Development of molecular design system using inverse analysis method

Abstract

In the field of pharmaceutical industry and other areas, QSPR/QSAR method is widely used for efficient design of functional molecules having desired combination of properties. In this study, we propose a novel methodology for helping molecular design using inverse-QSPR/QSAR method. This method enables us to exhaustively generate chemical structures which have desired properties or activities. The method is composed of three parts: construction of QSPR/QSAR models, analysis of the model inversely, generation of structures exhaustively. QSPR/QSAR models are constructed with MLR/OLS for the following inverse analysis. A mixture of Gaussian distributions is used to characterize the probability distribution of data set in descriptor space. Combining these probability models, inverse analysis is conducted using the framework of linear Gaussian models. Exhaustive chemical structures are generated by using specific kind of descriptors inside the pre-determined region in which the probability density values are high. It is also possible to determine the region considering applicability domain of QSPR/QSAR model. By using proposed method, efficient structure generation is expected.