李志良, 胡芳, 梁本熹, 余虎, 石乐明, 李梦龙, 酒井诚. 神经网络用于环丙胺类衍生物的构效关系研究J. 药学学报, 1996, 31(1): 38-42.
引用本文: 李志良, 胡芳, 梁本熹, 余虎, 石乐明, 李梦龙, 酒井诚. 神经网络用于环丙胺类衍生物的构效关系研究J. 药学学报, 1996, 31(1): 38-42.
ZL Li, F Hu, BX Liang, H Yu, ML Li, LM Shi , M Sakai, . NEURAL NETWORKS IN QSAR STUDIES:ESTIMATION AND PREDICTION OF BIOLOGICAL ACTIVITY FOR N-(SUBSTITUTED PHENOXYETHYL)-CYCLOPROPYLAMINESJ. Acta Pharmaceutica Sinica, 1996, 31(1): 38-42.
Citation: ZL Li, F Hu, BX Liang, H Yu, ML Li, LM Shi , M Sakai, . NEURAL NETWORKS IN QSAR STUDIES:ESTIMATION AND PREDICTION OF BIOLOGICAL ACTIVITY FOR N-(SUBSTITUTED PHENOXYETHYL)-CYCLOPROPYLAMINESJ. Acta Pharmaceutica Sinica, 1996, 31(1): 38-42.

神经网络用于环丙胺类衍生物的构效关系研究

NEURAL NETWORKS IN QSAR STUDIES:ESTIMATION AND PREDICTION OF BIOLOGICAL ACTIVITY FOR N-(SUBSTITUTED PHENOXYETHYL)-CYCLOPROPYLAMINES

  • 摘要: 将神经网络应用于定量构效关系研究。用改进的反传算法探讨了单胺氧化酶抑制剂N-(苯氧乙基)环丙胺取代衍生物的生物活性与取代基电子效应σ、疏水作用π、空间效应Es等参数之间的定量关系。给出了精密拟合和准确预测(最大误差均小于10%),优于经典的多元线性回归及逐步回归方法。作为一种有效的计量化学新方法,神经网络有良好的预测能力和非线性处理功能,从而可望在QSAR研究中发挥重要作用。

     

    Abstract: Neural networks(NN)methods were applied to quantitative structure-activity relationship(QSAR)studies.The relationship between biological activity(pC=pIC50)and electronic,hydrophobic and steric parameters and dumming index(sigma,pi,Es,was investigated by usingmodified backpropagation(MBP)neural networks.The biological activity of N-(substitutedphenoxyethyl)-cyclopropylamines derivative regression was estimated and predicted with relative errorless than 16%and with correct classification ratio being 94.4%,The results obtained by thedeveloped NN(MBP)method seem to be better than those by multivariate regression(MR)and step-wise regression(SR).The NN(MBP)method was,therefore,regarded as an excellent chemometricmedeling technique for estimating and predicting biological activity on basis of chemical structure forQSAR studies。

     

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