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吡啶取代嘧啶类Mer激酶抑制剂的3D-QSAR建模与分子对接研究

3D-QSAR modeling and molecular docking study on Mer kinase inhibitors of pyridine-substituted pyrimidines.

作者信息

Yu Zhuang, Li Xianchao, Ge Cuizhu, Si Hongzong, Cui Lianhua, Gao Hua, Duan Yunbo, Zhai Honglin

机构信息

Department of Oncology, The Affiliated Hospital of Medical College Qingdao University, Qingdao University, Qingdao, 266071, Shandong, China,

出版信息

Mol Divers. 2015 Feb;19(1):135-47. doi: 10.1007/s11030-014-9556-0. Epub 2014 Oct 30.

Abstract

Mer kinase is a novel therapeutic target for many cancers, and overexpression of Mer receptor tyrosine kinase has been observed in several kinds of tumors. To deeply understand the structure-activity correlation of a series of pyridine/pyrimidine analogs as potent Mer inhibitors, a combined molecular docking and three-dimensional quantitative structure-activity relationship modeling was carried out. A comparative molecular similarity indices analysis model was developed based on the maximum common substructure alignment. The optimum model exhibited statistically significant results: the cross-validated correlation coefficient q2 was 0.599, and non-cross-validated r2 value was 0.984. Furthermore, the results of internal validation such as bootstrapping, Y-randomization as well as external validation (the external predictive correlation coefficient r2 ext = 0.728) confirmed the rationality and good predictive ability of the model. Using the crystal structure of Mer kinase, the selected pyridine/pyrimidine compounds were docked into the enzyme active site. Some key amino acid residues were determined, and hydrogen bonding and hydrophobic interactions between Mer kinase and inhibitors were identified. The satisfactory results from this study may aid in the research and development of novel potent Mer kinase inhibitors.

摘要

Mer激酶是多种癌症的新型治疗靶点,在几种肿瘤中已观察到Mer受体酪氨酸激酶的过表达。为深入了解一系列吡啶/嘧啶类似物作为强效Mer抑制剂的构效关系,开展了分子对接和三维定量构效关系建模相结合的研究。基于最大公共子结构比对建立了比较分子相似性指数分析模型。最佳模型显示出具有统计学意义的结果:交叉验证相关系数q2为0.599,非交叉验证r2值为0.984。此外,自举法、Y随机化等内部验证结果以及外部验证(外部预测相关系数r2 ext = 0.728)证实了该模型的合理性和良好的预测能力。利用Mer激酶的晶体结构,将所选的吡啶/嘧啶化合物对接至酶活性位点。确定了一些关键氨基酸残基,并识别出Mer激酶与抑制剂之间的氢键和疏水相互作用。本研究获得的满意结果可能有助于新型强效Mer激酶抑制剂的研发。

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