Membrane protein structure modeling with experimental restraints

具有实验限制的膜蛋白结构建模

基本信息

批准号：
8025220
负责人：
Andras Fiser
金额：
$ 31.54万
依托单位：
ALBERT EINSTEIN COLLEGE OF MEDICINE
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：
2011-05-01 至 2015-04-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): In this project we will develop a computational approach to model membrane proteins for which a limited number of experimental restraints are available but for which the experimental structure is difficult to obtain. We will utilize our recently developed fragment library of supersecondary structure elements (Smotifs) that exhaustively classifies all known building blocks of proteins. Recently we have shown that this library of Smotifs saturated almost 10 years ago, and that new folds seem to be a novel combination of existing Smotifs. Therefore we hypothesize that all protein folds should be possible to build from this library. In order to model membrane proteins we can calculate hypothetical chemical shift values for all our Smotifs, while chemical shift values for a protein of interest can usually be quickly and easily obtained and assigned from initial NMR experiments. This proposal is concerned with developing algorithms that can match experimentally observed and theoretically calculated chemical shift patterns of Smotifs and therefore identify a subset of Smotif conformations that form a protein. The second part of the proposal is concerned of setting up an optimization approach (a sampling algorithm along the degrees of freedom of Smotif combinations and a scoring function) that will rapidly assemble overlapping Smotifs into compact folds using additional experimental restraints obtained from NMR dipolar coupling data. In later years of the project we will apply our technique on specific proteins for which chemical shift and dipolar coupling data were obtained and subsequently verify our computational models with spin labeling experiments. The technologies developed in this application will provide the foundation required for efficient modeling of membrane proteins for which a very limited number of experimental structures are available in the PDB. Meanwhile membrane proteins constitute the majority of targets of currently known drugs. Our effort is focused on increasing the rate of discovering membrane protein structures and therefore will lay a foundation for more effective rational drug design. PUBLIC HEALTH RELEVANCE: The majority of currently known drugs target membrane proteins, of which only about 0.5% have been structurally characterized. In this proposal we will develop a fragment assembly modeling approach that takes advantage of NMR chemical shift data and our recently developed supersecondary structure library. Our effort is concerned with increasing the rate of discovering membrane protein structures and will lay a foundation for effective rational drug design for this important class of proteins.

描述（由申请人提供）：在此项目中，我们将开发一种计算方法来建模膜蛋白，可为其提供有限数量的实验约束，但很难获得实验结构。我们将利用我们最近开发的超二级结构元素（SMOTIFS）的片段，这些元素（SMOTIFS）详尽地对所有已知的蛋白质构建块进行了分类。最近，我们证明了大约10年前的Smotifs库饱和，而新折叠似乎是现有Smotifs的新型组合。因此，我们假设所有蛋白质折叠都应从该库中构建。为了建模膜蛋白，我们可以计算所有SMOTIF的假设化学位移值，而感兴趣的蛋白质的化学位移值通常可以快速，轻松地从初始NMR实验中获得并分配。该建议与开发可以与SMOTIF的实验观察到的化学位移模式相匹配的算法涉及，因此确定了形成蛋白质的SMOTIF构象的子集。该提案的第二部分涉及建立一种优化方法（沿SMOTIF组合自由度和评分函数的抽样算法和一个评分函数），该方法将使用从NMR偶极coupling数据获得的其他实验限制来迅速将重叠的SMOTIF迅速组装成紧凑的折叠中。在该项目的后期，我们将应用我们的技术，将获得化学位移和偶极偶联数据的特定蛋白质应用于特定蛋白质，并随后通过自旋标记实验验证我们的计算模型。本应用程序中开发的技术将为膜蛋白有效建模所需的基础，在PDB中可用的实验结构非常有限。同时，膜蛋白构成了当前已知药物的大多数靶标。我们的努力集中在提高发现膜蛋白结构的速度上，因此将为更有效的理性药物设计奠定基础。公共卫生相关性：大多数当前已知的药物靶向膜蛋白，其中仅在结构上表征了约0.5％。在此提案中，我们将开发一种碎片组装建模方法，该方法利用NMR化学移位数据和我们最近开发的超副结构库。我们的努力与提高发现膜蛋白结构的速度有关，并将为这类重要的蛋白质有效合理药物设计奠定基础。