QSPRs for estimating nematic transition temperatures of pyridine-containing liquid crystalline compounds

Abstract

ABSTRACTQuantitative structure–property relationships were developed to predict the nematic–isotropic transition temperatures of 92 pyridine-containing liquid crystalline compounds using molecular descriptors calculated by CODESSA software and DRAGON software. The descriptors were also analysed by using principal component analysis. Essentials accounting for a reliable model were all considered carefully during model construction and assessment process. Five variables were selected out by stepwise forward regression analysis and were used as inputs to perform the multiple linear regression, support vector machine and projection pursuit regression (PPR) study. All models were validated through two ways, that is, internal cross-validation combined with a test set. Comparatively, the PPR model performs best both in the fitness and in the prediction capacity. For the test set, it gave a predictive correlation coefficient (R) of 0.991, root mean square error of 11.799 and absolute average relative deviation of 5.456, respectively. The relationships between the descriptors and the nematic–isotropic transition temperature of compounds were also discussed. The odd–even effect in the transition temperatures of mesogens in the same homologous series was also discussed.