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利用各种对齐方法研究 JNK1 抑制剂的 3D-QSAR。

3D-QSAR studies of JNK1 inhibitors utilizing various alignment methods.

机构信息

Department of Bio New Drug Development, College of Medicine, Chosun University, 375 Seosuk-dong, Dong-gu Gwangju, Korea.

出版信息

Chem Biol Drug Des. 2012 Jan;79(1):53-67. doi: 10.1111/j.1747-0285.2011.01168.x. Epub 2011 Nov 4.

DOI:10.1111/j.1747-0285.2011.01168.x
PMID:21722320
Abstract

We report our three-dimensional quantitative structure activity relationship (3D-QSAR) studies of the series of anilinopyrimidine derivatives of JNK1 inhibitors. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were applied using different alignment methods. The ligand-based atom-by-atom matching alignment has produced better values for CoMFA (q(2) = 0.646 and r(2) = 0.983), while in CoMSIA it has achieved only lower statistical values. The pharmacophore-based model has produced (q(2) = 0.568, r(2) = 0.938) and (q(2) = 0.670, r(2) = 0.982) for CoMFA and CoMSIA models, respectively. As the model was based on the receptor-guided alignment, all the compounds were optimized within the receptor, resulting in q(2) = 0.605 and r(2) = 0.944 for CoMFA, and q(2) = 0.587 and r(2) = 0.863 for CoMSIA. Molecular Dynamic simulation studies suggested that the generated models were consistent with the low-energy protein ligand conformation. The CoMFA and CoMSIA contour maps indicated that the substitutions of the electropositive groups in the phenyl ring, and an addition of hydrophobic groups in the pyrimidine ring, are important to enhance the activity of this series. Moreover, the virtual screening analysis against NCI database yields potentials hits, and the results obtained would be useful to synthesize selective and highly potent c-Jun N-terminal kinase 1 analogs.

摘要

我们报告了 JNK1 抑制剂系列苯胺嘧啶衍生物的三维定量构效关系(3D-QSAR)研究。采用不同的对齐方法进行了比较分子场分析(CoMFA)和比较分子相似性指数分析(CoMSIA)。基于配体的原子对原子匹配对齐方法产生了更好的 CoMFA 值(q²=0.646 和 r²=0.983),而在 CoMSIA 中仅达到了较低的统计值。基于药效团的模型分别产生了 CoMFA 和 CoMSIA 模型的(q²=0.568,r²=0.938)和(q²=0.670,r²=0.982)。由于该模型基于受体指导的对齐,所有化合物都在受体内部进行了优化,得到 CoMFA 的 q²=0.605 和 r²=0.944,CoMSIA 的 q²=0.587 和 r²=0.863。分子动力学模拟研究表明,生成的模型与低能量蛋白配体构象一致。CoMFA 和 CoMSIA 等高线图表明,苯环中正电性基团的取代以及嘧啶环中疏水基团的添加对于提高该系列的活性非常重要。此外,针对 NCI 数据库的虚拟筛选分析产生了潜在的命中化合物,这些结果对于合成选择性和高效的 c-Jun N-末端激酶 1 类似物将是有用的。

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