Combined 3D-QSAR modeling and molecular docking study on multi-acting quinazoline derivatives as HER2 kinase inhibitors
| العنوان: | Combined 3D-QSAR modeling and molecular docking study on multi-acting quinazoline derivatives as HER2 kinase inhibitors |
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| المؤلفون: | sako mirzaie, Monajjemi, M., Hakhamaneshi, M. S., Fathi, F., Jamalan, M. |
| المصدر: | EXCLI Journal Scopus-Elsevier |
| بيانات النشر: | Leibniz Research Centre for Working Environment and Human Factors, 2013. |
| سنة النشر: | 2013 |
| مصطلحات موضوعية: | self-organizing molecular field analysis, selforganizing molecular field analysis, human epidermal growth factor receptor 2, Original Article, AutoDock, quinazoline, 3D-QSAR |
| الوصف: | A series of new quinazoline derivatives has been recently reported as potent multi-acting histone deacetylase (HDAC), epidermal growth factor receptor (EGFR), and human epidermal growth factor receptor 2 (HER2) inhibitors. HER2 is one of the major targets for the treatment of breast cancer and other carcinomas. Three-dimensional structure-activity relationship (3DQSAR) is a well-known technique, which is used to drug design and development. This technique is used for quantitatively predicting the interaction between a molecule and the active site of a specific target. For each 3D-QSAR study, a three-dimensional model is created from a large curve fit to find a fitting between computational descriptors and biological activity. This model could be used as a predictive tool in drug design. The best model has the highest correlation between theoretical and experimental data. Self-Organizing Molecular Field Analysis (SOMFA), a grid-based and alignment-dependent 3D-QSAR method, is employed to study the correlation between the molecular properties and HER2 inhibitory potency of the quinazoline derivatives. Before presentation of inhibitor structures to SOMFA study, conformation of inhibitors was determined by AutoDock4, HyperChem and AutoDock Vina, separately. Overall, six independent models were produced and evaluated by the statistical partial least square (PLS) analysis. Among the several generated 3D-QSARs, the best model was selected on the basis of its statistical significance and predictive potential. The model derived from the superposition of docked conformation with AutoDock Vina with reasonable crossvalidated q2 (0.767), non cross-validated r2 (0.815) and F-test (97.22) values showed a desirable predictive capability. Analysis of SOMFA model could provide some useful information in the design of novel HER2 kinase inhibitors with better spectrum of activity. EXCLI Journal ; Vol. 12, 2013 |
| وصف الملف: | application/pdf |
| اللغة: | English |
| تدمد: | 1611-2156 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0ffd9d3d9e3584a17cff3f526cb8e4f http://europepmc.org/articles/PMC4531791 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....d0ffd9d3d9e3584a17cff3f526cb8e4f |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 16112156 |
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