Prediction of bile salt export pump inhibition using biomimetic chromatographic descriptors: Integrating membrane affinity and protein binding: Original scientific article

Chrysanthos Stergiopoulos; Klara Valko

doi:10.5599/admet.3303

Authors

Chrysanthos Stergiopoulos Laboratory of Process Analysis and Design, School of Chemical Engineering, National Technical University of Athens, Iroon Polytechniou 9, 157 75 Zografou, Athens, Greece https://orcid.org/0000-0001-6002-4870
Klara Valko Bio-Mimetic Chromatography Ltd, Business & Technology Centre, Bessemer Drive, Stevenage, Herts, SG1 2DX, United Kingdom https://orcid.org/0000-0003-4605-2941

DOI:

https://doi.org/10.5599/admet.3303

Keywords:

Hepatotoxicity, canalicular transport, predictive modelling, drug distribution, transporter inhibition

Abstract

Background and purpose: Bile salt export pump (BSEP) inhibition is a key mechanistic driver of cholestatic drug-induced liver injury, yet current prediction approaches rely mainly on in vitro potency and calculated physicochemical descriptors that do not adequately reflect local exposure at the canalicular membrane. This study aimed to evaluate whether biomimetic chromatographic descriptors could improve predictions of BSEP inhibition by incorporating mechanistically relevant information on membrane affinity and protein binding. Experimental approach: A dataset of 62 structurally diverse compounds with reported BSEP inhibition data was compiled and modelled using multiple linear regression. Biomimetic descriptors derived from immobilized artificial membrane chromatography and human serum albumin affinity (log k_HSA) were compared against conventional descriptors such as lipophilicity and molecular weight. Model performance was assessed using internal and external validation, graphical diagnostics, Y-randomization, and applicability domain analysis. Key results: Models based on biomimetic descriptors demonstrated superior, more balanced predictive performance than conventional physicochemical models, with greater robustness and external predictivity. The combination of membrane-affinity and protein-binding descriptors provided a more accurate representation of the determinants governing BSEP interactions. Conclusion: Biomimetic chromatographic descriptors provide an experimentally grounded approximation of membrane-proximal exposure, a key determinant of BSEP interactions that conventional descriptors do not capture. This approach extends beyond traditional quantitative structure-activity relationship by incorporating distribution-relevant properties into predictive modelling and offers a simple, interpretable framework to support early identification of transporter-mediated toxicity risk in drug discovery.

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