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In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations
The vascular endothelial growth factor receptor-2 kinases (VEGFR-2) expressed on tumor cells and vessels are attractive targets for cancer treatment. Potent inhibitors for the VEGFR-2 receptor are novel strategies to develop anti-cancer drugs. In this work, template ligand-based 3D-QSAR studies were...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The Royal Society of Chemistry
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184002/ https://www.ncbi.nlm.nih.gov/pubmed/37197188 http://dx.doi.org/10.1039/d3ra01316b |
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author | Jiang, Yuhan Yang, Wei Wang, Fangfang Zhou, Bo |
author_facet | Jiang, Yuhan Yang, Wei Wang, Fangfang Zhou, Bo |
author_sort | Jiang, Yuhan |
collection | PubMed |
description | The vascular endothelial growth factor receptor-2 kinases (VEGFR-2) expressed on tumor cells and vessels are attractive targets for cancer treatment. Potent inhibitors for the VEGFR-2 receptor are novel strategies to develop anti-cancer drugs. In this work, template ligand-based 3D-QSAR studies were performed on a series of benzoxazole derivatives toward different cell lines (HepG2, HCT-116 and MCF-7). Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques were used to generate 3D-QSAR models. Good predictability was derived for the optimal CoMFA models (HepG2: R(cv)(2) = 0.509, R(pred)(2) = 0.5128; HCT-116: R(cv)(2) = 0.574, R(pred)(2) = 0.5597; MCF-7: R(cv)(2) = 0.568, R(pred)(2) = 0.5057) and CoMSIA models (HepG2: R(cv)(2) = 0.711, R(pred)(2) = 0.6198; HCT-116: R(cv)(2) = 0.531, R(pred)(2) = 0.5804; MCF-7: R(cv)(2) = 0.669, R(pred)(2) = 0.6577). In addition, the contour maps derived from CoMFA and CoMSIA models were also generated to illustrate the relationship between different fields and the inhibitory activities. Moreover, molecular docking and molecular dynamics (MD) simulations were also conducted to understand the binding modes and the potential interactions between the receptor and the inhibitors. Some key residues (Leu35, Val43, Lys63, Leu84, Gly117, Leu180 and Asp191) were pointed out for stabilizing the inhibitors in the binding pocket. The binding free energies for the inhibitors agreed well with the experimental inhibitory activity and indicated that steric, electrostatic and hydrogen bond interactions are the main driving force for inhibitor-receptor binding. Overall, a good consistency between theoretical 3D-SQAR and molecular docking and MD simulation studies would provide directions for the design of new candidates, avoiding time-consuming and costly synthesis and biological evaluations. On the whole, the results derived from this study could expand the understanding of benzoxazole derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity targeting VEGFR-2. |
format | Online Article Text |
id | pubmed-10184002 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-101840022023-05-16 In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations Jiang, Yuhan Yang, Wei Wang, Fangfang Zhou, Bo RSC Adv Chemistry The vascular endothelial growth factor receptor-2 kinases (VEGFR-2) expressed on tumor cells and vessels are attractive targets for cancer treatment. Potent inhibitors for the VEGFR-2 receptor are novel strategies to develop anti-cancer drugs. In this work, template ligand-based 3D-QSAR studies were performed on a series of benzoxazole derivatives toward different cell lines (HepG2, HCT-116 and MCF-7). Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) techniques were used to generate 3D-QSAR models. Good predictability was derived for the optimal CoMFA models (HepG2: R(cv)(2) = 0.509, R(pred)(2) = 0.5128; HCT-116: R(cv)(2) = 0.574, R(pred)(2) = 0.5597; MCF-7: R(cv)(2) = 0.568, R(pred)(2) = 0.5057) and CoMSIA models (HepG2: R(cv)(2) = 0.711, R(pred)(2) = 0.6198; HCT-116: R(cv)(2) = 0.531, R(pred)(2) = 0.5804; MCF-7: R(cv)(2) = 0.669, R(pred)(2) = 0.6577). In addition, the contour maps derived from CoMFA and CoMSIA models were also generated to illustrate the relationship between different fields and the inhibitory activities. Moreover, molecular docking and molecular dynamics (MD) simulations were also conducted to understand the binding modes and the potential interactions between the receptor and the inhibitors. Some key residues (Leu35, Val43, Lys63, Leu84, Gly117, Leu180 and Asp191) were pointed out for stabilizing the inhibitors in the binding pocket. The binding free energies for the inhibitors agreed well with the experimental inhibitory activity and indicated that steric, electrostatic and hydrogen bond interactions are the main driving force for inhibitor-receptor binding. Overall, a good consistency between theoretical 3D-SQAR and molecular docking and MD simulation studies would provide directions for the design of new candidates, avoiding time-consuming and costly synthesis and biological evaluations. On the whole, the results derived from this study could expand the understanding of benzoxazole derivatives as anticancer agents and would be of great help in lead optimization for early drug discovery of highly potent anticancer activity targeting VEGFR-2. The Royal Society of Chemistry 2023-05-15 /pmc/articles/PMC10184002/ /pubmed/37197188 http://dx.doi.org/10.1039/d3ra01316b Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Jiang, Yuhan Yang, Wei Wang, Fangfang Zhou, Bo In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title |
In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title_full |
In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title_fullStr |
In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title_full_unstemmed |
In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title_short |
In silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3D-QSAR, molecular docking and molecular dynamics simulations |
title_sort | in silico studies of a novel scaffold of benzoxazole derivatives as anticancer agents by 3d-qsar, molecular docking and molecular dynamics simulations |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10184002/ https://www.ncbi.nlm.nih.gov/pubmed/37197188 http://dx.doi.org/10.1039/d3ra01316b |
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