Santos-Filho Osvaldo A, Hopfinger A J, Zheng Tao
Laboratory of Molecular Modeling and Design (M/C 781), College of Pharmacy, The University of Illinois at Chicago, 833 South Wood Street, Chicago, Illinois 60612-7231, USA.
Mol Pharm. 2004 Nov-Dec;1(6):466-76. doi: 10.1021/mp049924+.
Molecular similarity and QSAR analyses have been used to develop compact, robust, and definitive models for skin penetration by organic compounds. The QSAR models have been sought to provide an interpretation and characterization of plausible molecular mechanisms of skin penetration. A training set of 40 structurally diverse compounds were selected to be representative of a parent set of 152 compounds in terms of both structural diversity and range in measured skin penetration. The subset of 40 compounds was used in a series of QSAR analyses in the search for the most significant, compact, and straightforward skin penetration QSAR models. Molecular dynamics simulations were employed to determine a set of MI (membrane-interaction) descriptors for each test compound (solute) interacting with a model DMPC monolayer membrane model. The MI-QSAR models may capture features of cellular membrane lateral transverse transport involved in the overall skin penetration process by organic compounds. An additional set of intramolecular solute descriptors, the non-MI-QSAR descriptors, were computed and added to the trial pool of descriptors for building QSAR models. All QSAR models were constructed using multidimensional linear regression fitting and a genetic algorithm optimization function. QSAR models were constructed using only non-MI-QSAR descriptors and using a combination of both these descriptor sets. It was found that a combination of non-MI-QSAR and MI-QSAR descriptors yielded the optimum models, not only with respect to the statistical measures of fit but also regarding model predictivity.
分子相似性和定量构效关系（QSAR）分析已被用于开发针对有机化合物皮肤渗透的紧凑、稳健且确定的模型。人们一直在寻求QSAR模型，以对皮肤渗透的合理分子机制进行解释和表征。选择了一组40种结构多样的化合物作为训练集，在结构多样性和测量的皮肤渗透率范围方面，它们代表了一组152种化合物的母体。这40种化合物的子集被用于一系列QSAR分析，以寻找最显著、紧凑且直接的皮肤渗透QSAR模型。采用分子动力学模拟来确定每种测试化合物（溶质）与模型二肉豆蔻酰磷脂酰胆碱（DMPC）单层膜模型相互作用的一组膜相互作用（MI）描述符。MI-QSAR模型可能捕捉到有机化合物在整体皮肤渗透过程中涉及的细胞膜横向跨膜转运特征。计算了另一组分子内溶质描述符，即非MI-QSAR描述符，并将其添加到用于构建QSAR模型的描述符试验库中。所有QSAR模型均使用多维线性回归拟合和遗传算法优化函数构建。QSAR模型分别仅使用非MI-QSAR描述符以及同时使用这两组描述符进行构建。结果发现，非MI-QSAR和MI-QSAR描述符的组合产生了最优模型，不仅在拟合的统计指标方面，而且在模型预测性方面也是如此。
