Human serum albumin-mimetic chromatography based hexadecyltrimethylammonium bromide as a novel direct probe for protein binding of acidic drugs

•A novel CTAB based HSA-mimetic chromatography is developed.•BMC methodology as an early predictor of protein–drug binding.•Fast, reproducible and simple protein binding assay of new acidic drugs.•Formation of pseudo HSA protein in CTAB-modified stationary phase.

Human serum albumin (HSA) is the most important drug carrier in humans mainly binding acidic drugs. Negatively charged compounds bind more strongly to HSA than it would be expected from their lipophilicity alone. With the development of new acidic drugs, there is a high need for rapid and simple protein binding screening technologies. Biopartitioning micellar chromatography (BMC) is a mode of micellar liquid chromatography, which can be used as an in vitro system to model the biopartitioning process of drugs when there are no active processes. In this study, a new kind of BMC using hexadecyltrimethylammonium bromide (CTAB) as micellar mobile phases was used for the prediction of protein binding of acidic drugs based on the similar property of CTAB micelles to HSA. The use of BMC is simple, reproducible and can provide key information about the pharmacological behavior of drugs such as protein binding properties of new compounds during the drug discovery process. The relationships between the MLC retention data of a heterogeneous set of 17 acidic and neutral drugs and their plasma protein binding parameter were studied and second-order polynomial models obtained in two different concentrations (0.07 and 0.09 M) of CTAB. However, the developed models are only being able to distinguish between strongly and weakly binding drugs. Also, the developed models were characterized by both the descriptive and predictive ability (R2 = 0.885, RCV2=0.838 and R2 = 0.898, RCV2=0.859 for 0.07 and 0.09 M CTAB, respectively). The application of the developed model to a prediction set demonstrated that the model was also reliable with good predictive accuracy.

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