COMBINED 3D-QSAR MODELING AND MOLECULAR DOCKING STUDY ON MULTI-ACTING QUINAZOLINE DERIVATIVES AS HER2 KINASE INHIBITORS
Yazarlar (5)
Sako Mirzaie Islamic Azad University, Science And Research Branch, İran
Prof. Dr. Majıd MONAJJEMI Islamic Azad University, Science And Research Branch, İran
Mohammad Saeed Hakhamaneshi Kurdistan University Of Medical Sciences, İran
Fardin Fathi Kurdistan University Of Medical Sciences, İran
Mostafa Jamalan Islamic Azad University, Science And Research Branch, İran
Makale Türü Özgün Makale (ESCI dergilerinde yayınlanan tam makale)
Dergi Adı Excli Journal
Dergi ISSN 1611-2156 Wos Dergi Scopus Dergi
Makale Dili İngilizce Basım Tarihi 01-2013
Cilt / Sayı / Sayfa 12 / 1 / 130–143 DOI
Makale Linki http://www.scopus.com/inward/record.url?eid=2-s2.0-84874381378&partnerID=MN8TOARS
Özet
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.
Anahtar Kelimeler
3D-QSAR | AutoDock | Human epidermal growth factor receptor 2 | Quinazoline | Selforganizing molecular field analysis
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Web of Science 14
Scopus 19

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