Laboratory of Chemometrics, Department of Chemistry, Biology and Biotechnology, University of Perugia, Via Elce di Sotto 8, 06123 Perugia, Italy.
Technologie Servier, 25-27 rue Eugène Vignat, BP 11749, 45007 Orléans cedex 1, France.
Eur J Pharm Sci. 2018 Aug 30;121:85-94. doi: 10.1016/j.ejps.2018.04.039. Epub 2018 Apr 28.
The presence of several binding sites for both substrates and inhibitors is yet a poorly explored thematic concerning the assessment of the drug-drug interactions risk due to interactions of multiple drugs with the human transport protein P-glycoprotein (P-gp or MDR1, gene ABCB1). In this study we measured the inhibitory behaviour of a set of known drugs towards P-gp by using three different probe substrates (digoxin, Hoechst 33,342 and rhodamine 123). A structure-based model was built to unravel the different substrates binding sites and to rationalize the cases where drugs were not inhibiting all the substrates. A separate set of experiments was used to validate the model and confirmed its suitability to either detect the substrate-dependent P-gp inhibition and to anticipate proper substrates for in vitro experiments case by case. The modelling strategy described can be applied for either design safer drugs (P-gp as antitarget) or to target specific sub-site inhibitors towards other drugs (P-gp as target).
由于多种药物与人类转运蛋白 P-糖蛋白（P-gp 或 MDR1，基因 ABCB1）相互作用，导致药物-药物相互作用风险，对于评估这种风险，多种底物和抑制剂的多个结合位点的存在仍然是一个探讨较少的主题。在这项研究中，我们使用三种不同的探针底物（地高辛、Hoechst 33,342 和罗丹明 123）来测量一组已知药物对 P-gp 的抑制行为。建立了一个基于结构的模型，以揭示不同的底物结合位点，并合理说明为什么有些药物不能抑制所有的底物。另一组实验用于验证该模型，并证实其适用于检测底物依赖性 P-gp 抑制，以及逐个案例预测适当的体外实验底物。所描述的建模策略可用于设计更安全的药物（以 P-gp 为抗靶标），或针对其他药物靶向特定的亚位点抑制剂（以 P-gp 为靶标）。
