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首页> 外文期刊>Journal of enzyme inhibition and medicinal chemistry. >Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model
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Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model

机译:基于SVM,Pharmacore和对接模型的多级虚拟筛选方法鉴定新型CDK2抑制剂

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Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF) pharmacophore and docking was utilised for screening the CDK2 inhibitors. The evaluation of the validation set indicated that this method can be used to screen large chemical databases because it has a high hit-rate and enrichment factor (80.1% and 332.83 respectively). Six compounds were screened out from NCI, Enamine and Pubchem database. After molecular dynamics and binding free energy calculation, two compounds had great potential as novel CDK2 inhibitors and they also showed selective inhibition against CDK2 in the kinase activity assay.
机译:细胞周期蛋白依赖性激酶2(CDK2)是SER / THR蛋白激酶的系列,其作为具有低毒癌症治疗靶标的高度选择性的SER / THR蛋白激酶。通过SVM,蛋白质 - 配体相互作用指纹(PLIF)药长和对接组合的多级虚拟筛选方法用于筛选CDK2抑制剂。验证集的评估表明,该方法可用于筛选大化学数据库,因为它具有高次速率和富集因子(分别为80.1%和332.83)。从NCI,enamine和Pubchem数据库中筛选出六种化合物。在分子动力学和结合的自由能量计算之后,两种化合物具有很大的潜力作为新型CDK2抑制剂,并且它们还显示出对激酶活性测定中的CDK2的选择性抑制。

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