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

Threading transmembrane protein structures: G protein-coupled receptor case study

线程跨膜蛋白结构：G 蛋白偶联受体案例研究

基本信息

批准号：
8281460
负责人：
Dorothy A. Hammond
金额：
$ 1.44万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-07-01 至 2013-10-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8281460
关键词：
Address Algorithms Alzheimer&apos s Disease Biological Process Case Study Cell physiology Cells Cellular Membrane Characteristics Computer Assisted Computer software Data Data Set Databases Diabetes Mellitus Disease Ensure Exons Expressed Sequence Tags Family Functional disorder G-Protein-Coupled Receptors Genbank Human Integral Membrane Protein Ions Length Lipids Membrane Proteins Modeling Mutation One-Step dentin bonding system Pharmaceutical Preparations Pharmacologic Substance Protein Isoforms Proteins Public Health Publishing RNA Splicing Research Respiration Rest Review Literature Rhodopsin Role Running Signal Transduction Structure System Techniques Variant Vertebral column abstracting base computer framework design human data malignant stomach neoplasm programs protein structure protein structure prediction receptor three dimensional structure tool trafficking

项目摘要

Project Summary/Abstract The purpose of this proposed study is to develop and validate threading framework for accurately predicting full-length helical trans-membrane proteins; then apply these algorithms to predict the structures of human G-protein coupled receptor (GPCR) proteins and their spliced variants. Trans-membrane proteins are very important aspect of human biological function, they serve critical roles in cellular processes such as respiration, signal transduction, cell trafficking, and transport of compounds and ions across cellular membranes. Dysfunctions in some trans-membrane proteins have been associated with diseases such as Alzheimer¿s and diabetes [1, 2]. They are also a target for more than 50% of pharmaceutical drugs. To better understand the mechanism of their function, which in turn help better understand the mechanism of their associated diseases, the three dimensional (3D) structure must be determined. This research seeks to provide a threading framework for predict the 3D structure of membrane proteins, using GPCR as case study, through the technique called threading. Threading is when a query sequence is aligned to all representative structures energetically. To achieve the above aims, a threading-based framework for predicting the backbone structures of alpha helical trans-membrane proteins will be developed, then adapt exiting structural refinement tools to obtain full-atom structures. Next, the threading framework obtained and refined in step one and two will be applied to the about 701 human rhodopsin GPCR and its spliced variants.

项目总结/摘要本研究的目的是开发和验证准确预测全长螺旋跨膜蛋白的线程框架，然后应用这些算法预测人类G蛋白偶联受体（GPCR）蛋白及其剪接变体的结构。跨膜蛋白是人体生物学功能的重要组成部分，在呼吸、信号转导、细胞运输、跨膜转运等细胞过程中发挥着重要作用。一些跨膜蛋白的功能障碍与阿尔茨海默病和糖尿病等疾病有关[1，2]。它们也是超过50%的药物的目标。为了更好地理解其功能的机制，这反过来又有助于更好地理解其相关疾病的机制，必须确定三维（3D）结构。本研究以GPCR为例，通过线程技术，为膜蛋白的三维结构预测提供了一个线程框架。线程化是指将查询序列与所有代表性结构进行能量比对。为了实现上述目标，将开发一个基于线程的框架来预测α螺旋跨膜蛋白的骨架结构，然后调整现有的结构精修工具以获得全原子结构。接下来，将在步骤一和步骤二中获得和精制的穿线框架应用于约701个人视紫红质GPCR及其剪接变体。