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基于 QM/MM 的强效 B-Raf 抑制剂的 3D QSAR 模型。

QM/MM based 3D QSAR models for potent B-Raf inhibitors.

机构信息

Department of Biotechnology and Bioinformatics, Korea University, Jochiwon-Eup, Yeongi-Gun, Chungnam 339-700, Korea.

出版信息

J Comput Aided Mol Des. 2010 May;24(5):385-97. doi: 10.1007/s10822-010-9337-5. Epub 2010 Apr 1.

Abstract

Three dimensional (3D) quantitative structure-activity relationship studies of 37 B-Raf inhibitors, pyrazole-based derivatives, were performed. Based on the co-crystallized compound (PDB ID: 3D4Q), several alignment methods were utilized to derive reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models. Receptor-guided alignment with quantum mechanics/molecular mechanics (QM/MM) minimization led to the best CoMFA model (q (2) = 0.624, r (2) = 0.959). With the same alignment, a statistically reliable CoMSIA model with steric, H-bond acceptor, and hydrophobic fields was also derived (q (2) = 0.590, r (2) = 0.922). Both models were validated with an external test set, which gave satisfactory predictive r (2) values of 0.926 and 0.878, respectively. Contour maps from CoMFA and CoMSIA models revealed important structural features responsible for increasing biological activity within the active site and explained the correlation between biological activity and receptor-ligand interactions. New fragments were identified as building blocks which can replace R1-3 groups through combinatorial screening methods. By combining these fragments a compound with a high bioactivity level prediction was found. These results can offer useful information for the design of new B-Raf inhibitors.

摘要

对 37 种基于吡唑的 B-Raf 抑制剂进行了三维(3D)定量构效关系研究。基于共晶化合物(PDB ID:3D4Q),采用了几种对齐方法来推导出可靠的比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)模型。基于量子力学/分子力学(QM/MM)最小化的受体引导对齐产生了最佳的 CoMFA 模型(q 2 = 0.624,r 2 = 0.959)。通过相同的对齐方式,还推导出了一个具有空间、氢键接受体和疏水场的统计学上可靠的 CoMSIA 模型(q 2 = 0.590,r 2 = 0.922)。这两个模型都通过外部测试集进行了验证,分别给出了令人满意的预测 r 2 值 0.926 和 0.878。CoMFA 和 CoMSIA 模型的等高线图揭示了负责增加活性部位内生物活性的重要结构特征,并解释了生物活性与受体-配体相互作用之间的相关性。通过组合筛选方法,鉴定出了一些新的片段作为构建块,可以取代 R1-3 基团。通过组合这些片段,发现了一种具有高生物活性水平预测的化合物。这些结果可为设计新型 B-Raf 抑制剂提供有用信息。

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