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Pharmacophore Refinement and 3D-QSAR Studies of Histamine H_3 Antagonists

机译:组胺H_3拮抗剂的药理学提炼和3D-QSAR研究

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摘要

Molecular modeling studies were performed to develop a predictive Common Pharmacophore Hypothesis (CPH) and use it for alignment in 3D-QSAR studies using CoMFA and CoMSIA, with a diverse set of 106 histamine H_3 antagonists. A five point CPH with three hydrophobic features, a basic or positive ionizable feature and an acceptor, for pharmacophore-based alignment of molecules, was derived using PHASE. This hypothesis was selected from a pool, by correlating the observed and estimated activity for the training set and test set of molecules using partial least square analysis. It was found to be comparable to the previously reported hypothesis. The validated pharmacophore hypothesis was used for alignment of molecules in CoMFA and CoMSIA model development. The models so generated showed a good "predictive" r~2 value of 0.763 and 0.820 for CoMFA and CoMSIA, respectively. The contour maps of the models were analyzed to give structural insight for activity improvement of future novel histamine H_3 antagonists. The CPH can also provide a powerful template for virtual screening and design of new histamine H_3 antagonists.
机译:进行了分子建模研究,以开发预测性的通用药理假设(CPH),并将其用于使用CoMFA和CoMSIA以及3种106种组胺H_3拮抗剂的3D-QSAR研究中的比对。使用PHASE推导了具有三个疏水性特征(碱性或正离子性特征和受体)的五点CPH,用于基于药效团的分子比对。通过使用偏最小二乘分析将分子的训练集和测试集的观察到的活动和估计的活动进行关联,从一个集合中选择此假设。发现它与先前报道的假设具有可比性。经过验证的药效基团假说用于CoMFA和CoMSIA模型开发中的分子比对。这样生成的模型对于CoMFA和CoMSIA分别显示出良好的“预测” r〜2值,分别为0.763和0.820。分析了模型的轮廓图,从而为未来新型组胺H_3拮抗剂的活性改善提供了结构上的见识。 CPH还可以为虚拟筛选和设计新的组胺H_3拮抗剂提供强大的模板。

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