分子軌道法とニューラルネットワークを基盤とした薬物吸収予測システムの開発

药物的发现和开发一直是时间和劳动密集型的。解决这一问题的关键是开发知识库，如药物分子和制剂的设计。生物膜的通透性是决定药物生物利用度和有效性的重要因素。在这种情况下，我们开发了数学模型，用于从化合物的分子结构预测它们。通过分子轨道计算得到药物的结构描述符，并采用多元线性回归或人工神经网络分析药物结构描述符与人体皮肤渗透系数之间的关系。我们发现，药物分子的偶极矩，极化率和原子电荷是重要的描述符来预测药物的皮肤渗透性，神经网络模型是一个上级的线性回归模型在描述描述符/渗透性的关系。该方法适用于预测Caco-2细胞单层的渗透性，该细胞单层已被用作肠上皮的模型。因此，分子轨道计算和神经网络相结合，可能有助于预测药物的药代动力学性质。此外，基于皮肤由角质层和下层组成的双层皮肤扩散模型，分析了载体对药物皮肤渗透性的影响，发现皮肤渗透性与载体介电常数密切相关。总之，这项研究可能能够加速药物发现和开发的有效性，特别是对于局部制剂。

Drug discovery and development of drugs has been time- and labor-intensitve. A key issue to solve this problem is to develop knowledge bases such as design of drug molecules and formulations. Permeability of biological membranes are important factors determining bioavailability and effectiveness of drugs. In this context, we developed mathematical models for predicting them from molecular structures of compounds. Structural descriptors of drugs were obtained by molecular orbital calculations, and the relationship between the descriptors and permeability coefficients through human skin was analyzed by multiple linear regression or artificial neural network. We revealed that dipole moment, polarizability, and atomic charges of drug molecules are important descriptors to predict skin permeability for drugs, and that a neural network model is much superior to a linear regression model in describing the descriptor/permeability relationship. This approach was applicable to prediction of permeability of Caco-2 cell monolayers, that have been used as a model of intestinal epithelium. Thus, the combination of molecular orbital calculation and neural network might be useful to predict pharmacokinetic properties of drugs. In addition, we analyzed the effect of vehicles on skin permeability of drugs based on a two-layer skin diffusion model, in which the skin is composed of stratum corneum and the lower layer, and found a close relationship between skin permeability and dielectric constant of vehicles. In conclusion, this study might be able to accelerate effectiveness of drug discovery and development, especially for topical formulations.