Mapping the Ligand-Modulated Conformational Landscape of GPCRs

绘制 GPCR 配体调节的构象图谱

• 批准号: 8594673
• 负责人: Morgan Elizabeth Lawrenz
• 金额: $ 5.22万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-19 至 2014-08-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8594673
• 关键词: Active Sites; Adenosine; Adenosine A2A Receptor; Adenylate Cyclase; Adrenergic Receptor; Affect; Affinity; Agonist; Algorithms; Allosteric Site; Architecture; Arrestins; Binding; Binding Sites; Biological; Biological Assay; Cardiovascular Physiology; Complex; Computer Assisted; Computer Simulation; Data; Data Set; Detergents; Docking; Drug Design; Drug Targeting; Event; G-Protein-Coupled Receptors; GTP-Binding Proteins; Goals; Impaired cognition; Information Theory; Kinetics; Lead; Ligand Binding; Ligands; Lipids; Maps; Membrane; Membrane Proteins; Methods; Micelles; Mining; Modeling; Parkinson Disease; Pathway interactions; Pharmaceutical Preparations; Population; Process; Property; Protein Activation Pathway; Protein Binding; Proteins; Receptor Activation; Research; Research Project Grants; Running; Sampling; Signal Pathway; Signal Transduction; Signaling Molecule; Simulate; Site; Solvents; Specificity; Structure; Techniques; Testing; Thermodynamics; Time; adenosine receptor activation; cluster computing; computer studies; conformational conversion; desensitization; design; drug efficacy; extracellular; improved; inhibitor/antagonist; mimetics; molecular dynamics; motor impairment; network models; novel; public health relevance; receptor; receptor binding; receptor coupling; research study; screening; simulation; small molecule; statistics; theories; virtual

DESCRIPTION (provided by applicant): G-protein coupled receptors (GPCRs) are membrane proteins that bind a variety of ligands and modulate many important biological signal cascades. Understanding ligand-biased functional dynamics of these GPCRs can direct the design of more effective and targeted drugs. Recent GPCR structures give opportunity for computational study of receptor dynamics. This research project studies two GPCRs, the ¿2 adrenergic receptor (¿2AR) and the A2A adenosine receptor (A2AR) with simulations of the proteins embedded in detergent micelles, a membrane mimetic that is often used in biophysical experiments. The specific aims are: 1) To predict the full activation and deactivation mechanism for ¿2AR and A2AR. With unique distributed computing architectures, we will run massively parallel all-atom, explicit solvent, explicit lipid molecular dynamics simulations of ¿2AR and A2AR bound to a variety of ligands. With robustly parameterized simulations at unprecedented timescales, we expect to predict the inactive-to-active transitions for these GPCRs for the first time. We use statistical analysis with Markov State Models (MSMs) and Transition Path Theory to reveal the most probable pathways and the kinetics of ¿2AR and A2AR activation and deactivation. These methods allow us to quantify ligand-induced population shifts that select the G-protein and, for ¿2AR, the ¿-arrestin pathways from the conformational landscape. 2) To investigate allosteric modulation of ¿2AR and A2AR conformational landscapes. Allosteric modulation of GPCRs is very attractive due to the ubiquity of the receptor active sites and the diverse conformational tuning, which can be utilized to give site-specific and event specific action. However, no selective small molecule allosteric modulators have been identified for ¿2AR and A2AR. We plan to mine the wealth of ¿2AR and A2AR simulation data obtained in aim (1) with MSMs and information theory methods to identify correlations and connectivity indicative of allosteric networks. These networks will guide targeted small molecule docking to putative allosteric sites. Top allosteric docking hits will be evaluated with experiments.

描述（由应用提供）：G蛋白偶联受体（GPCR）是结合多种配体并调节许多重要的生物信号级联的膜蛋白。了解这些GPCR的配体偏置功能动力学可以直接设计更有效和有针对性的药物。最近的GPCR结构为受体动力学的计算研究提供了机会。该研究项目研究了两个GPCR，即2个肾上腺素受体（2AR）和A2A腺苷受体（A2AR），并使用嵌入胶束中的蛋白质模拟，这是一种经常用于生物物理实验中的膜模拟物。具体目的是：1）预测2AR和A2AR的全部激活和失活机制。借助独特的分布式计算体系结构，我们将运行大量平行的全原子，明确的溶剂，显式的脂质分子动力学模拟»2AR和A2AR与各种配体结合。在前所未有的时间尺度上，我们希望首次预测这些GPCR的非活动性转变。我们使用马尔可夫州模型（MSM）和过渡路径理论使用统计分析来揭示最有问题的途径以及2AR和A2AR激活和失活的动力学。这些方法使我们能够量化配体诱导的种群转移，从而选择了G蛋白，并且对于2AR，从构象范围内使用的 - - arrestin途径。 2）研究2AR和A2AR构象景观的变构调节。 GPCR的变构调节非常有吸引力，因为受体活动位点的无处不在和发散的构象调整，可用于提供特定于现场和事件的动作。但是，尚未确定针对2AR和A2AR的选择性小分子变构调节剂。我们计划以AIM（1）获得MSMS和信息理论方法获得的2AR和A2AR仿真数据的财富，以识别指示变构网络的相关性和连接性。这些网络将指导针对性的小分子对接到推定的变构位点。将通过实验评估顶部的变构对接命中。