蛋白质磁共振——从结构生物学到结构基因组学

在后基因组时代,随着大量物种全基因组序列的获得,结构生物学家面临着结构基因组学的新机遇和挑战。与传统的结构生物学不同的是,结构基因组学的研究主要集中在结构和功能未知并且与从前研究的蛋白质相似性很小的蛋白质。准确的来讲,结构基因组学通过高通量蛋白质表达、结构解析来完成所有蛋白质家族的结构表征,从而能够通过结构预测功能。加州结构基因组学联合实验室发展了高度自动化的蛋白质合成、结晶、结构解析生产线。然而由于一些蛋白质不能被结晶,要想覆盖所有蛋白质结构域还有很大困难。Wuthrich的研究小组通过一些高通量的目的蛋白质筛选和NMR结构解析的方法解决了这一难题。与X射线晶体学解析蛋白质结构相比,NMR技术由于能够解析更接近生理状态的溶液结构而具有互补性。通过获得溶液中的蛋白质稳定性、动力学特征和相互作用信息,正如在朊蛋白和SARS相关蛋白的研究中所表现的那样,NMR技术从扩大已知的蛋白质结构数据库、新的蛋白质功能到化学生物学研究中都扮演着激动人心的角色。     

NMR assignments of the yellow fever virus envelope protein domain III

Nearly complete backbone and sidechain resonance assignments have been obtained for the third domain, residues S288–K398, of the envelope protein from the Asibi strain of yellow fever virus using double- and triple-resonance spectroscopy.     

Solid-state NMR triple-resonance backbone assignments in a protein

Triple-resonance solid-state NMR spectroscopy is demonstrated to sequentially assign the 13C and 15N amide backbone resonances of adjacent residues in an oriented protein sample. The observed 13C chemical shift frequency provides an orientational constraint complementary to those measured from the 1H and 15N amide resonances in double-resonance experiments.     

Efficient analysis of protein 2D NMR spectra using the software packageEASY

Summary The programEASY supports the spectral analysis of biomacromolecular two-dimensional (2D) nuclear magnetic resonance (NMR) data. It provides a user-friendly, window-based environment in which to view spectra for interactive interpretation. In addition, it includes a number of automated routines for peakpicking, spin-system identification, sequential resonance assignment in polypeptide chains, and cross peak integration. In this uniform environment, all resulting parameter lists can be recorded on disk, so that the paper plots and handwritten notes which normally accompany manual assignment of spectra can be largely eliminated. For example, in a protein structure determination by 2D¹H NMR,EASY accepts the frequency domain datasets as input, and after combined use of the automated and interactive routines it can yield a listing of conformational constraints in the format required as input for the calculation of the 3D structure. The program was extensively tested with current protein structure determinations in our laboratory. In this paper, its main features are illustrated with data on the protein basic pancreatic trypsin inhibitor.     

Principal components analysis of protein structure ensembles calculated using NMR data

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations.     

Solution NMR structure determination of proteins revisited

This 'Perspective' bears on the present state of protein structure determination by NMR in solution. The focus is on a comparison of the infrastructure available for NMR structure determination when compared to protein crystal structure determination by X-ray diffraction. The main conclusion emerges that the unique potential of NMR to generate high resolution data also on dynamics, interactions and conformational equilibria has contributed to a lack of standard procedures for structure determination which would be readily amenable to improved efficiency by automation. To spark renewed discussion on the topic of NMR structure determination of proteins, procedural steps with high potential for improvement are identified.     

Tools for the automated assignment of high-resolution three-dimensional protein NMR spectra based on pattern recognition techniques

One of the major bottlenecks in the determination of proteinstructures by NMR is in the evaluation of the data produced by theexperiments. An important step in this process is assignment, where thepeaks in the spectra are assigned to specific spins within specificresidues. In this paper, we discuss a spin system assignment tool based onpattern recognition techniques. This tool employs user-specified templatesto search for patterns of peaks in the original spectra; these patterns maycorrespond to side-chain or backbone fragments. Multiple spectra willnormally be searched simultaneously to reduce the impact of noise. Thesearch generates a preliminary list of putative assignments, which arefiltered by a set of heuristic algorithms to produce the final results list.Each result contains a set of chemical shift values plus information aboutthe peaks found. The results may be used as input for combinatorialroutines, such as sequential assignment procedures, in place of peak lists.Two examples are presented, in which (i) HCCH-COSY and -TOCSY spectra arescanned for side-chain spin systems; and (ii) backbone spin systems aredetected in a set of spectra comprising HNCA, HN(CO)CA, HNCO, HN(CA)CO,CBCANH and CBCA(CO)NH.     

