Structure-Based Identification of OATP1B1/3 Inhibitors
Structure-Based Identification of OATP1B1/3 Inhibitors
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DOI：
10.1124/mol.112.084152
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发表时间：
2013-06-01
影响因子：
3.6
通讯作者：
Annaert, Pieter P.
中科院分区：
文献类型：
--
作者：
De Bruyn, Tom;van Westen, Gerard J. P.;Annaert, Pieter P.
最近的几项研究表明，抑制肝脏转运蛋白有机阴离子转运多肽1B 1（OATP 1B 1）和1B 3（OATP 1B 3）可导致临床相关的药物相互作用（DDI）。为了避免由于OATP 1B介导的DDI导致的后期开发药物失败，应在候选药物评价过程的早期阶段实施预测性体外和计算机模拟方法。在本研究中，我们首先开发了一种高通量的体外转运蛋白抑制试验的OATP 1B亚家族。在OATP 1B 1或1B 3转染的中国仓鼠卵巢细胞中，共检测了2000种化合物作为OATP 1B底物荧光素钠摄取的潜在调节剂。在等摩尔底物抑制剂浓度为10 μ M时，分别鉴定出212和139个分子为OATP 1B 1和OATP 1B 3抑制剂（最小50%抑制）。对于69种化合物（以前未被鉴定为OATP 1B抑制剂），也测定了浓度依赖性抑制作用，得到的Ki值范围为0.06 - 6.5 μ M。基于这些体外数据，我们随后开发了一种基于蛋白化学计量学的计算机模拟模型，该模型预测了试验组（数据集的20%）中的OATP 1B抑制剂，具有高特异性（86%）和灵敏度（78%）。此外，还鉴定了与OATP 1B 1/1B 3抑制或失活相关的几种理化化合物性质和亚结构。最后，用原始数据集中未包含的一组54种化合物前瞻性验证了模型性能。该验证表明，80%和74%的化合物分别被正确分类为OATP 1B 1和OATP 1B 3抑制。
Several recent studies show that inhibition of the hepatic transport proteins organic anion-transporting polypeptide 1B1 (OATP1B1) and 1B3 (OATP1B3) can result in clinically relevant drug-drug interactions (DDI). To avoid late-stage development drug failures due to OATP1B-mediated DDI, predictive in vitro and in silico methods should be implemented at an early stage of the drug candidate evaluation process. In the present study, we first developed a high-throughput in vitro transporter inhibition assay for the OATP1B subfamily. A total of 2000 compounds were tested as potential modulators of the uptake of the OATP1B substrate sodium fluorescein, in OATP1B1- or 1B3-transfected Chinese hamster ovary cells. At an equimolar substrate-inhibitor concentration of 10 mu M, 212 and 139 molecules were identified as OATP1B1 and OATP1B3 inhibitors, respectively (minimum 50% inhibition). For 69 compounds, previously not identified as OATP1B inhibitors, concentration-dependent inhibition was also determined, yielding K-i values ranging from 0.06 to 6.5 mu M. Based on these in vitro data, we subsequently developed a proteochemometrics-based in silico model, which predicted OATP1B inhibitors in the test group (20% of the dataset) with high specificity (86%) and sensitivity (78%). Moreover, several physicochemical compound properties and substructures related to OATP1B1/1B3 inhibition or inactivity were identified. Finally, model performance was prospectively verified with a set of 54 compounds not included in the original dataset. This validation indicated that 80 and 74% of the compounds were correctly classified for OATP1B1 and OATP1B3 inhibition, respectively.