文献类型：期刊文献

中文题名：Structure-based ensemble-QSAR model： a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

英文题名：Structure-based ensemble-QSAR model： a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

作者：Xian-qiang SUN[1,2];Lei CHEN[1];Yao-zong LI[1,3];Wei-hua LI[1];Gui-xia LIU[1];Yao-quan TU[2];Yun TANG[1]

机构：[1]Shanghai Key Laboratory of New Drug Design, School ofPharmacy, East China University of Science and Technology, Shanghai 200237, China;[2]Division of Theoretical Chemistry and Biology, School of Biotechnology, KTH Royal Institute of Technology, S-106 91 Stockholm, Sweden;[3]Department of Chemistry, Ume& University, S-90187 Ume&, Sweden

年份：2014

卷号：35

期号：2

起止页码：301

中文期刊名：Acta Pharmacologica Sinica

外文期刊名：中国药理学报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2013_2014】；PubMed;

语种：英文

中文关键词：epidermal growth factor receptor; tyrosine kinase; ensemble docking; ensemble-QSAR; drug design

外文关键词：epidermal growth factor receptor; tyrosine kinase; ensemble docking; ensemble-QSAR; drug design

摘要：Aim： To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase （EGFR TK） and its inhibi- tors. Methods： One 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 conforma- tions determined by the corresponding protein structures. Results： Compared 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. Conclusion： The 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.
Aim： To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase （EGFR TK） and its inhibi- tors. Methods： One 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 conforma- tions determined by the corresponding protein structures. Results： Compared 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. Conclusion： The 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.