Chemical shift based editing of CH<Subscript>3</Subscript> groups in fractionally <Superscript>13</Superscript>C-labelled proteins using GFT (3, 2)D CT-H<Emphasis Type="Underline">CC</Emphasis>H-COSY: stereospecific assignments of CH<Subscript>3</Subscript> groups of Val and Leu residues

We propose a (3, 2)D CT-HCCH-COSY experiment to rapidly collect the data and provide significant dispersion in the spectral region containing (13)C-(1)H cross peaks of CH(3) groups belonging to Ala, Ile, Leu, Met, Thr and Val residues. This enables one to carry out chemical shift based editing and grouping of all the (13)C-(1)H cross peaks of CH(3) groups belonging to Ala, Ile, Leu, Met, Thr and Val residues in fractionally (10%) (13)C-labelled proteins, which in turn aids in the sequence-specific resonance assignments in general and side-chain resonance assignments in particular, in any given protein. Further, we demonstrate the utility of this experiment for stereospecific assignments of the pro-R and pro-S methyl groups belonging to the Leu and Val residues in fractionally (10%) (13)C-labelled proteins. The proposed experiment opens up a wide range of applications in resonance assignment strategies and structure determination of proteins.     

Heteronuclear three-dimensional NMR spectroscopy of a partially denatured protein: The A-state of human ubiquitin

Summary Human ubiquitin is a 76-residue protein that serves as a protein degradation signal when conjugated to another protein. Ubiquitin has been shown to exist in at least three states: native (N-state), unfolded (U-state), and, when dissolved in 60% methanol:40% water at pH 2.0, partially folded (A-state). If the A-state represents an intermediate in the folding pathway of ubiquitin, comparison of the known structure of the N-state with that of the A-state may lead to an understanding of the folding pathway. Insights into the structural basis for ubiquitin's role in protein degradation may also be obtained. To this end we determined the secondary structure of the A-state using heteronuclear three-dimensional NMR spectroscopy of uniformly ¹⁵N-enriched ubiquitin. Sequence-specific ¹H and ¹⁵N resonance assignments were made for more than 90% of the residues in the A-state. The assignments were made by concerted analysis of three-dimensional ¹H-¹⁵N NOESY-HMQC and TOCSY-HMQC data sets. Because of ¹H chemical shift degeneracies, the increased resolution provided by the ¹⁵N dimension was critical. Analysis of short- and long-range NOEs indicated that only the first two strands of -sheet, comprising residues 2–17, remain in the A-state, compared to five strands in the N-state. NOEs indicative of an -helix, comprising residues 25–33, were also identified. These residues were also helical in the N-state. In the N-state, residues in this helix were in contact with residues from the first two strands of -sheet. It is likely, therefore, that residues 1–33 comprise a folded domain in the A-state of ubiquitin. On the basis of ¹H chemical shifts and weak short-range NOEs, residues 34–76 do not adopt a rigid secondary structure but favor a helical conformation. This observation may be related to the helix-inducing effects of the methanol present. The secondary structure presented here differs from and is more thorough than that determined previously by two-dimensional ¹H methods [Harding et al. (1991) Biochemistry, 30, 3120–3128].     

Phase labeling of C−H and C−C spin-system topologies: Application in constant-time PFG-CBCA(CO)NH experiments for discriminating amino acid spin-system types

Summary Triple-resonance experiments facilitate the determination of sequence-specific resonance assignments of medium-sized ¹³C, ¹⁵N-enriched proteins. Some triple-resonance experiments can also be used to obtain information about amino acid spin-system topologies by proper delay tuning. The constant-time PFG-CBCA(CO)NH experiment allows discrimination between five different groups of amino acids by tuning (phase labeling) independently the delays for proton-carbon refocusing and carbon-carbon constant-time frequency labeling. The proton-carbon refocusing delay allows discrimination of spin-system topologies based on the number of protons attached to C and C atoms (i.e. C-H phase labeling). In addition, tuning of the carbon-carbon constant-time frequency-labeling delay discriminates topologies based on the number of carbons directly coupled to C and C atoms (i.e. C-C phase labeling). Classifying the spin systems into these five groups facilitates identification of amino acid types, making both manual and automated analysis of assignments easier. The use of this pair of optimally tuned PFG-CBCA(CO)NH experiments for distinguishing five spin-system topologies is demonstrated for the 124-residue bovine pancreatic ribonuclease A protein.     

Classifier ensembles for protein structural class prediction with varying homology

Structural class characterizes the overall folding type of a protein or its domain. A number of computational methods have been proposed to predict structural class based on primary sequences; however, the accuracy of these methods is strongly affected by sequence homology. This paper proposes, an ensemble classification method and a compact feature-based sequence representation. This method improves prediction accuracy for the four main structural classes compared to competing methods, and provides highly accurate predictions for sequences of widely varying homologies. The experimental evaluation of the proposed method shows superior results across sequences that are characterized by entire homology spectrum, ranging from 25% to 90% homology. The error rates were reduced by over 20% when compared with using individual prediction methods and most commonly used composition vector representation of protein sequences. Comparisons with competing methods on three large benchmark datasets consistently show the superiority of the proposed method.     

