Membrane Protein Structure Using Evolutionary Couplings and Sparse NMR Data

使用进化耦合和稀疏 NMR 数据的膜蛋白结构

• 批准号: 9383967
• 负责人: GAETANO T MONTELIONE
• 金额: $ 51.6万
• 依托单位: RUTGERS, THE STATE UNIV OF N.J.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9383967
• 关键词: Address; Advisory Committees; Algorithmic Software; Algorithms; Antibiotics; Base Sequence; Benchmarking; Binding Proteins; Bioinformatics; Biological; Complex; Computing Methodologies; Coupling; Cryoelectron Microscopy; Data; Data Quality; Detergents; Dimensions; Dimerization; Electron Microscopy; Ensure; Environment; Enzymes; Equilibrium; Escherichia coli; Future; Genome; Goals; Homeostasis; Hybrids; Integral Membrane Protein; Isotope Labeling; Isotopes; Ligand Binding; Lipoproteins; Literature; Membrane; Membrane Proteins; Methods; Micelles; Modeling; Molecular Conformation; Molecular Models; Multi-Drug Resistance; Mutation; NOESY; National Institute of Allergy and Infectious Disease; Nuclear Magnetic Resonance; Phylogenetic Analysis; Preparation; Production; Program Development; Proteins; Protocols documentation; Reproducibility; Research; Resolution; Resources; Sampling; Sequence Alignment; Structure; System; Testing; Time; United States National Institutes of Health; Validation; X-Ray Crystallography; biodefense; cryogenics; design; dimer; drug development; drug discovery; improved; innovation; maltose-binding protein; method development; molecular modeling; nanodisk; pathogen; pathogenic bacteria; periplasm; programs; protein reconstitution; protein structure; receptor; screening; solid state nuclear magnetic resonance; structural biology; success; three dimensional structure; three-dimensional modeling; tool

PROJECT SUMMARY Integral Membrane Proteins (IMPs) include many biomedically-important gate keepers, receptors, transporters, homeostasis regulators, and potential drug discovery targets. Three-dimensional (3D) structure determination of IMPs by X-ray crystallography, cryo-electron microscopy (cryo-EM), or Nuclear Magnetic Resonance (NMR) methods remains a major challenge for structural biology. While NMR can generally provide accurate 3D structures of small soluble proteins, structure determination by solution NMR of IMPs, prepared in stabilizing membrane-mimicking environments which generally require 2H,13C,15N-enrichment of the IMP, can be quite challenging. Evolutionary couplings (ECs), evolutionarily-correlated mutations derived from multiple sequence alignments, can also be used to provide information about native residue pair contacts, and to model the 3D structures of IMPs. Combining EC and NMR data provides a powerful approach for overcoming incompleteness of NMR NOESY data obtained for perdeuterated IMP samples, and the challenges in identifying true native protein structure contacts from the phylogenetic EC analysis. In particular, inter-helical contact information that is difficult to obtain for perdeuterated IMPs by NMR is well represented in the sequence co-variance EC data. Our goals are to develop a robust, reproducible, and fully automated EC-NMR platform suitable for accurate and reliable structure determination of IMPs, particularly α-helical IMPs, and apply these methods for 3D structure analysis of biomedically- important IMPs. EC-NMR will be further developed using β-barrel and α-helical IMPs of known structure, and then applied to studies of IMPs of unknown structure selected from designated NIH NIAID priority pathogenic bacteria. We will (i) further develop and apply the Single Protein Production (SPP) method for producing isotope-enriched IMPs in E. coli, (ii) implement a micro-scale NMR screening pipeline for IMP sample optimization, (iiii) rigorously and comprehensively address the question of how EC and NOESY data quality and quantity correlate with the accuracy of EC-NMR structures, (iv) design improved algorithms for structure determination of IMPs combining ECs and NMR data, and (v) develop tools for validation of IMP structures determined by both conventional NMR and EC-NMR methods. Advanced molecular modeling methods will be implemented to improve accuracy of EC-NMR structures. ECs will also be combined with NMR data to identify and determine structures of multiple “native states” of proteins. This study will expand the range of proteins that can be studied by NMR, provide more accurate structural and dynamic information than can be obtained with existing methods, and provide fundamental structural information needed for future antibiotic drug development targeted to high-priority pathogens.

项目摘要 整体膜蛋白（IMP）包括许多生物医学重要的门守门员，接收器， 转运蛋白，稳态调节剂和潜在的药物发现靶标。三维（3D） 通过X射线晶体学，冷冻电子显微镜（Cryo-EM）或 核磁共振（NMR）方法仍然是结构生物学的主要挑战。 虽然NMR通常可以提供小固体蛋白的精确3D结构，但结构 通过溶液NMR的IMPS测定，在稳定膜模拟环境中制备 通常需要2h，13c，15n富集的IMP，这可能是非常挑战的。进化 耦合（EC），来自多个序列比对的进化相关的突变，可以 也可用于提供有关本地居住对触点的信息，并为3D建模 小鬼结构。结合EC和NMR数据为克服提供了强大的方法 对于perdeuter的IMP样本获得的NMR NOESY数据的不完整，以及在 从系统发育EC分析中确定真正的天然蛋白质结构接触。尤其， NMR难以获得的Perdeuterated Imps很难获得的螺旋间接触信息很好 在序列共同变异EC数据中表示。我们的目标是开发一个健壮，可重复的， 以及完全自动化的EC-NMR平台，适用于准确可靠的结构确定 Imps，尤其是α-螺旋的IMP，并将这些方法应用于生物医学上的3D结构分析 重要的小鬼。 EC-NMR将使用已知的β-桶和α-螺旋的IMP进一步开发 结构，然后应用于从指定NIH中选择的未知结构的小鬼研究 NIAID优先致病细菌。我们将（i）进一步开发并应用单蛋白生产 （SPP）在大肠杆菌中产生富含同位素的IMP的方法，（ii）实施微型NMR 筛选IMP样品优化的管道，（iiii）严格，全面地解决 EC和NOESY数据质量和数量与EC-NMR的准确性相关的问题 结构，（iv）设计改进的算法，用于结合EC和EC结合的IMPS结构 NMR数据和（v）开发工具用于验证由两种常规的IMP结构确定的IMP结构 NMR和EC-NMR方法。将实施高级分子建模方法以改进 EC-NMR结构的准确性。 EC还将与NMR数据合并以识别和确定 蛋白质多种“本地状态”的结构。这项研究将扩大可以 通过NMR进行研究，提供比获得更准确的结构和动态信息 使用现有方法，并提供未来抗生素所需的基本结构信息 药物开发针对高优先性病原体。