Relating GPCRs by biased ligands for enhanced therapeutic efficacy

通过偏向配体关联 GPCR 以增强治疗效果

• 批准号: 8455893
• 负责人: Carl Nicholas Hodge
• 金额: $ 30.12万
• 依托单位: SEACHANGE PHARMACEUTICALS, INC.
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-18 至 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8455893
• 关键词: AVPR2 gene; Address; Adverse effects; Agonist; Animal Model; Antipsychotic Agents; Arrestins; Biological Assay; CXCR4 gene; Clinical; Computer Simulation; Computing Methodologies; Coupled; Dopamine D2 Receptor; Drug Kinetics; Drug usage; Exhibits; G Protein-Coupled Receptor Genes; G-Protein-Coupled Receptors; GTP-Binding Proteins; Generations; Goals; Group Structure; Housing; Ligands; Literature; Maps; Marketing; Measures; Methods; Molecular Conformation; Outcome; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Pharmacology; Published Comment; Reliance; Second Messenger Systems; Signal Pathway; Signal Transduction; System; Testing; Therapeutic; Treatment Efficacy; Work; aripiprazole; arrestin3; cost; drug market; metabotropic glutamate receptor 3; novel therapeutics; pre-clinical; prospective; public health relevance; receptor; screening; second messenger; theories

DESCRIPTION (provided by applicant): Goals: The goal is to expand the known pharmacological relationships among arrestin and G protein biased ligands. Starting with the Gi-coupled dopamine D2 receptor (D2R), we will predict biased ligands, evaluating our methods both retrospectively and via prospective experimental assay. We then extend this work to additional receptors, and finally organize the results into a map relating receptor polypharmacology by the functional selectivity of their ligands. Significance. Whereas biased ligands that preferentially activate arrestin or canonical signaling may comprise novel therapeutic opportunities unexploited among the well trammeled G protein coupled receptors, their discovery is more often serendipitous and few if any predictive computational models exist for it. The field suffers from a paucity of actual biased ligands, whose incompletely explored ranks include even marketed drugs such as aripiprazole, which may owe its efficacy to this mechanism. New screening capabilities to measure ?-arrestin1/2 recruitment at large scale provide unique and timely support for the computational methods, experimentally confirmed biased ligands, and "biased polypharmacology" maps proposed here. Theory/Background: Not all ligands are created equal. For GPCRs, ligands similar in selectivity, polypharmacology, and pharmacokinetics nonetheless exhibit differing patterns of second messenger signaling and therapeutic efficacy. This "functional selectivity" differentiates ligands that activate signal transduction via the canonical (G coupled) and the ¿arrestin1/2 (aka arrestin3/4, hereafter "arrestin") pathways. Pathway engagement is ligand specific and contributes to drug outcomes. As one example, effective third generation antipsychotics that induce fewer side effects were originally thought to be partial agonists of D2R, but may instead signal exclusively via ¿arrestin2. Aim 1: To predict and test new arrestin-biased ligands. Biased ligands are thought to stabilize transmembrane receptor conformational ensembles to preferentially activate a signaling pathway; in practice however we must more often deduce receptor conformations from ligand efficacy than the other way around. We will pursue two goals: a. Leveraging its sole reliance on ligand structures, grouped by efficacy, we will adapt the Similarity Ensemble Approach (SEA) to differentiate groups of biased ligands. b. Further, we will predict and test new biased ligands at D2R for antipsychotic use. Milestones. The essential features of this system exist, and proof of principle has been demonstrated in predicting new targets for over 35 targets for 20 drugs using SEA. Here we refine SEA's notion of "target" to encode ligand bias. There are two pragmatic milestones. i. Evaluating five computational methods that leverage a ligand centric viewpoint to predict new biased ligands, from SEA alone to in house "marker set" receptor signatures. ii. Prospectively testing 20 arrestin biased D2R ligand predictions experimentally and advancing (a) one drug to antipsychotic animal models or (b) up to three preclinical compounds to PK profiling, as warranted. Aim 2: To relate GPCR pharmacology by biased ligands. We will extend our maps of all GPCRs to reflect biased ligand classes. This will allow us to interrogate the method's reach and impact: a. Determining whether arrestin biased ligands associate more closely in the map with canonical ligands of the same receptor-or instead with the arrestin biased ligands of an unrelated receptor. b. Adapting methods from Aim 1 to predict and test biased ligands for further therapeutic receptors. Milestones. We will relate functional selectivity to the wider context of known GPCR pharmacology by: i. Combining biased ligands from this study and from the literature into a global map of receptor relationships. ii. Demonstrating broad applicability by predicting and testing a further 20 biased ligands at each of two receptors (for 40 total) selected from the list f therapeutic receptors with ligands known to exhibit biased downstream signaling. Whereas these goals are admittedly ambitious, preliminary results suggest that they are feasible.

