...
首页> 外文期刊>Journal of theoretical & computational chemistry >Pharmacophore modeling, 3D-QSAR and molecular docking studies of quinazolines and aminopyridines as selective inhibitors of inducible nitric oxide synthase
【24h】

Pharmacophore modeling, 3D-QSAR and molecular docking studies of quinazolines and aminopyridines as selective inhibitors of inducible nitric oxide synthase

机译:喹唑啉和氨基吡啶的3D-QSAR和氨基吡啶作为诱导型一氧化氮合酶选择性抑制剂

获取原文
获取原文并翻译 | 示例

摘要

Pharmacophore modeling and 3D-Quantitative Structure Activity Relationship (3D-QSAR) studies have been performed on a dataset of thirty-two quinazoline and aminopyridine derivatives to get an insight into the important structural features required for binding to inducible nitric oxide synthase (iNOS). A four-point CPH (Common Pharmacophore Hypothesis), AHPR.29, with a hydrogen bond acceptor, hydrophobic group, positively charged ionizable group and an aromatic ring, has been obtained as the best pharmacophore model. Satisfactory statistical parameters of correlation (R-2) and cross-validated (Q(2)) correlation coefficients, 0.9288 and 0.6353, respectively, show high robustness and good predictive ability of our selected model. The contour maps have been developed from this model and the analysis has provided an interpretable explanation of the effect that various features and substituents have on the potency and selectivity of inhibitors towards iNOS. Docking studies have also been performed in order to analyze the interactions between the enzyme and the inhibitors. Our proposed model can thus be further used for screening a large database of compounds and design new iNOS inhibitors.
机译:Pharmacophore建模和3D定量结构活动关系(3D-QSAR)研究已经在三十二喹唑啉和氨基吡啶衍生物的数据集上进行,以了解与诱导型一氧化氮合酶(InOS)结合所需的重要结构特征。已经获得了四分之四的CPH(常见的药仔植物假说),AHPR.29,具有氢粘合受体,疏水基团,带正电的可电离基团和芳环,作为最佳的药效线模型。相关性(R-2)和交叉验证(Q(2))相关系数,0.9288和0.6353的令人满意的统计参数分别显示出我们所选模型的高稳健性和良好的预测能力。从该模型中开发了轮廓图,分析提供了一种可解释的解释,即各种特征和取代基对INOS的抑制剂的效力和选择性的影响。还已经进行了对接研究以分析酶与抑制剂之间的相互作用。因此,我们所提出的模型可以进一步用于筛选大型化合物和设计新的InOS抑制剂。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号