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基于改进的多元自适应回归样条法和比较分子相似性指数分析法的布鲁顿酪氨酸激酶抑制剂定量构效关系研究

Quantitative structure-activity relationship study on BTK inhibitors by modified multivariate adaptive regression spline and CoMSIA methods.

作者信息

Xu A, Zhang Y, Ran T, Liu H, Lu S, Xu J, Xiong X, Jiang Y, Lu T, Chen Y

机构信息

a Laboratory of Molecular Design and Drug Discovery, School of Basic Science , China Pharmaceutical University , Nanjing , Jiangsu , P.R. China.

出版信息

SAR QSAR Environ Res. 2015;26(4):279-300. doi: 10.1080/1062936X.2015.1032346. Epub 2015 Apr 23.

Abstract

Bruton's tyrosine kinase (BTK) plays a crucial role in B-cell activation and development, and has emerged as a new molecular target for the treatment of autoimmune diseases and B-cell malignancies. In this study, two- and three-dimensional quantitative structure-activity relationship (2D and 3D-QSAR) analyses were performed on a series of pyridine and pyrimidine-based BTK inhibitors by means of genetic algorithm optimized multivariate adaptive regression spline (GA-MARS) and comparative molecular similarity index analysis (CoMSIA) methods. Here, we propose a modified MARS algorithm to develop 2D-QSAR models. The top ranked models showed satisfactory statistical results (2D-QSAR: Q(2) = 0.884, r(2) = 0.929, r(2)pred = 0.878; 3D-QSAR: q(2) = 0.616, r(2) = 0.987, r(2)pred = 0.905). Key descriptors selected by 2D-QSAR were in good agreement with the conclusions of 3D-QSAR, and the 3D-CoMSIA contour maps facilitated interpretation of the structure-activity relationship. A new molecular database was generated by molecular fragment replacement (MFR) and further evaluated with GA-MARS and CoMSIA prediction. Twenty-five pyridine and pyrimidine derivatives as novel potential BTK inhibitors were finally selected for further study. These results also demonstrated that our method can be a very efficient tool for the discovery of novel potent BTK inhibitors.

摘要

布鲁顿酪氨酸激酶(BTK)在B细胞活化和发育中起关键作用,并已成为治疗自身免疫性疾病和B细胞恶性肿瘤的新分子靶点。在本研究中,通过遗传算法优化的多元自适应回归样条(GA-MARS)和比较分子相似性指数分析(CoMSIA)方法,对一系列基于吡啶和嘧啶的BTK抑制剂进行了二维和三维定量构效关系(2D和3D-QSAR)分析。在此,我们提出一种改进的MARS算法来建立2D-QSAR模型。排名靠前的模型显示出令人满意的统计结果(2D-QSAR:Q(2)=0.884,r(2)=0.929,r(2)pred=0.878;3D-QSAR:q(2)=0.616,r(2)=0.987,r(2)pred=0.905)。2D-QSAR选择的关键描述符与3D-QSAR的结论高度一致,并且3D-CoMSIA等高线图有助于解释构效关系。通过分子片段替换(MFR)生成了一个新的分子数据库,并进一步用GA-MARS和CoMSIA预测进行评估。最终选择了25种吡啶和嘧啶衍生物作为新型潜在的BTK抑制剂进行进一步研究。这些结果还表明,我们的方法可以成为发现新型强效BTK抑制剂的非常有效的工具。

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