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Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach
Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL(pro) and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmac...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9261181/ https://www.ncbi.nlm.nih.gov/pubmed/35818588 http://dx.doi.org/10.1007/s11224-022-02004-z |
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author | Daoui, Ossama Elkhattabi, Souad Chtita, Samir |
author_facet | Daoui, Ossama Elkhattabi, Souad Chtita, Samir |
author_sort | Daoui, Ossama |
collection | PubMed |
description | Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL(pro) and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmaceutical use against COVID-19. The objective of this study was to remodel the structures of 9,10-dihydrophenanthrene derivatives to achieve a powerful biological activity against 3CL(pro) and favorable pharmacokinetic properties for drug design and discovery. Therefore, by the use of bioinformatics techniques, we developed robust 3D-QSAR models that are capable of describing the structure–activity relationship for 46 molecules based on 9,10-dihydrophenanthrene derivatives using CoMFA/SE (R(2) = 0.97, Q(2) = 0.81, R(2)(pred) = 0.95, (c)R(2)(p) = 0.71) and CoMSIA/SEHDA (R(2) = 0.94, Q(2) = 0.76, R(2)(pred) = 0.91, (c)R(2)(p) = 0.65) techniques. Accordingly, 96 lead compounds were generated based on a template molecule that showed the highest observed activity in vitro (T40, pIC(50) = 5.81) and predicted their activities and bioavailability in silico. The rational screening outputs of 3D-QSAR, Molecular docking, ADMET, and MM-GBSA led to the identification of 9 novel modeled molecules as potent noncovalent drugs against SARS-CoV-2-3CL(pro). Finally, by molecular dynamics simulations, the stability and structural dynamics of 3CL(pro) free and complex (PDB code: 6LU7) were discussed in the presence of samples of 9,10-dihydrophenanthrene derivative in an aqueous environment. Overall, the retrosynthesis of the proposed drug compounds in this study and the evaluation of their bioactivity in vitro and in vivo may be interesting for designing and discovering a new drug effective against COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11224-022-02004-z. |
format | Online Article Text |
id | pubmed-9261181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92611812022-07-07 Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach Daoui, Ossama Elkhattabi, Souad Chtita, Samir Struct Chem Original Research Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL(pro) and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmaceutical use against COVID-19. The objective of this study was to remodel the structures of 9,10-dihydrophenanthrene derivatives to achieve a powerful biological activity against 3CL(pro) and favorable pharmacokinetic properties for drug design and discovery. Therefore, by the use of bioinformatics techniques, we developed robust 3D-QSAR models that are capable of describing the structure–activity relationship for 46 molecules based on 9,10-dihydrophenanthrene derivatives using CoMFA/SE (R(2) = 0.97, Q(2) = 0.81, R(2)(pred) = 0.95, (c)R(2)(p) = 0.71) and CoMSIA/SEHDA (R(2) = 0.94, Q(2) = 0.76, R(2)(pred) = 0.91, (c)R(2)(p) = 0.65) techniques. Accordingly, 96 lead compounds were generated based on a template molecule that showed the highest observed activity in vitro (T40, pIC(50) = 5.81) and predicted their activities and bioavailability in silico. The rational screening outputs of 3D-QSAR, Molecular docking, ADMET, and MM-GBSA led to the identification of 9 novel modeled molecules as potent noncovalent drugs against SARS-CoV-2-3CL(pro). Finally, by molecular dynamics simulations, the stability and structural dynamics of 3CL(pro) free and complex (PDB code: 6LU7) were discussed in the presence of samples of 9,10-dihydrophenanthrene derivative in an aqueous environment. Overall, the retrosynthesis of the proposed drug compounds in this study and the evaluation of their bioactivity in vitro and in vivo may be interesting for designing and discovering a new drug effective against COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11224-022-02004-z. Springer US 2022-07-07 2022 /pmc/articles/PMC9261181/ /pubmed/35818588 http://dx.doi.org/10.1007/s11224-022-02004-z Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Daoui, Ossama Elkhattabi, Souad Chtita, Samir Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title | Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title_full | Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title_fullStr | Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title_full_unstemmed | Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title_short | Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CL(pro) enzyme for COVID-19 therapy: a computer-aided drug design approach |
title_sort | rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3cl(pro) enzyme for covid-19 therapy: a computer-aided drug design approach |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9261181/ https://www.ncbi.nlm.nih.gov/pubmed/35818588 http://dx.doi.org/10.1007/s11224-022-02004-z |
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