Membrane Protein Structure Using Evolutionary Couplings and Sparse NMR Data

项目总结 整合膜蛋白(IMP)包括许多生物医学上重要的门把守、受体、 转运体、动态平衡调节器和潜在的药物发现目标。三维(3D) 用X射线结晶学、低温电子显微镜(Cryo-EM)测定IMPS的结构 核磁共振(核磁共振)方法仍然是结构生物学的主要挑战。 虽然核磁共振通常可以提供小分子可溶蛋白质的准确3D结构，但结构 仿膜稳定环境中制备的IMPS的溶液核磁共振测定 这通常需要IMP的2H，13C，15N-浓缩，可能是相当具有挑战性的。进化论 偶联(ECs)是源于多个序列比对的进化相关突变，可以 还可用于提供有关天然残基对接触的信息，并对3D进行建模 小鬼的结构。结合EC和核磁共振数据提供了一个强大的方法来克服 过氚IMP样品的核磁共振NOESY数据的不完全性，以及在 从系统发育EC分析中鉴定真正的天然蛋白质结构接触。特别是， 用核磁共振很难获得的过氚IMPS螺旋间联系信息是很好的 以序列协方差EC数据表示。我们的目标是开发一种健壮的、可再生的、 和全自动的EC-核磁共振平台，适用于准确可靠的结构测定 IMPS，特别是α-螺旋IMPS，并将这些方法应用于生物医学中的三维结构分析- 重要的小鬼。EC-核磁共振将使用已知的β-Barrel和α-Helical IMPS进一步开发 结构，然后将其应用于从指定的NIH选择的未知结构的IMP的研究 NIAID优先致病菌。我们将(一)进一步开发和应用单蛋白生产 (SPP)在大肠杆菌中生产富同位素IMP的方法，(II)实现微型核磁共振 IMP样品优化筛选流水线，(三)严格全面解决 EC和NOESY数据的质量和数量如何与EC-核磁共振的准确性相关的问题 结构，(Iv)设计了结合ECS和ECS的IMPS结构确定改进算法 核磁共振数据，以及(V)开发工具来验证由传统的 核磁共振和EC-核磁共振方法。将实施先进的分子建模方法，以提高 EC-核磁共振结构的准确性。ECS还将与核磁共振数据相结合，以识别和确定 蛋白质的多个“自然状态”的结构。这项研究将扩大可以 被核磁共振研究，提供比所能获得的更准确的结构和动态信息 与现有方法进行比较，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。

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.