QSAR and QSPR studies of a highly structured physicochemical domain

The relevance of terms other than linear when deriving quantitative structure-activity relationship/quantitative structure-property relationship (QSAR/QSPR) models has been rarely considered so far. In this study, the impact of quadratic and interacting terms has been taken into account. The first effect of including such highly structured terms is a significant extension of the parametric domain that moves from the initial N to N(N + 3)/2 parameters. This substantial enlargement over the conventional linear boundaries involves a higher computational cost due to the increased combinatorial number of resulting theoretical QSAR/QSPR models. To face this issue, novel genetic-algorithm-based software, MGZ (multigenetic zooming), was developed and used for both variable selection and model building. To speed up the entire process of domain searching, MGZ was supported with multiple independent evolving populations and genetic storms to further QSAR/QSPR analyses. In addition, a novel fitness function was developed to score models on the basis of their inner predictive capability, assessed on the training set, structure complexity, and presence of nonlinear terms. The models were further validated by monitoring model redundancy and performing intensive randomization runs. The Selwood data set was used as a reference set to derive QSAR models. Furthermore, a QSPR study was conducted on the solubility data set of a large array of organic compounds. The results reported in the present paper demonstrate that our approach is successful in finding linear models, which are at least as good as the models previously derived using standard statistical approaches, and in deriving new nonlinear models with good statistical figures.     

QSAR/QSPR在POPs归趋与风险评价中的应用*

持久性有机污染物(POPs)是目前备受国际社会关注的高危害性有机污染物,对它们的环境归趋分析和风险评价需要获得大量可靠的性质数据和毒性数据,而定量结构活性/性质相关(QSAR/QSPR)方法为快速有效地获得这些数据提供了可能性。QSAR/QSPR模型已在预测POPs的生物活性/性质,补充缺失的基础数据及探求POPs的环境过程机制和生态效应机理等方面得到了广泛应用,近年来也在新POPs物质的筛选、归趋模拟以及风险评价等方面有着更进一步的应用或潜在应用前景。本文介绍了QSAR/QSPR在POPs性质和生物活性预测中的基本应用及其在POPs归趋和风险评价中的扩展应用,并对QSAR/QSPR在POPs研究领域的应用前景进行了展望。