权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

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：
8913703
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/8913703
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 Lead 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 design hypertension treatment improved innovation interdisciplinary approach method development mutant novel public health relevance receptor research study 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β-抑制蛋白）偶联介导多种信号传导途径。这些激动剂，称为偏向配体，通过激活某些信号通路而赋予GPCR功能特异性。与当今无偏见的GPCR靶向药物相比，有偏见的配体承诺精确的治疗益处和更少的副作用。不幸的是，由于缺乏关于GPCR-换能器复合物的结构数据以及已知的偏置配体的稀缺性，偏置信号传导的分子机制仍然难以捉摸。获得关于GPCR的信号传导复合物的结构的实验数据是令人生畏的，因为GPCR是高度动态的，并且在实验室中分离和纯化在技术上是困难的。因此，基于结构的设计偏向配体的治疗和进一步的机制实验研究一直缓慢。如果我们能够提高实验的成功率和效率，就可以加快对GPCR复杂信号转导格局的理解。在这里，我们提出了一种方法，使用一个可靠的和时间有效的计算方法来指导和加速并行实验，以稳定和容易地纯化GPCR换能器复合物。这些方法需要与实验进展同步发展。在短短三年的R 01项目中，我们（Vaidehi，Tate和Grisshammer）的合作努力产生了前所未有的计算方法，显着增加了对GPCR热稳定突变体动力学的理解，并加速了GPCR的纯化。我们在开发和应用新的计算方法方面取得的进展为扩大和推进计算工具箱提供了前所未有的机会，以识别偏置和热稳定的GPCR突变体，这些突变体可以使GPCR的构象与不同的细胞内转导蛋白稳定配对，这是偏置信号传导的中心过程。在先前R 01的成功的基础上，我们提出通过同时的计算方法开发和实验来推进我们的跨学科方法，以（1）工程化突变神经降压素受体1（NTSR 1），其即使使用无偏激动剂也显示偏性信号传导，以研究这种肽受体的偏性信号传导机制，（2）推进计算方法LITiConDesign，预测GPCR-转换器复合物的热稳定突变，和（3）预测禽β 1 AR-Gs、人A2 AR-Gs、β 1 AR-β-arrestin 1和A2 AR-β-arrestin 1复合物的热稳定突变，并通过提供反馈以改进计算方法的实验来验证这些预测。所提出的工作的结果是一个强大的计算方法，定期预测偏见和热稳定突变体的GPCR-换能器复合物。该方法还将加速解开NTSR 1中的偏置信号传导机制，该机制可以容易地扩展到其他GPCR。