Computational methods for NMR structure determination of proteins in membranes

描述（由申请人提供）：本申请是对NIH探索性/发展性研究资助的PA-09-164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整体膜蛋白进行核磁共振结构分析。这些蛋白质/脂质大分子复合物对传统的结构生物学方法具有挑战性，但可以使用定向样品的固态核磁共振波谱进行表征。计算方法的发展是这种方法的一个重要方面。定向样品光谱中包含的信息在提供蛋白质结构直接图像的能力方面是独一无二的，与从各向同性样品中获得的核磁共振光谱有很大不同。因此，它需要一种不同的数据分析方法。该项目的具体目标是利用生物信息学、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，用于该项目的两位研究者，Marassi （Burnham）和Opella （UCSD）的实验室中获得的大量核磁共振数据，用于膜中的a-螺旋和¿-桶整体膜蛋白。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。目标是将定向样品核磁共振计算方法与XPLOR- NIH和ROSETTA计划的能力相结合。

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.