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首页> 外文期刊>Medicinal Chemistry Research >Insight into the structural requirement of aryltriazolinone derivatives as angiotensin II AT1 receptor: 2D and 3D-QSAR k-Nearest Neighbor Molecular Field Analysis approach
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Insight into the structural requirement of aryltriazolinone derivatives as angiotensin II AT1 receptor: 2D and 3D-QSAR k-Nearest Neighbor Molecular Field Analysis approach

机译:深入了解芳基三唑啉酮衍生物作为血管紧张素II AT1 受体的结构要求:2D和3D-QSAR k最近邻分子场分析方法

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Quantitative structure–activity relationship (QSAR) studies were carried out on a series of 48 recently synthesised N 2-aryltriazolinone biphenyl sulphonamides derivatives to investigate the structural requirements of their inhibitory activities against angiotensin II AT1 receptor. Partial least square (PLS) methodology coupled with various feature selection methods, viz. stepwise (SW), genetic algorithm, and simulated annealing, was applied to derive QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The statistically significant best 2D-QSAR model having correlation coefficient r 2 = 0.8456 and cross-validated squared correlation coefficient q 2 = 0.7359 with external predictive ability of pred_r 2 = 0.8142 and pred_r 2se = 0.2817 was developed by SW–PLS with the descriptors like T_O_O_2, slogp, T_N_F_4, H-acceptor count, and Chi3cluster. Molecular field analysis was used to construct the best 3D-QSAR model using SW–PLS method, showing good correlative and predictive capabilities in terms of q 2 = 0.8201 and pred_r 2 = 0.7894. The steric, electrostatic, and hydrophobic descriptors at the grid points S_837, S_1010, E_940, E_285, E_1143, and H_903 play an important role in the design of new molecule. The results of this study may be useful on the designing of more potent analogs as antihypertensive agents.
机译:对一系列最近合成的48种N 2 -芳基三唑啉酮联苯磺酰胺衍生物进行了定量构效关系研究,以研究其对血管紧张素II AT1受体抑制活性的结构要求。偏最小二乘(PLS)方法结合各种特征选择方法,即。应用逐步算法(SW),遗传算法和模拟退火算法,得出QSAR模型,并通过内部和外部验证进一步验证了QSAR模型的统计意义和预测能力。具有相关系数r 2 = 0.8456和交叉验证平方相关系数q 2 = 0.7359且具有外部预测能力pred_r 2 = 0.8142和pred_r 2的具有统计学意义的最佳2D-QSAR模型 se = 0.2817由SW–PLS开发,其描述符包括T_O_O_2,slogp,T_N_F_4,H受体数和Chi3cluster。分子场分析被用来建立最好的3D-QSAR模型,采用SW–PLS方法,在q 2 = 0.8201和pred_r 2 = 0.7894方面表现出良好的相关性和预测能力。网格点S_837,S_1010,E_940,E_285,E_1143和H_903的空间,静电和疏水描述符在新分子的设计中起着重要作用。这项研究的结果可能对设计更有效的类似物作为降压药有用。

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