ArticleActa pharmacologica Sinica2014
Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors.
Article in Acta pharmacologica Sinica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Quantitative structure-activity relationship and ADME prediction studies on series of spirooxindoles derivatives forHeliyon · 2024Article
- Drug design by machine-trained elastic networks: predicting Ser/Thr-protein kinase inhibitors' activities.Molecular diversity · 2021Article
- Synthesis and pharmacological evaluation of novel epidermal growth factor receptor inhibitors against prostate tumor cells.Oncology letters · 2018Article
- Screening of multi-targeted natural compounds for receptor tyrosine kinases inhibitors and biological evaluation on cancer cell lines, in silico and in vitro.Medical oncology (Northwood, London, England) · 2015Article
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7 authors.
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Abstract
aimTo develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors.
methodsOne hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures.
resultsCompared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands.
conclusionThe novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.
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