubmed-7833253 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78332532021-01-26 Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study Masand, Vijay H. Akasapu, Siddhartha Gandhi, Ajaykumar Rastija, Vesna Patil, Meghshyam K. Chemometr Intell Lab Syst Tutorial Article In the present work, an extensive QSAR (Quantitative Structure Activity Relationships) analysis of a series of peptide-type SARS-CoV main protease (MPro) inhibitors following the OECD guidelines has been accomplished. The analysis was aimed to identify salient and concealed structural features that govern the MPro inhibitory activity of peptide-type compounds. The QSAR analysis is based on a dataset of sixty-two peptide-type compounds which resulted in the generation of statistically robust and highly predictive multiple models. All the developed models were validated extensively and satisfy the threshold values for many statistical parameters (for e.g. R(2) = 0.80–0.82, Q(2)(loo) = 0.74–0.77, Q(2)(LMO) = 0.66–0.67). The developed QSAR models identified number of sp(2) hybridized Oxygen atoms within seven bonds from aromatic Carbon atoms, the presence of Carbon and Nitrogen atoms at a topological distance of 3 and other interrelations of atom pairs as important pharmacophoric features. Hence, the present QSAR models have a good balance of Qualitative (Descriptive QSARs) and Quantitative (Predictive QSARs) approaches, therefore useful for future modifications of peptide-type compounds for anti- SARS-CoV activity. Elsevier B.V. 2020-11-15 2020-10-03 /pmc/articles/PMC7833253/ /pubmed/33518858 http://dx.doi.org/10.1016/j.chemolab.2020.104172 Text en © 2020 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 | Tutorial Article Masand, Vijay H. Akasapu, Siddhartha Gandhi, Ajaykumar Rastija, Vesna Patil, Meghshyam K. Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title | Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title_full | Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title_fullStr | Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title_full_unstemmed | Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title_short | Structure features of peptide-type SARS-CoV main protease inhibitors: Quantitative structure activity relationship study |
title_sort | structure features of peptide-type sars-cov main protease inhibitors: quantitative structure activity relationship study |
topic | Tutorial Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7833253/ https://www.ncbi.nlm.nih.gov/pubmed/33518858 http://dx.doi.org/10.1016/j.chemolab.2020.104172 |
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