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基于蒙特卡罗方法的马来酰亚胺衍生物作为糖原合酶激酶-3β抑制剂的定量构效关系建模。

Monte Carlo method based QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors.

机构信息

University of Niš, Faculty of Medicine, Department of Chemistry, Niš, Serbia.

University of Niš, Faculty of Medicine, Department of Chemistry, Niš, Serbia.

出版信息

Comput Biol Med. 2015 Sep;64:276-82. doi: 10.1016/j.compbiomed.2015.07.004. Epub 2015 Jul 16.

DOI:10.1016/j.compbiomed.2015.07.004
PMID:26257010
Abstract

The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and r(m)(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and r(m)(2)=0.8199 for the test and r(2)=0.8418, r(av)(m)(2)=0.7469 and ∆r(m)(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3β inhibitors has been presented by using defined structural alerts.

摘要

蒙特卡罗方法被用于建立作为糖原合酶激酶-3β抑制剂的马来酰亚胺衍生物的定量构效关系模型。第一个 QSAR 模型是为一系列 74 个 3-苯胺基-4-芳基马来酰亚胺衍生物开发的。第二个 QSAR 模型是为一系列 177 个马来酰亚胺衍生物开发的。QSAR 模型是通过简化分子输入线进样系统来表示分子结构进行计算的。已经检查了两个拆分:一个用于第一个 QSAR 模型的训练集和测试集的拆分,另一个用于第二个模型的训练集、测试集和验证集的拆分。所开发模型的统计质量非常好。为 3-苯胺基-4-芳基马来酰亚胺衍生物计算的模型具有以下统计参数:训练集的 r(2)=0.8617;测试集的 r(2)=0.8659 和 r(m)(2)=0.7361。为马来酰亚胺衍生物计算的模型具有以下统计参数:训练集的 r(2)=0.9435;测试集的 r(2)=0.9262 和 r(m)(2)=0.8199;验证集的 r(2)=0.8418、r(av)(m)(2)=0.7469 和 ∆r(m)(2)=0.1476。已经定义了被认为是增加和降低抑制活性的分子片段的结构指标。通过使用定义的结构警示,展示了新的潜在糖原合酶激酶-3β抑制剂的计算机辅助设计。

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