Abstract: In order to discover the relationships between thermodynamic properties and molecular descriptors, the thermodynamic properties of 60 resveratrol analogues, such as the mean polarizability (α), the standard molar enthalpy of formation(HΘ), the thermal energy(EΘ), the molar heat capacity under constant volume(CΘ_V)and the standard molar entropy(SΘ), were investigated in this work, and the molecular descriptors, the topological indexes of principal quantum number(⁰P2,0P4,0P_3')and the sum of them(∑⁰P), were calculated. With less variables, the sum of topological indexes of principal quantum number(∑⁰P)was confirmed as the base variable for the models through comparative analysis. Base on the characteristics of sine series, the series sin(k∑0P)(where k=1, 2, 3, …)were incorporated into the models to eliminate the residuals. Reducing the multicollinearity among independents and seeking less variables, the quantitative structure-property relationship(QSPR)models of thermodynamic properties were established with the max adjusted coefficient of determination(R²_adj)as the destination. The results showed that it was successful to eliminate the residuals and improved the predictabilities by introducing sin(5∑⁰P)and sin(8∑⁰P)into the models. And all the correlation coefficients are larger than 0.99, even reach 1. The leave one out cross validation method was adopted to test the stability, and the prediction ability of each model was tested by 7 resveratrol analogues(not in samples), and both results showed quite satisfactory. It has been demonstrated that the quantitative structure-property relationship(QSPR)models have satisfactory stability and good predictability.

Key words: medicine, organic compounds, computer simulation, prediction, thermodynamic properties