Membrane protein structure modeling with experimental restraints

描述（由申请人提供）：在这个项目中，我们将开发一种计算方法来模拟膜蛋白，这种膜蛋白的实验限制数量有限，但实验结构难以获得。我们将利用我们最近开发的超二级结构元件片段库（Smotifs），详尽地分类所有已知的蛋白质构建块。最近我们已经证明，这个Smotifs库在近10年前就饱和了，新的褶皱似乎是现有Smotifs的新组合。因此，我们假设所有的蛋白质折叠都可以从这个文库中构建出来。为了模拟膜蛋白，我们可以计算所有Smotifs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实验中获得和分配。这个提议是关于开发算法，可以匹配实验观察和理论计算的Smotifs的化学位移模式，从而确定形成蛋白质的Smotifs构象子集。该建议的第二部分涉及建立一种优化方法（沿着Smotifs组合的自由度和评分函数的采样算法），该方法将使用从核磁共振偶极耦合数据获得的额外实验约束快速将重叠的Smotifs组装成紧凑的褶皱。在项目的后期，我们将把我们的技术应用于获得化学位移和偶极耦合数据的特定蛋白质上，并随后用自旋标记实验验证我们的计算模型。在本应用中开发的技术将为膜蛋白的有效建模提供所需的基础，而在PDB中可用的实验结构数量非常有限。同时，膜蛋白构成了目前已知药物的大部分靶点。我们的工作重点是提高发现膜蛋白结构的速度，从而为更有效合理的药物设计奠定基础。

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.