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（由适用提供）：与激动剂结合后，G蛋白偶联受体（GPCR）培养基多个信号传导途径，通过与细胞内换能器蛋白（例如G蛋白或β-arrestins）耦合。这些激动剂称为有偏的配体，通过激活其他其他信号通路来赋予GPCR的功能特异性。与当今公正的GPCR靶向药物相比，有偏见的配体有偏见的精确治疗益处，而作为药物的副作用较少。不幸的是，由于GPCR转换复合物的结构数据很少以及已知偏置配体的稀缺性，因此有偏置信号传导的分子机制仍然难以捉摸。获得GPCR信号传导复合物的结构的实验数据令人生畏，因为GPCR在实验室中很难隔离和净化。因此，用于热和进一步的机械实验研究的有偏见的配体的基于结构的设计速度很慢。如果我们可以提高实验试验的成功和效率，可以加速理解GPCR的复杂信号传导格局的进展。在这里，我们提出了一种使用可靠且有效的计算方法来指导和加速并发实验，以稳定并轻松净化GPCR传感器复合物。与实验进步一起开发。在短期的三年R01项目中，我们（Vaidehi，Tate和Grishammer）协作工作导致了前所未有的计算方法，从而显着增加了对GPCR热稳定突变体动态的理解，并加速了GPCR的纯化。我们在开发和应用新颖的计算方法方面取得了进展，为扩展和推进计算工具箱的前所未有的机会，以识别偏置和恒温化的GPCR突变体，这些GPCR突变体可以偏向GPCR的构象，以稳定地将GPCR与不同的细胞内传感器蛋白（偏置信号中的集中式过程中的过程）相配对。我们建议以简单的计算方法的发展和实验来推进我们的跨学科方法，以（1）（1）工程师突变神经素受体1（NTSR1），即使没有偏见的激动剂，也表明了偏见，以研究这种偏见的信号受体机制，以预测pepper受体的偏见，（2）计算方法的群体（2） GPCR-透射配合物和（3）预测鸟类1AR-GS，人A2AR-GS，ß1AR-ß-ARRESTIN1和A2AR-ß-ARRESTIN1配合物的恒温突变，并通过实验可以提供反馈以改善计算方法的实验来验证这些预测。拟议的工作的结果是一种强大的计算方法，用于常规预测GPCR-Transducer复合物的偏置和热稳定突变体。该方法还将加速NTSR1中偏置信号传导机制的解体，该机制可以轻松扩展到其他GPCR。