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首页> 外文期刊>Open Pharmaceutical Sciences Journal >Structural Features of Quercetin Derivatives by Using Pharmaco-phore Modeling Approach
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Structural Features of Quercetin Derivatives by Using Pharmaco-phore Modeling Approach

机译：药典建模方法研究槲皮素衍生物的结构特征

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Background: Quercetin which is a natural occurring flavonoid, exert a direct pro-apoptotic effect on tumor cells by blocking the growth of several cancer cell lines at different phases of the cell cycle. Quercetin derivatives have attracted considerable attention for their cytotoxity against human cancer cell lines. In this study the derivatives of Quercetin were used for docking followed by pharmacophore modeling for studying the 3D features and configurations responsible for biological activity of structurally diverse compounds.Objective: To develop a model which depicts the crucial structural features responsible for anti-lung cancer activities.Method: A robust pharmacophore developed for the receptor have been analyzed to identify potential areas of selectivity in the hyperspace of 3D pharmacophores that may lead to the discovery of anti-lung cancer drug or such compounds which could serve as templates for the design of new molecules as potential anti lung cancer agents.Results: The generated best pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of R~(2) = 0.86 for training set and R~(2) = 0.76 for the test set molecules. The Cross validation regression coefficient is Q~(2) = 0.84 for training set and Q~(2) = 0.5 for test set molecules.Conclusion: The R~(2) and Q~(2) reveals that pharmacophore model provide insights into the structural and chemical features of the EGFR inhibitors of Quercetin derivatives that can be used as lead compound for further synthesis as well as for screening other similar novel inhibitors of EGFR.
机译：背景：槲皮素是一种天然存在的类黄酮，通过在细胞周期的不同阶段阻断几种癌细胞系的生长，从而对肿瘤细胞产生直接的促凋亡作用。槲皮素衍生物由于其对人癌细胞系的细胞毒性而引起了相当大的关注。在这项研究中，槲皮素的衍生物用于对接，然后进行药效团建模，以研究负责结构多样化合物生物活性的3D特征和构型。目的：建立一个模型，描述负责抗肺癌活性的关键结构特征方法：已经分析了为受体开发的强大药效团，以识别3D药效团超空间中潜在的选择性区域，这可能会导致发现抗肺癌药物或此类化合物，这些化合物可作为设计新药的模板结果：生成的最佳药效基团假说产生了统计学上显着的3D-QSAR模型，训练集的相关系数为R〜（2）= 0.86，测试的相关系数为R〜（2）= 0.76设置分子。交叉验证回归系数对于训练集为Q〜（2）= 0.84，对于测试集分子为Q〜（2）= 0.5。结论：R〜（2）和Q〜（2）揭示了药效团模型提供了对槲皮素衍生物的EGFR抑制剂的结构和化学特性，可用作进一步合成以及筛选其他类似的EGFR新抑制剂的先导化合物。

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