Computational methods for NMR structure determination of proteins in membranes

描述（由申请人提供）：本申请是对PA-09-164 NIH探索/发展研究赠款的回应。该项目的总体目标是开发新的计算方法，用于在磷脂双层膜的天然功能环境中对膜蛋白进行NMR结构分析。这些蛋白质/脂质大分子复合物是具有挑战性的结构生物学的传统方法，但可以使用定向样品的固态NMR光谱进行表征。计算方法的发展是这种方法的一个重要方面。从定向样品的光谱中包含的信息是独特的，它能够提供蛋白质结构的直接图像，并且与从各向同性样品获得的NMR光谱非常不同。因此，它需要一种不同的数据分析方法。该项目的具体目标旨在利用生物信息学，数值方法和模拟退火方法的分子动力学的最新发展。计算方法将被开发，测试和实施的NMR数据在实验室中获得的两个研究人员在这个项目上，Marassi（伯纳姆）和Opella（加州大学圣地亚哥分校），为α-螺旋和<$-桶膜中的膜蛋白的大量。这些研究人员将与在生物分子结构计算、生物信息学和结构预测方面具有互补专业知识的计算机科学家密切合作。目标是将定向样品NMR计算方法与XPLOR- NIH和ROSETTA程序的能力联合收割机相结合。 公共卫生相关性：这项研究将开发和实施新的计算工具，用于从实验NMR数据计算膜蛋白的三维结构。膜蛋白是药物受体的主要类别，这项研究将加速许多疾病药物的发现。

DESCRIPTION (provided by applicant): This application is in response to PA-09-164 for NIH Exploratory/Developmental Research Grants. The overall goal of the project is to develop new computational methods for NMR structural analysis of integral membrane proteins within their native, functional environment of the phospholipid bilayer membrane. These protein/lipid macromolecular complexes are challenging for the conventional methods of structural biology but can be characterized using solid-state NMR spectroscopy of oriented samples. The development of computational methods is an essential aspect of this approach. The information contained in the spectra from oriented samples is unique in its ability to provide direct images of protein structures, and very different from that of NMR spectra obtained from isotropic samples. Thus, it requires a different approach for data analysis. The Specific Aims of this project are designed to take advantage of recent developments in bioinformatics, numerical methods, and molecular dynamics for simulated annealing methods. The computational methods will be developed, tested and implemented for a large body of NMR data obtained in the laboratories of the two investigators on this project, Marassi (Burnham) and Opella (UCSD), for both a-helical and ¿-barrel integral membrane proteins in membranes. These investigators will work closely with computer scientists with complementary expertise in biomolecular structure calculation, and bioinformatics and structure prediction. The Aims will be to combine the oriented sample NMR computational methods with the capabilities of the XPLOR- NIH and ROSETTA programs. PUBLIC HEALTH RELEVANCE: This research will develop and implement new computational tools for calculating the three-dimensional structures of membrane proteins from experimental NMR data. Membrane proteins are the principal class of drug receptors and this research will accelerate the discovery of drugs for many diseases.