首页> 外文期刊>American Journal of Pharmacological Sciences >Identification of Potential C-kit Protein Kinase Inhibitors Associated with Human Liver Cancer Atom-based 3D-QSAR Modeling, Pharmacophores-based Virtual Screening and Molecular Docking Studies
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Identification of Potential C-kit Protein Kinase Inhibitors Associated with Human Liver Cancer Atom-based 3D-QSAR Modeling, Pharmacophores-based Virtual Screening and Molecular Docking Studies

机译:鉴定潜在的C-kit蛋白激酶抑制剂与基于人肝癌原子的3D QSAR建模,基于药物的虚拟筛选和分子对接研究

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Rhodanine and its derivatives exhibit interesting biological activities as well as a wide range of biological applications. In this study, a dataset of seventy-four molecules with anticancer activities against human cancer cell line Huh-7D12, were chosen for the modeling of pharmacophores and Quantitative Structure Activity (3D-QSAR) relationship. Pharmacophoric models containing five sites were generated from three characteristics: hydrogen bond acceptor (A), hydrophobic (H) and aromatic ring (R). After the validation, eight hypotheses which presented a good power of selectivity of the active agents were selected (GH > 0.5). Internal and external validation parameters indicated that the generated 3D-QSAR model exhibits good predictive capabilities and significant statistical reliability (R2 = 0.9606, Q2 = 0.955, = 0.952). Pharmacophoric models and contour maps provided significant information on the main structural features of rhodanine derivatives. Twenty-one molecules were returned from the Enamine chemical database after molecular docking studies (HTVS, SP, XP, and IFD). These provided an estimate of ligand-protein binding interactions essential for anticancer activity. The ADMET prediction of these 21 compounds suggested that their pharmacophoric properties lie within an acceptable range. This result indicates that these new compounds provide an effective basis for the methodical development of potent inhibitors of the protein kinase C-kit.
机译:Rhodanine及其衍生物表现出有趣的生物活动以及广泛的生物应用。在该研究中,选择患有针对人癌细胞系HUH-7D12的抗癌活性的七十四个分子的数据集,用于药物和定量结构活性(3D-QSAR)关系。含有五个位点的药物模型由三种特征产生:氢键受体(A),疏水(H)和芳环(R)。在验证之后,选择呈现良好的选择性活性剂的八个假设(GH> 0.5)。内部和外部验证参数表明所生成的3D-QSAR模型具有良好的预测功能和显着的统计可靠性(R2 = 0.9606,Q2 = 0.955,= 0.952)。药片模型和轮廓图提供了有关Rhodanine衍生物的主要结构特征的重要信息。在分子对接研究(HTVS,SP,XP和IFD)后从烯胺化学数据库中返回二十一分子。这些提供了对抗癌活性必需的配体 - 蛋白结合相互作用的估计。对这些21种化合物的呼气预测表明,其药物性能位于可接受的范围内。该结果表明,这些新化合物提供了蛋白激酶C-kit的有效抑制剂的有效培养的有效依据。

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