描述（由申请人提供）： 目标：目标是扩大抑制蛋白和G蛋白有偏见之间的已知药理关系。从GI偶联的多巴胺D2受体（D2R）开始，我们将预测有偏的配体，回顾性和通过前瞻性实验测定法评估我们的方法。然后，我们将这项工作扩展到其他受体，并最终通过其配体的功能选择性将结果组织到与受体多形药有关的地图中。 意义。尽管优先激活停滞蛋白或规范信号传导的有偏见的配体可能包括在良好的格拉姆式G蛋白偶联受体中无法解释的新型治疗机会，但它们的发现通常是偶然的，并且如果有任何预测性计算模型，则很少有。该领域遭受了实际偏见的配体的匮乏，其探索的排名不完全包括甚至是销售的药物，例如阿立哌唑，这可能会使其效率归功于这种机制。大规模测量的新筛选功能？-arrestin1/2大规模募集提供了对计算方法的独特而及时的支持，实验确认的有偏见的配体以及“有偏见的多形药理学”图。 理论/背景：并非所有配体都是平等的。对于GPCR，选择性，多种药物和药代动力学的配体仍然表现出第二丝方信号传导和治疗效率的不同模式。这种“功能选择性”不同的是通过规范（g耦合）和`hustanin1/2（又名Hustanin3/4，以后的“阻止素”）途径激活信号转导的配体。途径参与是特定于配体的，并有助于药物结果。作为一个例子，最初认为有效诱导副作用更少的有效的第三代抗精神病药是D2R的部分激动剂，但可以完全通过»tharstin2发出信号。 目标1：预测和测试新的逮捕蛋白偏见的配体。人们认为有偏的配体可以稳定跨膜受体构象共聚物，以优先激活信号通路。但是，实际上，我们必须比相反的情况更多地从配体效率推断出受体构象。我们将追求两个目标：通过利用其唯一的浮雕在配体结构上，通过效率分组，我们将适应相似性集合方法（SEA），以区分有偏的配体的组。 b。此外，我们将在D2R时预测并测试新的有偏见的配体用于抗精神病药物。 里程碑。该系统的基本特征存在，并且在预测使用SEA的20种药物的35个目标的新目标方面已经证明了原理证明。在这里，我们完善了SEA的“目标”概念，以编码配体偏见。有两个务实的里程碑。我。评估利用以配体观点的五种计算方法来预测从海上到房屋“标记集”受体特征的新偏见的配体。 ii。前瞻性测试20种阻止素在实验上偏向D2R配体预测并进步（a）一种药物为抗精神病动物模型，或（b）最多三种临床前化合物，可用于PK分析，如有保证。 AIM 2：偏置配体相关的GPCR药理学。我们将扩展所有GPCR的地图，以反映有偏见的配体类。这将使我们能够询问该方法的影响力和影响：确定抑制素是否偏见的配体是否会与同一受体或同一受体的规范配体更紧密地将其与无关受体的偏置配体有偏见。 b。 AIM 1的适应方法可预测和测试进一步治疗受体的偏置配体。 里程碑。我们将通过以下方式将功能选择性与已知GPCR药理学的更广泛背景联系起来。将这项研究的有偏见的配体和文献结合在一起，成为全球受体关系图。 ii。通过预测和测试两个受体中的每个受体（40个）从列表F治疗受体中选择的另外20个有偏见的配体来证明广泛的适用性，并具有已知暴露于偏置下游信号传导的配体。尽管这些目标是雄心勃勃的，但初步结果表明它们是可行的。