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Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach
[Image: see text] The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave t...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893467/ https://www.ncbi.nlm.nih.gov/pubmed/36743017 http://dx.doi.org/10.1021/acsomega.2c07585 |
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author | Daoui, Ossama Elkhattabi, Souad Bakhouch, Mohamed Belaidi, Salah Bhandare, Richie R. Shaik, Afzal B. Mali, Suraj N. Chtita, Samir |
author_facet | Daoui, Ossama Elkhattabi, Souad Bakhouch, Mohamed Belaidi, Salah Bhandare, Richie R. Shaik, Afzal B. Mali, Suraj N. Chtita, Samir |
author_sort | Daoui, Ossama |
collection | PubMed |
description | [Image: see text] The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure–activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch–bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug. |
format | Online Article Text |
id | pubmed-9893467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-98934672023-02-03 Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach Daoui, Ossama Elkhattabi, Souad Bakhouch, Mohamed Belaidi, Salah Bhandare, Richie R. Shaik, Afzal B. Mali, Suraj N. Chtita, Samir ACS Omega [Image: see text] The abnormal expression of the c-Met tyrosine kinase has been linked to the proliferation of several human cancer cell lines, including non-small-cell lung cancer (NSCLC). In this context, the identification of new c-Met inhibitors based on heterocyclic small molecules could pave the way for the development of a new cancer therapeutic pathway. Using multiple linear regression (MLR)-quantitative structure–activity relationship (QSAR) and artificial neural network (ANN)-QSAR modeling techniques, we look at the quantitative relationship between the biological inhibitory activity of 40 small molecules derived from cyclohexane-1,3-dione and their topological, physicochemical, and electronic properties against NSCLC cells. In this regard, screening methods based on QSAR modeling with density-functional theory (DFT) computations, in silico pharmacokinetic/pharmacodynamic (ADME-Tox) modeling, and molecular docking with molecular electrostatic potential (MEP) and molecular mechanics-generalized Born surface area (MM-GBSA) computations were used. Using physicochemical (stretch–bend, hydrogen bond acceptor, Connolly molecular area, polar surface area, total connectivity) and electronic (total energy, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels) molecular descriptors, compound 6d is identified as the optimal scaffold for drug design based on in silico screening tests. The computer-aided modeling developed in this study allowed us to design, optimize, and screen a new class of 36 small molecules based on cyclohexane-1,3-dione as potential c-Met inhibitors against NSCLC cell growth. The in silico rational drug design approach used in this study led to the identification of nine lead compounds for NSCLC therapy via c-Met protein targeting. Finally, the findings are validated using a 100 ns series of molecular dynamics simulations in an aqueous environment on c-Met free and complexed with samples of the proposed lead compounds and Foretinib drug. American Chemical Society 2023-01-19 /pmc/articles/PMC9893467/ /pubmed/36743017 http://dx.doi.org/10.1021/acsomega.2c07585 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Daoui, Ossama Elkhattabi, Souad Bakhouch, Mohamed Belaidi, Salah Bhandare, Richie R. Shaik, Afzal B. Mali, Suraj N. Chtita, Samir Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach |
title | Cyclohexane-1,3-dione
Derivatives as Future Therapeutic
Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and
Structure-Based Drug Designing Approach |
title_full | Cyclohexane-1,3-dione
Derivatives as Future Therapeutic
Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and
Structure-Based Drug Designing Approach |
title_fullStr | Cyclohexane-1,3-dione
Derivatives as Future Therapeutic
Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and
Structure-Based Drug Designing Approach |
title_full_unstemmed | Cyclohexane-1,3-dione
Derivatives as Future Therapeutic
Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and
Structure-Based Drug Designing Approach |
title_short | Cyclohexane-1,3-dione
Derivatives as Future Therapeutic
Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and
Structure-Based Drug Designing Approach |
title_sort | cyclohexane-1,3-dione
derivatives as future therapeutic
agents for nsclc: qsar modeling, in silico adme-tox properties, and
structure-based drug designing approach |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893467/ https://www.ncbi.nlm.nih.gov/pubmed/36743017 http://dx.doi.org/10.1021/acsomega.2c07585 |
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