Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors

Abstract The partition coefficients between bovine serum albumin (BSA) and water ( K BSA / 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 log K BSA / w . However, it was found that the conventional descriptors are inappropriate for modeling log K BSA / w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA / 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 log K BSA / 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 ( V s − a d j − ) , the chemical form adjusted molecular dipole moment ( dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (log D ). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the log K BSA / 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.