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: 10074763
• 负责人: GAETANO T MONTELIONE
• 金额: $ 47.69万
• 依托单位: RENSSELAER POLYTECHNIC INSTITUTE
• 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/10074763
• 关键词: Membrane; Protein; Structure; Using; Evolutionary

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.

项目概要 整合膜蛋白 (IMP) 包括许多生物医学上重要的守门者、受体、 转运蛋白、稳态调节剂和潜在的药物发现靶标。 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 通常可以提供小可溶性蛋白质的准确 3D 结构，但结构 通过溶液 NMR 测定在稳定膜模拟环境中制备的 IMP 通常需要 IMP 的 2H、13C、15N 富集，这可能是相当具有挑战性的。 耦合（EC），源自多重序列比对的进化相关突变，可以 也可用于提供有关天然残基对接触的信息，以及对 3D 模型进行建模 结合 EC 和 NMR 数据提供了克服 IMP 结构的强大方法。 从全氘化 IMP 样品获得的 NMR NOESY 数据不完整，以及在 从系统发育 EC 分析中识别真正的天然蛋白质结构联系。 通过 NMR 很难获得全氘化 IMP 的螺旋间接触信息， 以序列协方差 EC 数据表示。我们的目标是开发一个稳健的、可重复的、 以及全自动 EC-NMR 平台，适用于准确可靠的结构测定 IMP，特别是 α-螺旋 IMP，并将这些方法应用于生物医学的 3D 结构分析 重要的 IMP 将使用已知的 β-桶形和 α-螺旋 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 IMP 的研究 NIAID 优先致病菌我们将 (i) 进一步开发并应用单一蛋白质生产。 (SPP) 在大肠杆菌中生产富含同位素的 IMP 的方法，(ii) 实施微尺度 NMR IMP 样品优化的筛选流程，(iii) 严格、全面地解决 EC 和 NOESY 数据质量和数量如何与 EC-NMR 准确性相关的问题 结构，(iv) 设计改进的算法，结合 EC 和 NMR 数据，以及 (v) 开发用于验证由传统方法确定的 IMP 结构的工具 将采用先进的分子建模方法来改进 NMR 和 EC-NMR 方法。 EC-NMR 结构的准确性也将与 NMR 数据相结合来识别和确定。 这项研究将扩大蛋白质的范围。 通过 NMR 研究，提供比可获得的更准确的结构和动态信息 与现有方法，并提供未来抗生素所需的基本结构信息 针对高优先级病原体的药物开发。