Quantitative Structure–Activity Relationship Analysis of a Series of Human Renal Organic Anion Transporter Inhibitors

Abstract

Organic anion transporters (OATs) have been proved to play important roles in the membrane transport of numerous potentially toxic xenobiotics, drugs, and endogenous metabolites. In general, OATs substrates can compete with one another for the transporter to mutually decrease renal secretion and thus delay the clearance and prolong the duration of action of each compound. Such interactions have the potential to bring about adverse outcomes for clinical cases. Therefore, it is very important to assess the molecular bioactivity to inhibit OATs during the development of new drugs and co-administration. In this work, the relationships between 45 chemicals and their corresponding hOAT1 and hOAT3 inhibitory activities were analyzed. The quantitative structure-activity relationship (QSAR) model was developed by genetic algorithm and multiple linear regression method. The predictive power of the proposed model was strictly evaluated, and the applicability domain was also defined. The proposed models were robust and satisfactory and could provide a feasible and effective tool for hOAT1 or hOAT3 inhibitor screening.