QSPR studies on the blood-air partition coefficient of volatile organic compounds using theoretical descriptors derived from electrostatic potentials on molecular surface

Abstract

Volatile organic compounds (VOCs) is a sort of important environmental pollutant. Based on study on Quantitative Structure-Property Relationship (QSPR), geometrical optimization and electrostatic potential calculations have been performed for 143 VOC molecules at the HF/6-31G* level of theory. A number of statistically-based parameters have been obtained. Multiple Linear Regression (MLR) and back-propagation artificial neural network (BP-ANN) nonlinear regression are used for the model building. The result shows that the BP-ANN can better expresses the relation between molecule surface electrostatic potential and blood-air partition coefficient than MLR, and the QSPR model established has comparatively stronger stability and predictive ability using BP-ANN method. The result also proves the applicability of molecule surface electrostatic potential parameter in QSPR study of Volatile organic chemical.