| 用神经网络法预测药物在体透过人皮肤的渗透性 |
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| 引用本文： | 傅旭春. 用神经网络法预测药物在体透过人皮肤的渗透性[J]. 浙江大学学报(医学版), 2003, 32(2): 152-154,158 |
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| 作者姓名： | 傅旭春 |
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| 作者单位： | 浙江大学城市学院药学系,浙江,杭州,310015 |
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| 摘 要： | 目的：预测药物在体透过人皮肤的渗透性。方法：以正辛醇／水分配系数(logP)、分子体积(V)、氢键酸度(∑β2^H)和氢键碱度(∑β2^H)等理化参数作为输入层神经元，以药物在一定时间内在体透过人皮肤的透过比的对数值(R，透过量／未透过量)作为输出层神经元，建立起合适的BP(Back—propagation)神经网络。结果：17个药物在一定时间内在体透过人皮肤的透过比的神经网络计算值和实测值均相当符合。结论：用BP神经网络法可以较好地预测药物在体透过人皮肤的渗透性。
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| 关 键 词： | 神经网络法 预测 药物 在体透过人皮肤 渗透性 药物设计 分配系数 |
| 文章编号： | 1008-9292(2003)02-0152-03 |
Prediction of human skin permeability of drugs in vivo with artificial neural network |
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| FU Xu chuen. Prediction of human skin permeability of drugs in vivo with artificial neural network[J]. Journal of Zhejiang University. Medical sciences, 2003, 32(2): 152-154,158 |
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| Authors: | FU Xu chuen |
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| Affiliation: | Department of Pharmacy, Zhejiang University City College, Hangzhou 310015, China. |
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| Abstract: | OBJECTIVE: To predict in vivo human skin permeability of drugs. METHODS: Appropriate BP(Back-propagation) neural network to predict human skin permeation ratios of drugs (R, absorbed/unabsorbed) was established. The octanol water partition coefficients (logP), molecular volumes (V), hydrogen bond acidities (sigma alpha 2(H)) and hydrogen bond basidities (sigma beta 2(H)) were selected as the neural units of input layer, and logR values were selected as the neural units of output layer. RESULTS: The calculated logR values of 17 drugs were in good accordance with their observed values. CONCLUSION: BP neural network can be used to predict in vivo human skin permeability of drugs. |
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| Keywords: | Drug design Skin absorption Partition coefficient Molecular volume Hydrogen bond BP neural network |
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