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QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors
The 3C-like protease (3CL(pro)), known as the main protease of SARS-COV, plays a vital role in the viral replication cycle and is a critical target for the development of SARS inhibitor. Comparative sequence analysis has shown that the 3CL(pro) of two coronaviruses, SARS-CoV-2 and SARS-CoV, show hig...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079496/ https://www.ncbi.nlm.nih.gov/pubmed/37024955 http://dx.doi.org/10.1186/s13065-023-00947-w |
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author | Soleymani, Niousha Ahmadi, Shahin Shiri, Fereshteh Almasirad, Ali |
author_facet | Soleymani, Niousha Ahmadi, Shahin Shiri, Fereshteh Almasirad, Ali |
author_sort | Soleymani, Niousha |
collection | PubMed |
description | The 3C-like protease (3CL(pro)), known as the main protease of SARS-COV, plays a vital role in the viral replication cycle and is a critical target for the development of SARS inhibitor. Comparative sequence analysis has shown that the 3CL(pro) of two coronaviruses, SARS-CoV-2 and SARS-CoV, show high structural similarity, and several common features are shared among the substrates of 3CL(pro) in different coronaviruses. The goal of this study is the development of validated QSAR models by CORAL software and Monte Carlo optimization to predict the inhibitory activity of 81 isatin and indole-based compounds against SARS CoV 3CL(pro). The models were built using a newer objective function optimization of this software, known as the index of ideality correlation (IIC), which provides favorable results. The entire set of molecules was randomly divided into four sets including: active training, passive training, calibration and validation sets. The optimal descriptors were selected from the hybrid model by combining SMILES and hydrogen suppressed graph (HSG) based on the objective function. According to the model interpretation results, eight synthesized compounds were extracted and introduced from the ChEMBL database as good SARS CoV 3CL(pro) inhibitor. Also, the activity of the introduced molecules further was supported by docking studies using 3CL(pro) of both SARS-COV-1 and SARS-COV-2. Based on the results of ADMET and OPE study, compounds CHEMBL4458417 and CHEMBL4565907 both containing an indole scaffold with the positive values of drug-likeness and the highest drug-score can be introduced as selected leads. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13065-023-00947-w. |
format | Online Article Text |
id | pubmed-10079496 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-100794962023-04-07 QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors Soleymani, Niousha Ahmadi, Shahin Shiri, Fereshteh Almasirad, Ali BMC Chem Research The 3C-like protease (3CL(pro)), known as the main protease of SARS-COV, plays a vital role in the viral replication cycle and is a critical target for the development of SARS inhibitor. Comparative sequence analysis has shown that the 3CL(pro) of two coronaviruses, SARS-CoV-2 and SARS-CoV, show high structural similarity, and several common features are shared among the substrates of 3CL(pro) in different coronaviruses. The goal of this study is the development of validated QSAR models by CORAL software and Monte Carlo optimization to predict the inhibitory activity of 81 isatin and indole-based compounds against SARS CoV 3CL(pro). The models were built using a newer objective function optimization of this software, known as the index of ideality correlation (IIC), which provides favorable results. The entire set of molecules was randomly divided into four sets including: active training, passive training, calibration and validation sets. The optimal descriptors were selected from the hybrid model by combining SMILES and hydrogen suppressed graph (HSG) based on the objective function. According to the model interpretation results, eight synthesized compounds were extracted and introduced from the ChEMBL database as good SARS CoV 3CL(pro) inhibitor. Also, the activity of the introduced molecules further was supported by docking studies using 3CL(pro) of both SARS-COV-1 and SARS-COV-2. Based on the results of ADMET and OPE study, compounds CHEMBL4458417 and CHEMBL4565907 both containing an indole scaffold with the positive values of drug-likeness and the highest drug-score can be introduced as selected leads. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13065-023-00947-w. Springer International Publishing 2023-04-07 /pmc/articles/PMC10079496/ /pubmed/37024955 http://dx.doi.org/10.1186/s13065-023-00947-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Soleymani, Niousha Ahmadi, Shahin Shiri, Fereshteh Almasirad, Ali QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title | QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title_full | QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title_fullStr | QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title_full_unstemmed | QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title_short | QSAR and molecular docking studies of isatin and indole derivatives as SARS 3CL(pro) inhibitors |
title_sort | qsar and molecular docking studies of isatin and indole derivatives as sars 3cl(pro) inhibitors |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10079496/ https://www.ncbi.nlm.nih.gov/pubmed/37024955 http://dx.doi.org/10.1186/s13065-023-00947-w |
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