Uppsala University Drug Optimization and Pharmaceutical Profiling Platform, Department of Pharmacy, Uppsala University, The Biomedical Centre, P.O. Box 580, 751 23, Uppsala, Sweden.
Pharm Res. 2012 Feb;29(2):411-26. doi: 10.1007/s11095-011-0564-9. Epub 2011 Aug 23.
To establish in vitro and in silico models that predict clinical drug-drug interactions (DDIs) with the OATP1B1 (SLCO1B1) transporter.
The inhibitory effect of 146 drugs and drug-like compounds on OATP1B1-mediated transport was studied in HEK293 cells. A computational model was developed to predict OATP1B1 inhibition. Concentration-dependent effects were investigated for six compounds; clinical DDIs were predicted by calculating change in exposure (i.e. R-values) in eight different ways.
Sixty-five compounds were identified as OATP1B1 inhibitors at 20 μM. The computational model predicted the test set with 80% accuracy for inhibitors and 91% for non-inhibitors. In vitro-in vivo comparisons underscored the importance of using drugs with known clinical effects as references. Thus, reference drugs, cyclosporin A, gemfibrozil, and fenofibrate, provided an inhibition interval to which three antiviral drugs, atazanavir, lopinavir, and amprenavir, could be compared and their clinical DDIs with OATP1B1 classified.
Twenty-two new OATP1B1 inhibitors were identified, a predictive OATP1B1 inhibition in silico model was developed, and successful predictions of clinical DDIs were obtained with OATP1B1.
建立体外和计算模型，预测与 OATP1B1（SLCO1B1）转运体相关的临床药物-药物相互作用（DDI）。
在 HEK293 细胞中研究了 146 种药物和类药物化合物对 OATP1B1 介导的转运的抑制作用。开发了一个计算模型来预测 OATP1B1 抑制作用。研究了六种化合物的浓度依赖性效应；通过八种不同的方式计算暴露（即 R 值）的变化来预测临床 DDI。
在 20μM 时，有 65 种化合物被鉴定为 OATP1B1 抑制剂。该计算模型对抑制剂的测试集预测准确率为 80%，对非抑制剂的预测准确率为 91%。体内外比较强调了使用具有已知临床效果的药物作为参考的重要性。因此，参考药物环孢素 A、吉非贝齐和非诺贝特提供了一个抑制区间，可以将三种抗病毒药物阿扎那韦、洛匹那韦和安普那韦与之进行比较，并对它们与 OATP1B1 的临床 DDI 进行分类。
鉴定了 22 种新的 OATP1B1 抑制剂，开发了一个预测 OATP1B1 抑制作用的计算模型，并成功预测了 OATP1B1 的临床 DDI。
