Atomic-level, large-scale structure prediction of G protein-coupled receptors

G蛋白偶联受体的原子水平大规模结构预测

• 批准号: 8105073
• 负责人: Yang Zhang
• 金额: $ 31.59万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-05-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8105073
• 关键词: Acetylcholine; Adrenergic Agents; Adrenergic Receptor; Algorithms; Amino Acid Sequence; Architecture; Bacteriorhodopsins; Benchmarking; Biological Process; Biology; Cattle; Cell Surface Receptors; Chemicals; Collaborations; Communities; Computational algorithm; Computers; Computing Methodologies; Data; Databases; Development; Disease; Dopamine; Drug Delivery Systems; Drug Design; Eukaryotic Cell; Family; Feedback; G-Protein-Coupled Receptors; GTP-Binding Proteins; Generations; Goals; Health; Histamine; Human; Integral Membrane Protein; Knowledge; Length; Ligand Binding; Ligands; Literature; Medical; Membrane Proteins; Methodology; Methods; Modeling; Molecular; Muscarinic Acetylcholine Receptor; Muscarinics; Mutagenesis; Pharmaceutical Preparations; Pharmacologic Substance; Physics; Physiological; Plant Roots; Preclinical Drug Evaluation; Procedures; Protein Family; Proteins; Proteome; Proteomics; Public Health; Relative (related person); Resolution; Rhodopsin; Role; Scientist; Screening procedure; Side; Signal Transduction; Site-Directed Mutagenesis; Speed; Staging; Structure; Testing; Validation; Variant; Vertebral column; Weight; adrenergic; base; chemokine; database structure; design; drug discovery; extracellular; fighting; improved; knowledge base; member; models and simulation; protein activation; protein structure; receptor; repository; research study; restraint; success; three dimensional structure; user-friendly; virtual; web site

DESCRIPTION (provided by applicant): G protein-coupled receptors (GPCRs) are the largest family of integral membrane proteins that occur in nearly every eukaryotic cell to transduce an extracellular signal (ligand binding) into an intracellular signal (G protein activation). This essential physiological role makes them the most important pharmaceutical targets which comprise approximately half of today's modern medicinal drugs. Clearly, 3D-structures of GPCRs would provide essential atomic-level information for elucidating the molecular organization and for efficient virtual screening of drug databases. However, except for the recently solved human beta2-andrenergic receptor, it has not yet been possible to obtain experimental structural information for other human GPCRs. Building on the recent success of the threading assemble refinement (TASSER) algorithm for reduced-level GPCR modeling, this proposal seeks to develop new computational methodologies for the generation of experiment- validated, atomic-level GPCR models. The focus will be on five pharmaceutically important families including Adrenergic, Chemokine, Dopamine, Histamine, and Muscarinic acetylcholine. Specific aims of the project are: (1) Development and benchmarking of a new GPCR-TASSER algorithm for atomic-level GPCR protein structure modeling. (2) Development and optimization of composite atomic and reduced GPCR potentials. (3) Dissemination of GPCR-TASSER algorithm for public use and examination. (4) Application of GPCR-TASSER to the pharmaceutically important GPCRs. (5) Validation and refinement of the GPCR models with experiment collaborators. The long-term goals are (a) to develop a set of computer algorithms for automated and atomic- level GPCR structure prediction (b) to extend the methodology to proteomic-scale structure modeling for all GPCRs in UniProt database (c) to construct a central repository for publicly-accessible GPCR algorithms and structure databases which are designed to eventually alleviate the urgent need in biology and medical communities for the detailed atomic GPCR structures. PUBLIC HEALTH RELEVANCE: In modern structure-based drug design, scientists use detailed knowledge of the 3-dimensional structure of protein targets associated with particular diseases to design synthetic compounds that fight the disease. More than half of all drug targets are G protein-coupled receptors (GPCRs), a family of proteins whose structures are extremely difficult to obtain by experiment. The development of computer-based algorithms that are able to generate high resolution GPCR structures will speed up the initial screening of putative chemical compounds and therefore have an important impact on the field of the new drug discovery and public health.

描述（由申请人提供）：G蛋白偶联受体（GPCR）是最大的整合膜蛋白家族，几乎存在于每种真核细胞中，将细胞外信号（配体结合）转换为细胞内信号（G蛋白激活）。这种重要的生理作用使它们成为最重要的药物靶标，占当今现代药物的大约一半。显然，GPCR的3D结构将为阐明分子组织和药物数据库的有效虚拟筛选提供必要的原子级信息。然而，除了最近解决的人β 2-肾上腺素能受体，它还没有可能获得其他人类GPCR的实验结构信息。基于最近成功的线程组装细化（TASSER）算法的减少级别的GPCR建模，该建议旨在开发新的计算方法的实验验证，原子级GPCR模型的生成。重点将放在五个重要的药物家族，包括肾上腺素，趋化因子，多巴胺，组胺和毒蕈碱乙酰胆碱。本项目的具体目标是：（1）开发一种新的用于原子级GPCR蛋白质结构建模的GPCR-TASSER算法并进行基准测试。(2)复合原子和还原GPCR势的开发和优化。(3)传播GPCR-TASSER算法供公众使用和检查。(4)GPCR-TASSER在药物重要GPCR中的应用。(5)与实验合作者一起验证和完善GPCR模型。长期目标是（a）开发一套用于自动化和原子级GPCR结构预测的计算机算法（B）以将该方法扩展到UniProt数据库中所有GPCR的蛋白质组学规模结构建模（c）构建一个用于公开可访问的GPCR算法和结构数据库，旨在最终缓解生物学和医学界对详细原子结构的迫切需求。GPCR结构。公共卫生相关性：在现代基于结构的药物设计中，科学家利用与特定疾病相关的蛋白质靶点的三维结构的详细知识来设计对抗疾病的合成化合物。超过一半的药物靶点是G蛋白偶联受体（GPCR），这是一个蛋白质家族，其结构极难通过实验获得。开发能够生成高分辨率GPCR结构的基于计算机的算法将加快推定化合物的初步筛选，因此对新药发现和公共卫生领域产生重要影响。