LAUSR

The partition coefficients between bovine serum albumin (BSA) and water (KBSA/w) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logKBSA/w. However, it was found that the conventional descriptors are inappropriate for modeling logKBSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for KBSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logKBSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (Vs-adj-), the chemical form adjusted molecular dipole moment (dipolemomentadj), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logKBSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs.