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首页> 外文期刊>Journal of Computational Medicine >Combined 3D QSAR Based Virtual Screening and Molecular Docking Study of Some Selected PDK-1 Kinase Inhibitors
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Combined 3D QSAR Based Virtual Screening and Molecular Docking Study of Some Selected PDK-1 Kinase Inhibitors

机译:基于3D QSAR的组合虚拟筛选和分子对接研究某些PDK-1激酶抑制剂

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摘要

Phosphoinositide-dependent kinase-1 (PDK-1) is an important therapeutic target for the treatment of cancer. In order to identify the important chemical features of PDK-1 inhibitors, a 3D QSAR pharmacophore model was developed based on 21 available PDK-1 inhibitors. The best pharmacophore model (Hypo1) exhibits all the important chemical features required for PDK-1 inhibitors. The correlation coefficient, root mean square deviation (RMSD), and cost difference were 0.96906, 1.0719, and 168.13, respectively, suggesting a good predictive ability of the model (Hypo1) among all the ten pharmacophore models that were analyzed. The best pharmacophore model (Hypo1) was further validated by Fisher’s randomization method (95%), test set method(r=0.87), and the decoy set with the goodness of fit (0.73). Further, this validated pharmacophore model Hypo1 was used as a 3D query to screen the molecules from databases like NCI database and Maybridge. The resultant hit compounds were subsequently subjected to filtration by Lipinski’s rule of five as well as the ADMET study. Docking study was done to refine the retrieved hits and as a result to reduce the rate of false positive. Best hits will further be subjected to in vitro study in future.
机译:磷脂酰肌醇依赖性激酶-1(PDK-1)是治疗癌症的重要治疗靶标。为了鉴定PDK-1抑制剂的重要化学特征,基于21种可用的PDK-1抑制剂开发了3D QSAR药效团模型。最佳药效团模型(Hypo1)具有PDK-1抑制剂所需的所有重要化学特征。相关系数,均方根偏差(RMSD)和成本差异分别为0.96906、1.0719和168.13,表明在所分析的所有十个药效团模型中,该模型(Hypo1)的预测能力均良好。最佳药效基团模型(Hypo1)通过Fisher随机方法(95%),测试集方法(r = 0.87)和诱饵集具有拟合优度(0.73)进一步得到验证。此外,该经过验证的药效团模型Hypo1用作3D查询,可从NCI数据库和Maybridge等数据库中筛选分子。随后将所得的命中化合物按照Lipinski的5法则以及ADMET研究进行过滤。进行了对接研究,以完善检索到的匹配结果,从而降低了误报率。今后,最好的歌曲将进一步进行体外研究。

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