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嘧啶、噻吩并吡啶和脲基噻吩甲酰胺类细胞周期检查点激酶 1 抑制剂的结构要求:定量构效关系、对接、分子动力学分析。

Structural requirements of pyrimidine, thienopyridine and ureido thiophene carboxamide-based inhibitors of the checkpoint kinase 1: QSAR, docking, molecular dynamics analysis.

机构信息

Bioinformatics Center, Northwest A&F University, Yangling, Shaanxi 712100, China.

出版信息

J Mol Model. 2012 Jul;18(7):3227-42. doi: 10.1007/s00894-011-1321-z. Epub 2012 Jan 15.

DOI:10.1007/s00894-011-1321-z
PMID:22246285
Abstract

Our focus of current research is directed toward clarification of novel inhibitors (pyrazolo[1,5-a] pyrimidine (PP), thienopyridines (TP) and 2-ureido thiophene carboxamide (UTC) derivatives) targeting Checkpoint kinase 1 (CHK(1)), which is an oncology target of significant current interest. Our computational approaches include: (i) QSAR analysis was carried out on the computed steric/electrostatic/hydrophobic/hydrogen bond donor/hydrogen bond acceptor interactions with the pseudoreceptor surface, which yielded predictive models capable of explaining much of the variance of inhibitors. The resultant optimum QSAR/CoMFA models exhibited (N(training) = 51, N(test) = 16, R(cv) (2) = 0.47, R(pred) (2) = 0.7) for PP, (N(training) = 45, N(test) = 9, R(cv) (2) = 0.52, R(pred) (2) = 0.75) for TP and (N(training) = 58, N(test) = 15, R(cv) (2) = 0.67, R(pred) (2) = 0.88) for UTC. (ii) Molecular docking and molecular dynamics simulations experiments of the inhibitors into the binding site of CHK(1) aided the interpretation of the QSAR models and demonstrated the binding modes in the aspects of inhibitor's conformation, subsite interaction, and hydrogen bonding interactions, which indicated that a set of critical residues (Cys87, Glu91, Glu85, Ser147, Asp148, Glu17, Leu84 and Asn135) played a key role in the drug-target interactions. The obtained results in the present work will be fruitful for the design of new potent and selective inhibitors of CHK(1).

摘要

我们目前的研究重点是阐明针对细胞周期检查点激酶 1(CHK(1))的新型抑制剂(吡唑并[1,5-a]嘧啶(PP)、噻吩并吡啶(TP)和 2-脒基噻吩甲酰胺(UTC)衍生物),CHK(1) 是当前具有重要研究意义的肿瘤靶点。我们的计算方法包括:(i)对计算得出的与伪受体表面的立体/静电/疏水/氢键供体/氢键受体相互作用进行了定量构效关系(QSAR)分析,得到了能够解释大部分抑制剂变异性的预测模型。所得最佳 QSAR/CoMFA 模型分别对 PP(N(training) = 51,N(test) = 16,R(cv) (2) = 0.47,R(pred) (2) = 0.7)、TP(N(training) = 45,N(test) = 9,R(cv) (2) = 0.52,R(pred) (2) = 0.75)和 UTC(N(training) = 58,N(test) = 15,R(cv) (2) = 0.67,R(pred) (2) = 0.88)具有良好的预测能力。(ii)抑制剂与 CHK(1) 结合位点的分子对接和分子动力学模拟实验有助于解释 QSAR 模型,并从抑制剂构象、亚位点相互作用和氢键相互作用等方面展示了结合模式,表明一组关键残基(Cys87、Glu91、Glu85、Ser147、Asp148、Glu17、Leu84 和 Asn135)在药物-靶标相互作用中发挥了关键作用。本工作获得的结果将为设计新型有效的 CHK(1) 选择性抑制剂提供有益的信息。

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