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源自不同类型抑制剂的法尼基转移酶药效团模型。

Farnesyltransferase pharmacophore model derived from diverse classes of inhibitors.

作者信息

Lu Aijun, Zhang Jian, Yin Xiaojin, Luo Xiaomin, Jiang Hualiang

机构信息

JiangSu Simcere Pharmaceutical Research Company Ltd. 210042 Nanjing, China.

出版信息

Bioorg Med Chem Lett. 2007 Jan 1;17(1):243-9. doi: 10.1016/j.bmcl.2006.09.055. Epub 2006 Oct 17.

Abstract

A three-dimensional pharmacophore model was developed based on 25 currently available inhibitors, which were carefully selected with great diversity in both molecular structure and bioactivity as required by HypoGen program in the Catalyst software, for discovering new farnesyltransferase (FTase) inhibitors. The best hypothesis (Hypo1), consisting of four features, namely, two hydrogen-bond acceptors, one hydrophobic point, and one ring aromatic feature, has a correlation coefficient of 0.949, a root-mean-square deviation of 1.321, and a cost difference of 163.15, suggesting that a highly predictive pharmacophore model was successfully obtained. The application of the model shows great success in predicting the activities of 227 known FTase inhibitors in our test set with a correlation coefficient of 0.776 with a cross-validation of 98% confidence level. Accordingly, our model should be reliable in identifying structurally diverse compounds with desired biological activity.

摘要

基于25种现有的抑制剂构建了一个三维药效团模型,这些抑制剂是根据Catalyst软件中HypoGen程序的要求,在分子结构和生物活性方面进行了精心挑选,以具有高度多样性,用于发现新的法尼基转移酶(FTase)抑制剂。最佳假设(Hypo1)由四个特征组成,即两个氢键受体、一个疏水点和一个环状芳香特征,其相关系数为0.949,均方根偏差为1.321,成本差异为163.15,表明成功获得了一个具有高度预测性的药效团模型。该模型的应用在预测我们测试集中227种已知FTase抑制剂的活性方面取得了巨大成功,相关系数为0.776,交叉验证的置信水平为98%。因此,我们的模型在识别具有所需生物活性的结构多样的化合物方面应该是可靠的。

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