Abstract:
The movement of organic anionic drugs across cell membranes is partly governed by interactions with SLC and ABC transporters in the intestine, liver, kidney, blood-brain barrier, placenta, breast, and other tissues. Major transporters involved include organic anion transporters (OATs, SLC22 family), organic anion transporting polypeptides (OATPs, SLCO family), and multidrug resistance proteins (MRPs, ABCC family). However, the sets of molecular properties of drugs that are necessary for interactions with OATs (OAT1, OAT3) vs. OATPs (OATP1B1, OATP1B3) vs. MRPs (MRP2, MRP4) are not well-understood. Defining these molecular properties is necessary for a better understanding of drug and metabolite handling across the gut-liver-kidney axis, gut-brain axis, and other multi-organ axes. It is also useful for tissue targeting of small molecule drugs and predicting drug-drug interactions and drug-metabolite interactions. Here, we curated a database of drugs shown to interact with these transporters in vitro and used chemoinformatic approaches to describe their molecular properties. We then sought to define sets of molecular properties that distinguish drugs interacting with OATs, OATPs, and MRPs in binary classifications using machine learning and artificial intelligence approaches. We identified sets of key molecular properties (e.g., rotatable bond count, lipophilicity, number of ringed structures) for classifying OATs vs. MRPs and OATs vs. OATPs. However, sets of molecular properties differentiating OATP vs. MRP substrates were less evident, as drugs interacting with MRP2 and MRP4 do not form a tight group owing to differing hydrophobicity and molecular complexity for interactions with the two transporters. If the results also hold for endogenous metabolites, they may deepen our knowledge of organ crosstalk, as described in the Remote Sensing and Signaling Theory. The results also provide a molecular basis for understanding how small organic molecules differentially interact with OATs, OATPs, and MRPs.
摘要:
有机阴离子药物跨细胞膜的运动部分受与肠道中SLC和ABC转运蛋白相互作用的控制。肝脏,肾,血脑屏障,胎盘,乳房,和其他组织。涉及的主要转运蛋白包括有机阴离子转运蛋白(OATs,SLC22系列),有机阴离子转运多肽(OATPs,SLCO系列),和多药耐药蛋白(MRPs,ABCC家族)。然而,与OATs相互作用所必需的药物的分子特性集(OAT1,OAT3)与OATPs(OATP1B1,OATP1B3)与MRP(MRP2,MRP4)尚未得到很好的理解。定义这些分子特性对于更好地理解药物和代谢物在肠-肝-肾轴上的处理是必要的。肠-脑轴,和其他多器官轴。它还可用于小分子药物的组织靶向和预测药物-药物相互作用和药物-代谢物相互作用。这里,我们整理了一个显示在体外与这些转运蛋白相互作用的药物数据库,并使用化学信息学方法描述了它们的分子特性。然后,我们试图定义区分与OAT相互作用的药物的分子特性集,OATPs,和使用机器学习和人工智能方法的二元分类中的MRP。我们确定了关键分子特性的集合(例如,可旋转债券计数,亲脂性,环状结构的数量)用于分类OAT与MRP和OAT与OATPs。然而,区分OATP与OATP的分子特性集MRP底物不太明显,因为与MRP2和MRP4相互作用的药物由于与两种转运蛋白相互作用的不同疏水性和分子复杂性而不形成紧密基团。如果内源性代谢物的结果也成立,他们可能会加深我们对管风琴相声的了解,如遥感和信号理论所述。该结果还为理解有机小分子如何与OAT进行差异相互作用提供了分子基础。OATPs,和MRP。