Computationally Guided Design of Thermostable mutants of GPCR-transducer complexes

GPCR-转导复合物热稳定突变体的计算引导设计

基本信息

批准号：
9279145
负责人：
Nagarajan Vaidehi
金额：
$ 34万
依托单位：
BECKMAN RESEARCH INSTITUTE/CITY OF HOPE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-01 至 2019-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9279145
关键词：
ADORA2A gene Adrenergic Receptor Adverse drug effect Adverse effects Agonist Amino Acids Arrestins Binding Biochemical Biological Assay Birds Cell membrane Cells Communities Complex Computing Methodologies Coupling Cytoplasmic Tail Data Detergents Diabetes Mellitus Drug Targeting Drug abuse Engineering Experimental Designs Feedback Functional disorder G-Protein-Coupled Receptors G-substrate GTP-Binding Proteins Hour Human Interdisciplinary Study Investigation Joints Laboratories Ligands Malignant Neoplasms Mediating Mediator of activation protein Methods Molecular Molecular Conformation Mutation Nature Neurotensin Receptors Outcome Pathway interactions Peptide Receptor Pharmaceutical Preparations Physics Point Mutation Process Property Proteins Publications Resources Schizophrenia Signal Pathway Signal Transduction Specificity Speed Structural Models Structure Testing Therapeutic Therapeutic Index Time Transducers Validation Work base beta-arrestin design experimental study hypertension treatment improved innovation interdisciplinary approach method development mutant novel protein B public health relevance receptor success thermostability

项目摘要

DESCRIPTION (provided by applicant): Upon binding to agonists, G protein-coupled receptors (GPCRs) mediate multiple signaling pathways by coupling to intracellular transducer proteins such as G proteins or ß-arrestins. These agonists, termed biased ligands, confer functional specificity to GPCRs by activating certain signaling pathways over others. Biased ligands promise precise therapeutic benefits with fewer side effects as drugs compared to today's unbiased GPCR-targeted drugs. Unfortunately due to the paucity of structural data on GPCR-transducer complexes as well as the scarcity of known biased ligands, the molecular mechanisms of biased signaling remain elusive. Obtaining experimental data on the structures of the signaling complexes of GPCRs is daunting since the GPCRs are highly dynamic and technically difficult to isolate and purify in the lab. Consequently, structure-based design of biased ligands for therapeutic and further mechanistic experimental studies has been slow. Progress in understanding the complex signaling landscape of GPCRs can be accelerated if we can increase the success and efficiency of experimental trials. Here, we propose an approach that uses a reliable and time-efficient computational method to guide and accelerate concurrent experiments to stabilize and easily purify GPCR transducer complexes. Such methods need to be developed in tandem with experimental advancements. In the short three-year R01 project our (Vaidehi, Tate and Grisshammer) collaborative efforts have resulted in unprecedented computational methods that markedly increased the understanding of the dynamics of GPCR thermostable mutants and accelerate the purification of GPCRs. The progress we have made in developing and applying novel computational methods has opened up unprecedented opportunities to expand and advance the computational toolbox to identify biasing and thermostabilizing GPCR mutants that can bias the conformations of GPCRs to stably pair with different intracellular transducer proteins, the central process in biased signaling. Building on te successes of the previous R01, we propose to advance our interdisciplinary approach with simultaneous computational method developments and experiments to (1) engineer mutant neurotensin receptor 1 (NTSR1) that shows bias signaling even with unbiased agonist, to study the biased signaling mechanisms of this peptide receptor, (2) advance the computational method LITiConDesign, to predict thermostabilizing mutations for GPCR-transducer complexes, and (3) predict thermostabilizing mutations for avian ß1AR-Gs, human A2AR-Gs, ß1AR-ß-arrestin1 and A2AR-ß-arrestin1 complexes and verify these predictions with experiments that would provide feedback to improve the computational methods. The outcome of the proposed work is a powerful computational method for routinely predicting biased and thermostable mutants of GPCR-transducer complexes. The method will also accelerate the unraveling of the mechanism of biased signaling in NTSR1 that can be extended easily to other GPCRs.

描述（由申请人提供）：与激动剂结合后，G 蛋白偶联受体 (GPCR) 通过与细胞内转导蛋白（如 G 蛋白或 ß-arrestins）偶联来介导多种信号传导途径。这些激动剂（称为偏向配体）赋予功能特异性。与当今的无偏配体相比，GPCR 通过激活某些信号通路，有望提供精确的治疗效果，并且副作用更少。 GPCR 靶向药物。不幸的是，由于缺乏 GPCR-转导复合物的结构数据以及已知偏向配体的稀缺，偏向信号传导的分子机制仍然难以获得有关 GPCR 信号传导复合物结构的实验数据。由于 GPCR 具有高度动态性，并且在技术上难以在实验室中进行分离和纯化，因此用于治疗和进一步机制实验研究的基于结构的偏向配体设计进展缓慢。如果我们能够提高实验试验的成功率和效率，就可以加速 GPCR 复杂信号传导景观的发展。在这里，我们提出了一种方法，使用可靠且省时的计算方法来指导和加速并发实验，以稳定和轻松纯化 GPCR 传感器复合物。此类方法需要与实验进展同步开发。在短短三年的 R01 项目中，我们（Vaidehi、Tate 和 Grissammer）的合作成果已经产生了前所未有的计算方法，显着增强了对 GPCR 动力学的理解。我们在开发和应用新型计算方法方面取得的进展为扩展和推进计算工具箱提供了前所未有的机会，以识别偏向和热稳定的 GPCR 突变体，这些突变体可以使 GPCR 的构象偏向稳定配对。不同的细胞内转导蛋白是偏向信号传导的核心过程，在先前 R01 的成功基础上，我们建议通过同步计算方法开发和实验来推进我们的跨学科方法，以 (1) 设计突变体。神经降压素受体 1 (NTSR1) 即使在无偏激动剂的情况下也显示偏向信号传导，以研究该肽受体的偏向信号传导机制，(2) 推进计算方法 LITiConDesign，以预测 GPCR-转导器复合物的热稳定突变，以及 (3) 预测禽类 ß1AR-Gs、人类 A2AR-Gs、ß1AR-ß-arrestin1 和A2AR-ß-arrestin1 复合物并通过实验验证这些预测，这些实验将提供反馈以改进计算方法。该方法还将提供一种强大的计算方法，用于常规预测 GPCR-转导器复合物的偏差和热稳定突变体。加速阐明 NTSR1 中偏向信号传导机制，该机制可以轻松扩展到其他 GPCR。