Integrating protein structural dynamics and evolutionary analysis with Bio3D

Background

Popular bioinformatics approaches for studying protein functional dynamics include comparisons of crystallographic structures, molecular dynamics simulations and normal mode analysis. However, determining how observed displacements and predicted motions from these traditionally separate analyses relate to each other, as well as to the evolution of sequence, structure and function within large protein families, remains a considerable challenge. This is in part due to the general lack of tools that integrate information of molecular structure, dynamics and evolution.

Results

Here, we describe the integration of new methodologies for evolutionary sequence, structure and simulation analysis into the Bio3D package. This major update includes unique high-throughput normal mode analysis for examining and contrasting the dynamics of related proteins with non-identical sequences and structures, as well as new methods for quantifying dynamical couplings and their residue-wise dissection from correlation network analysis. These new methodologies are integrated with major biomolecular databases as well as established methods for evolutionary sequence and comparative structural analysis. New functionality for directly comparing results derived from normal modes, molecular dynamics and principal component analysis of heterogeneous experimental structure distributions is also included. We demonstrate these integrated capabilities with example applications to dihydrofolate reductase and heterotrimeric G-protein families along with a discussion of the mechanistic insight provided in each case.

Conclusions

The integration of structural dynamics and evolutionary analysis in Bio3D enables researchers to go beyond a prediction of single protein dynamics to investigate dynamical features across large protein families. The Bio3D package is distributed with full source code and extensive documentation as a platform independent R package under a GPL2 license from http://thegrantlab.org/bio3d/.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0399-6) contains supplementary material, which is available to authorized users.     

Towards miniaturization of a structural genomics pipeline using micro-expression and microcoil NMR

In structural genomics centers, nuclear magnetic resonance (NMR) screening is in increasing use as a tool to identify folded proteins that are promising targets for three-dimensional structure determination by X-ray crystallography or NMR spectroscopy. The use of 1D ¹H NMR spectra or 2D [¹H,¹⁵N]-correlation spectroscopy (COSY) typically requires milligram quantities of unlabeled or isotope-labeled protein, respectively. Here, we outline ways towards miniaturization of a structural genomics pipeline with NMR screening for folded globular proteins, using a high-density micro-fermentation device and a microcoil NMR probe. The proteins are micro-expressed in unlabeled or isotope-labeled media, purified, and then subjected to 1D ¹H NMR and/or 2D [¹H,¹⁵N]-COSY screening. To demonstrate that the miniaturization is functioning effectively, we processed nine mouse homologue protein targets and compared the results with those from the “macro-scale” Joint Center of Structural Genomics (JCSG) high-throughput pipeline. The results from the two pipelines were comparable, illustrating that the data were not compromised in the miniaturized approach.     

Secondary structural effects on protein NMR chemical shifts

For an amino acid in protein, its chemical shift, (, )_s, is expressed as a function of its backbone torsion angles ( and ) and secondary state (s): (, )_{s=, )_coil+(, )_s}, where (, )_coil represents its chemical shift at coil state (s=coil); (, )_s (s=sheet or helix) is herein defined as secondary structural effect correction factor, which are quantitatively determined from Residue-specific Secondary Structure Shielding Surface (RSS) for ¹³CO, ¹³C, ¹³C,¹H, ¹⁵N, and ¹HN nuclei. The secondary structural effect correction factors defined in this study differ from those in earlier investigations by separating out the backbone conformational effects. As a consequence, their magnitudes are significantly smaller than those earlier reported. The present (, )_sheet and (, )_helix were found varying little with backbone conformation and the 20 amino acids, specifically for ¹³CO, ¹³C, and ¹H nuclei. This study also carries out some useful investigations on other chemical shift prediction approaches – the traditional shielding surfaces, SHIFTS, SHIFTX, PROSHIFT, and identifies some unexpected shortcomings with these methods. It provides some useful insights into understanding protein chemical shifts and suggests a new route to improving chemical shifts prediction. The RSS surfaces were incorporated into the program PRSI [Wang and Jardetzky, J. Biomol. NMR, 28: 327–340 (2004)], which is available for academic users at http://www.pronmr.com or by sending email to the author (yunjunwang@yahoo.com).     

Unique opportunities for NMR methods in structural genomics

This Perspective, arising from a workshop held in July 2008 in Buffalo NY, provides an overview of the role NMR has played in the United States Protein Structure Initiative (PSI), and a vision of how NMR will contribute to the forthcoming PSI-Biology program. NMR has contributed in key ways to structure production by the PSI, and new methods have been developed which are impacting the broader protein NMR community.