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靛玉红类CDK1抑制剂的同源模建、分子对接及3D-QSAR研究 被引量:17

Homology Modeling, Molecular Docking, and 3D-QSAR of Indirubin Analogues as CDK1 Inhibitors
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摘要 细胞周期蛋白依赖性激酶1的异常表达会导致G2期的停滞及多种肿瘤的发生,故CDK1近年来已成为一个理想的治疗靶点.本文以细胞分裂调控蛋白2的同源体为模板,同源模建了CDK1的结构,并与靛玉红类小分子抑制剂进行分子对接.分别运用三种叠合方法进行分子叠合,并在此基础上采用Sybyl 7.1中的比较分子场分析(CoMFA)模块及Discovery Studio 3.0中的三维定量构效关系(3D-QSAR)模块(以下简称为DS)分别建立了3D-QSAR模型.其中,将分子对接叠合与公共骨架叠合联合运用的叠合方法所得3D-QSAR模型的评价参数是最佳的(CoMFA:q2=0.681,r2=0.909,r2pred.=0.836;DS:q2=0.579,r2=0.971,r2pred.=0.795,其中q2为交叉验证系数,r2为非交叉验证系数).本文的研究结果在对靛玉红类小分子进行结构修饰设计出新的CDK1抑制剂方面,可提供重要的理论基础. The abnormal expression of cyclin-dependent kinase 1 (CDK1) leads to stagnation of the G2 phase and a variety of tumors. Therefore, CDK1 has been reported recently as an ideal cell cycle target for cancer drug discovery. In this paper, we use the cell division control protein 2 homolog as a template to homologically model the protein of CDK1 that is subsequently docked with the inhibitors of indirubin analogues. Three molecular alignment methods were used, and the corresponding three-dimensional quantitative structure-activity relationship (3D-QSAR) models were built using the comparative molecular field analysis (CoMFA) protocol in Sybyl 7.1 and the 3D-QSAR protocol (abbreviated for DS) in Discovery Studio 3.0. It was found that the molecular alignment method combining molecular docking with public template is most suitable for building the 3D-QSAR models, and shows the best calculated results (CoMFA: q^2=0.681, P=0.909, and r^2 =0.836; DS: q^2= 0.579, r^2=0.971, and r^pred =0.795, where q^2 denotes the cross-validated correlation coefficient and r^2 denotes the non-cross-validated correlation coefficient). This paper may provide significant theoretical foundation for designing novel CDK1 inhibitors by carrying out structural modifications of indirubin analogues.
出处 《物理化学学报》 SCIE CAS CSCD 北大核心 2014年第2期371-381,共11页 Acta Physico-Chimica Sinica
基金 国家"重大新药创制"科技重大专项(2009ZX09103-149)资助~~
关键词 细胞周期蛋白依赖性激酶1 靛玉红 3D-QSAR 比较分子场分析 同源模建 Cyclin-dependentkinase 1 Indirubin 3D-QSAR CoMFA Homology modeling
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