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首页> 外文期刊>Indian drugs >PREDICTIVE QSAR MODELING OF PYRIDAZINYL DERIVATIVES USING K-NEAREST NEIGHBOR AND PHARMACOPHORE APPROACH
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PREDICTIVE QSAR MODELING OF PYRIDAZINYL DERIVATIVES USING K-NEAREST NEIGHBOR AND PHARMACOPHORE APPROACH

机译:用K最近邻和药效线方法预测吡啶基衍生物的QSAR模型

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摘要

This study was carried out elucidate the structural properties required for pyridazinyl derivatives to exhibit angiotensin II receptor activity. The best 2D-QSAR model was selected, having correlation coefficient r2 = 0.8156, cross validated squared correlation coefficient q2 = 0.7348 and predictive ability of the selected model was also confirmed by leave one out cross validation method. Further analysis was carried out using 3D-QSAR method k-nearest neighbor molecular field analysis approach; a leave-one-out cross-validated correlation coefficient of 0.7188 and a predictivity for the external test set (0.7613) were obtained. By studying the QSAR models, one can select the suitable substituent for active compound with maximum potency.
机译:进行该研究阐明吡啶基衍生物表现出血管紧张素II受体活性所需的结构性。 选择了最佳的2D-QSAR模型,具有相关系数R2 = 0.8156,交叉验证的平方相关系数Q2 = 0.7348以及所选模型的预测能力也通过留出一个外交叉验证方法来确认。 通过3D-QSAR方法K-Collest邻分子场分析方法进行进一步分析; 获得0.7188的休留交叉验证相关系数和外部测试组(0.7613)的预测性。 通过研究QSAR模型,可以选择具有最大效力的活性化合物的合适取代基。

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