Exploring Structure and Sequence Spaces of G Protein-Coupled Receptor Signaling

探索 G 蛋白偶联受体信号传导的结构和序列空间

• 批准号: 8856586
• 负责人: Patrick Daniel Barth
• 金额: $ 30.13万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8856586
• 关键词: Address; Adrenergic Receptor; Amino Acid Sequence; Biological; Cattle; Cells; Communication; Computer Simulation; Coupled; Data; Development; Disease; Dopamine Receptor; Exhibits; Family; Future; G Protein-Coupled Receptor Signaling; G-Protein-Coupled Receptors; Generic Drugs; Genes; Goals; Human; Laboratories; Life; Mediating; Membrane; Modeling; Molecular Conformation; Mutation; Positioning Attribute; Property; Proteins; Research; Resolution; Rhodopsin; Sampling; Sequence Homology; Signal Transduction; Staging; Stimulus; Structural Protein; Structure; System; Techniques; Testing; Therapeutic; Variant; design; drug market; experimental analysis; extracellular; functional genomics; member; programs; receptor; response

DESCRIPTION (provided by applicant): Signaling across biological membranes is critical to living cells and involves membrane- embedded receptors, which transduce extracellular stimuli into cytoplasmic responses through long-range allosteric communication. G protein-coupled receptors (GPCRs) constitute the largest family among these receptors. They are encoded by more than eight hundred genes in humans and are involved in a large diversity of critical functions but also diseases, making GPCRs the target of close to 30 % of current marketed drugs. Although a wealth of genomic and functional data is available on these receptors, the lack of high-resolution structural and mechanistic information hinders the development of specific therapies to modulate their function. The goal of this proposal is to uncover the sequence, structure and energetic relationships governing GPCR signaling properties. We will address this problem using structure modeling, computational protein design, statistical analysis and experimental approaches. An immediate challenge will be to uncover the structure space sampled by representative members of naturally evolved GPCRs. [This will be achieved by modeling the conformations of inactive and active states of the receptor and identifying the networks of physical interactions mediating the allosteric transitions using structural sampling techniques that will be developed within the program RosettaMembrane.] An orthogonal question is which amino-acid sequence space encodes the folding and structural plasticity in GPCRs. It will be answered by statistical comparison between natural sequences and sequences evolved in silico under multiple physical constraints using the design mode of RosettaMembrane. As stringent tests of the accuracy of the structural, energetic and mechanistic predictions, GPCR variants with modified signaling properties will be designed and experimentally tested. The high-resolution information gained from these studies will set the stage for the rational design of GPCR variants with reprogrammed signaling properties for future structural and functional studies at the system level.

描述（由申请人提供）：跨生物膜的信号传导对活细胞至关重要，并涉及膜包埋受体，其通过长距离变构通讯将细胞外刺激转化为细胞质反应。G蛋白偶联受体（GPCR）是这些受体中最大的家族。它们由人类八百多个基因编码，参与多种关键功能，也参与疾病，使GPCR成为目前近30%市售药物的目标。虽然这些受体有丰富的基因组和功能数据，但缺乏高分辨率的结构和机制信息阻碍了调节其功能的特定疗法的发展。该提案的目标是揭示控制GPCR信号性质的序列，结构和能量关系。我们将使用结构建模，计算蛋白质设计，统计分析和实验方法来解决这个问题。一个直接的挑战将是揭示自然进化的GPCR的代表性成员采样的结构空间。[This将通过对受体的非活性和活性状态的构象进行建模，并使用将在RosettaMembrane程序中开发的结构采样技术识别介导变构转换的物理相互作用网络来实现。一个正交问题是哪个氨基酸序列空间编码GPCR中的折叠和结构可塑性。它将回答自然序列和序列之间的统计比较进化在多个物理约束下使用RosettaMembrane的设计模式。作为对结构、能量和机制预测准确性的严格测试，将设计和实验测试具有修饰的信号传导性质的GPCR变体。从这些研究中获得的高分辨率信息将为具有重编程信号传导特性的GPCR变体的合理设计奠定基础，用于未来系统水平的结构和功能研究。