Substrate Specificity of the Choroid Plexus and Kidney Transporter Oat1

描述（由申请方提供）：除了ABC超家族成员外，有机阴离子转运蛋白（如Oat 1）（首次由PI实验室鉴定）很可能是体内最重要的异生物质和多特异性代谢物转运蛋白。燕麦被认为是至关重要的 用于调节药物、毒素和代谢物在CSF、血液、尿液和其它体液之间的分布。在本重新提交申请中，我们建议采用计算机模拟、体外、结构生物学和体内方法，以提供底物-转运蛋白相互作用的全面情况，并使用PI组相对独特的试验对其进行验证。因此，该小组有多种计算机，体外和体内方法，我们的合作者（Chang博士）是药物转运领域的主要结构生物学家之一。 运输商尚未执行，我们认为，我们是在一个理想的位置，这样做。我们计划使用基于配体和转运蛋白的计算建模，我们有丰富的经验，以确定通过Oat 1（SA 1，将与圣地亚哥超级计算机的合作者一起完成）摄取和处理的靶向底物的分子决定因素。然后将使用药效团进行化学结构库的虚拟筛选，然后进行化合物的湿实验室验证。我们还将与Chang博士（涉及他的实验室和TransportPDB，NIH蛋白质结构计划的一个组成部分）合作，结晶和确定Oat 1的高分辨率X射线结构，以获得对其底物结合和运输（SA 2）的结构要求的关键见解。在SA 3中，我们建议通过体内药代动力学分析（与OAT 1敲除相比，我们之前已经显示了异常的全身代谢以及有缺陷的药物和毒素处理）测试Oat 1转运抑制的预测，进一步验证我们对底物-转运蛋白相互作用（来自SA 1和SA 2）的分析。这些研究的结果也可能对理解Oat 1在全身和组织特异性代谢中的作用产生广泛的影响（除了可能导致延长药物半衰期的抑制剂）。我们试图解决所有先前的批评，重点是澄清“意义”，“创新”和“方法”，我们已经为结晶目标提供了初步的数据。我们还在2010-2011年发表了许多相关的“计算湿实验室论文”。在其中一篇论文中，我们描述了使用药效团建模和虚拟筛选来识别一种新的高亲和力抑制剂，该抑制剂在转运试验中得到初步验证;这种高亲和力抑制剂也可能有助于获得Oat 1底物结合结构。也许是这个领域的独特之处，PI汇集了世界级的专家（都在UCSD或Scripps），他们的实验室经常使用所提出的方法。还讨论了“替代”的计算和湿实验室的方法的情况下，主要的方法是不太成功的比预期的。

DESCRIPTION (provided by applicant): Apart from members of the ABC superfamily, organic anion transporters such as Oat1, first identified by the PI's lab, may well be the most important xenobiotic and multi-specific metabolite transporters in the body. Oats are believed to be critical for regulating the distribution of drugs, toxins and metabolites between the CSF, blood, urine and other body fluids. In this RESUBMISSION application, we propose to employ in silico, in vitro, structural biological and in vivo methods to provide a comprehensive picture of substrate-transporter interactions and to validate this using assays that are relatively unique to the PI's group. Thus the group has multiple in silico, in vitro and in vivo approaches working, and our collaborator (Dr. Chang) is one of the premier structural biologists in the field of drug transport So far a "full circuit" of in silico-in vitro-in vivo analysis of any of the non-ABC mammalian drug transporters has not been performed, and we argue that we are in an ideal position to do this. We plan to use ligand and transporter-based computational modeling, with which we have extensive experience, to identify the molecular determinants which target substrates for uptake and handling via Oat1 (SA1, to be done with collaborators at the San Diego Supercomputer). Virtual screening of chemical structural libraries using pharmacophores will then be done, followed by wet lab validation of compounds. We will also crystallize and determine the high-resolution x-ray structure of Oat1 in collaboration with Dr. Chang (involving both his laboratory and TransportPDB, a component of the NIH Protein Structural Initiative) to gain key insights into the structural requirements for its substrate binding and transport (SA2). In SA3, we propose to further validate our analysis of substrate-transporter interactions (from SA1 and SA2) by testing predictions of inhibition of Oat1 transport by in vivo pharmacokinetic analysis (in comparison with the OAT1 knockout in which we have previously shown both aberrant systemic metabolism as well as defective drug and toxin handling). The results of these studies could also have broad implications for understanding the role of Oat1 in whole body and tissue-specific metabolism (quite apart from potentially leading to inhibitors that prolong drug half-life). We have tried to address all the prior criticisms, focusing on clarifying the "Significance," "Innovation" and "Approach," and we have provided preliminary data for the crystallization aim. We have also published many relevant "computational-wet lab papers" in 2010-2011. In one of these papers, we describe the use of pharmacophore modeling and virtual screening to identify a novel high-affinity inhibitor that was preliminarily validated in a transport assay; this high-affinity inhibior may also aid in obtaining an Oat1 substrate-bound structure. Perhaps unique for this field, the PI has brought together world-class experts (all at UCSD or Scripps) whose labs regularly use the proposed methods. Also discussed are "alternative" computational and wet lab approaches in case the primary approach is less successful than anticipated.