Molecular and Dynamic Insights into the Function of GPCRs Involved in Drug Abuse

美国因吸毒过量死亡人数创历史新高，远远超过因枪支死亡人数 或车祸。百分之六十的死亡是由非法毒品（例如海洛因）或合法毒品造成的 处方阿片类药物（例如奥施康定和Percocet）。这不仅引起了联邦的关注 有具体要求的政府通过加强毒品追踪、执法和公众宣传来解决这一问题 意识，但医生也改变了治疗疼痛的方式，在开药时变得更加犹豫 阿片类药物，因为围绕其滥用存在争议。然而，有效的疼痛治疗方法 对于超过 1.1 亿患有慢性疼痛的美国成年人来说，仍然缺乏管理，并且缺乏全面的管理 问题的解决很可能需要在分子水平上了解这些药物的作用原理，以便 以确定如何微调阿片类药物信号以达到所需的治疗途径并远离 那些介导不利影响的人。这些信息对于最终设计强大的化学工具至关重要 可能被开发成改进的治疗方法。 越来越多的证据表明阿片类变构调节剂和 G 蛋白偏向 阿片类激动剂可以作为改进的止痛药，减少副作用，这是这项工作的总体目标 本申请中描述的目的是获得关于替代（变构）结合位点的原子信息和/或 阿片受体的配体特异性（偏向）构象，包括药物受体结合动力学的详细信息， 用作最终发现改进疗法的新的、令人兴奋的途径。为此，我们将聘请 计算驱动的方法，用于生成对阿片受体独特机制的假设生成 将由独立资助的研究人员反复测试的功能。这些研究预计将 通过帮助我们确定阿片类药物变构调节的价值，对生物医学研究产生重大影响， 药物发现中的偏向激动和结合动力学。

Deaths from drug overdoses have hit record numbers in the US, far exceeding the number of deaths from guns or car accidents. Sixty percent of these deaths are caused by either illegal drugs (e.g., heroin) or legal prescription opioids (e.g., Oxycontin and Percocet). Not only has this drawn the attention of the federal government with specific requests to address the issue by increasing drug tracking, enforcement, and public awareness, but also doctors have changed the way they treat pain, becoming more hesitant to prescribe opioids because of the controversy surrounding their abuse. However, effective treatments for pain management are still lacking for the over 110 million American adults suffering from chronic pain, and a full resolution of the problem will most likely require a molecular level understanding of how these drugs work so as to determine how to fine-tune opioid signaling towards the desired therapeutic pathways and away from those mediating adverse effects. This information is essential to eventually design powerful chemical tools that may be developed into improved therapeutics. Building upon the growing body of evidence suggesting that opioid allosteric modulators and G protein-biased opioid agonists may act as improved painkillers with reduced side effects, the overall goal of the work described in this application is to obtain atomistic information about alternative (allosteric) binding sites and/or ligand-specific (biased) conformations of opioid receptors, including details of drug-receptor binding kinetics, for use as new, exciting avenues to eventually discover improved therapeutics. To this end, we will employ a computation-driven approach for hypothesis generation of unique mechanistic insights into opioid receptor function that will be tested iteratively by independently funded investigators. These studies are expected to significantly impact biomedical research by helping us establish the value of opioid allosteric modulation, biased agonism, and binding kinetics in drug discovery.