Yuanpeng J. Huang

Protein NMR spectroscopy in structural genomics.

Protein NMR spectroscopy provides an important complement to X-ray crystallography for structural genomics, both for determining three-dimensional protein structures and in characterizing their biochemical and biophysical functions.

Structural biology: proteins flex to function.

Static pictures of protein structures are so prevalent that it is easy to forget they are dynamic molecular machines. Characterizing their intrinsic motions may be necessary to understand how they work.Split personalityHeres a new way to look at familiar enzymes. A new technology that can detect ultra-rare states of a protein (cyclophilin A in this instance) shows that rather than having a range of conformations to which it resorts during catalysis, it has them all before it starts. Protein motions needed for catalysis are intrinsic to the enzyme and take in the whole molecule, not just the traditional centre of attention, the active site.

Assessment of template‐based protein structure predictions in CASP10

Template‐based modeling (TBM) is a major component of the critical assessment of protein structure prediction (CASP). In CASP10, some 41,740 predicted models submitted by 150 predictor groups were assessed as TBM predictions. The accuracy of protein structure prediction was assessed by geometric comparison with experimental X‐ray crystal and NMR structures using a composite score that included both global alignment metrics and distance‐matrix–based metrics. These included GDT‐HA and GDC‐all global alignment scores, and the superimposition‐independent LDDT distance‐matrix–based score. In addition, a superimposition‐independent RPF metric, similar to that described previously for comparing protein models against experimental NMR data, was used for comparing predicted protein structure models against experimental protein structures. To score well on all four of these metrics, models must feature accurate predictions of both backbone and side‐chain conformations. Performance rankings were determined independently for server and the combined server plus human‐curated predictor groups. Final rankings were made using paired head‐to‐head Students t‐test analysis of raw metric scores among the top 25 performing groups in each category. Proteins 2014; 82(Suppl 2):43–56.

Solution NMR structure of the NlpC/P60 domain of lipoprotein Spr from Escherichia coli: structural evidence for a novel cysteine peptidase catalytic triad.

Escherichia coli Spr is a membrane-anchored cell wall hydrolase. The solution NMR structure of the C-terminal NlpC/P60 domain of E. coli Spr described here reveals that the protein adopts a papain-like alpha+beta fold and identifies a substrate-binding cleft featuring several highly conserved residues. The active site features a novel Cys-His-His catalytic triad that appears to be a unique structural signature of this cysteine peptidase family. Moreover, the relative orientation of these catalytic residues is similar to that observed in the analogous Ser-His-His triad, a variant of the classic Ser-His-Asp charge relay system, suggesting the convergent evolution of a catalytic mechanism in quite distinct peptidase families.

CASD-NMR: Critical Assessment of Automated Structure Determination by NMR

We report the completion of the first comparison of automated NMR protein structure calculation methods and announce its continuation in the form of an ongoing, community-wide experiment: CASD-NMR (Critical Assessment of Automated Structure Determination of Proteins by NMR). CASD-NMR is open for any laboratory to participate and/or to submit targets. NMR spectroscopy is the only technique for the determination of the solution structure of biological macromolecules. This typically requires both the assignment of resonances and a labor-intensive analysis of multidimensional NOESY spectra, where peaks are matched to assigned resonances. Software tools for the full automation of the NOESY assignment and the structure calculation steps have the potential to boost the efficiency, reproducibility and reliability of NMR structures. Within the e-NMR project (www.e-nmr.eu), which is funded by the European Commission (Project number 213010), we are developing an approach to assess whether such automated methods can indeed produce structures that closely match those manually refined using the same experimental data (the “reference structures”). The concept closely resembles that of other community-wide experiments, such as CASP, the Critical Assessment of Techniques for Protein Structure Prediction1, and CAPRI, the Critical Assessment of Prediction of Interactions2. At variance with both CASP and CAPRI, CASD-NMR is entirely based on experimental data, presenting special issues in assembling, organizing, and distributing these data among participants. We provided seven research teams in the field with ten experimental data sets for various protein systems of known structure and two sets for protein structures not yet publicly available (“blind tests”), courtesy of the NorthEast Structural Genomics consortium (NESG). We then met in Florence, Italy on May 4–6, 2009 to analyze the structures generated (Fig. 1), by comparison to the reference structures and by using software tools for structure validation. This first experiment indicated that while most submissions had correct overall folds, on certain targets some programs failed to calculate accurate packing and length of secondary structure elements. The root mean square deviations (RMSDs) of the backbone coordinates from the manually-solved structures were typically in the 1–2 A range, but reached values as high as 9 A in some cases. Figure 1 Performance of various automated structure calculation methods

Automated protein fold determination using a minimal NMR constraint strategy

Determination of precise and accurate protein structures by NMR generally requires weeks or even months to acquire and interpret all the necessary NMR data. However, even medium‐accuracy fold information can often provide key clues about protein evolution and biochemical function(s). In this article we describe a largely automatic strategy for rapid determination of medium‐accuracy protein backbone structures. Our strategy derives from ideas originally introduced by other groups for determining medium‐accuracy NMR structures of large proteins using deuterated, 13C‐, 15N‐enriched protein samples with selective protonation of side‐chain methyl groups (13CH3). Data collection includes acquiring NMR spectra for automatically determining assignments of backbone and side‐chain 15N, HN resonances, and side‐chain 13CH3 methyl resonances. These assignments are determined automatically by the program AutoAssign using backbone triple resonance NMR data, together with Spin System Type Assignment Constraints (STACs) derived from side‐chain triple‐resonance experiments. The program AutoStructure then derives conformational constraints using these chemical shifts, amide 1H/2H exchange, nuclear Overhauser effect spectroscopy (NOESY), and residual dipolar coupling data. The total time required for collecting such NMR data can potentially be as short as a few days. Here we demonstrate an integrated set of NMR software which can process these NMR spectra, carry out resonance assignments, interpret NOESY data, and generate medium‐accuracy structures within a few days. The feasibility of this combined data collection and analysis strategy starting from raw NMR time domain data was illustrated by automatic analysis of a medium accuracy structure of the Z domain of Staphylococcal protein A.

Assessing precision and accuracy of protein structures derived from NMR data

One of the most challenging problems facing the field of biomolecular NMR spectroscopy is the lack of generally accepted, uniform criteria for defining the precision and accuracy of structures derived from NMR data. Although widely cited, metrics such as residual constraint violations, constraints per residue, and convergence across an ensemble of conformers [root-mean-square deviations (RMSDs)] provide necessary, but not sufficient, criteria for defining a good-quality solution NMR structure. Most importantly, none of these measures have standard conventions by which they are computed; each measure is assessed somewhat differently in different laboratories, using subjective criteria which may not be possible to reproduce in another laboratory. Owing to the lack of widely accepted algorithms and conventions for making these assessments, the same structure analyzed by different groups will often yield different structure quality assessment statistics. Two articles in this issue of Proteins demonstrate the pressing need for establishing community-wide standards for defining the accuracy and precision of NMR-derived protein structures. In one article, Snyder and Montelione present a method for determining internally well-defined “core atom set(s)” based on distance variance matrices, and for calculating a “joint RMSD” quantifying the precision of an ensemble of NMR-derived structures. In the other article, Nederveen et al. recalculate over 500 NMR-derived structures from archived constraint files, and demonstrate the value of standardized methods of structure calculation and assessment. They show that not only can improved methods of structure calculation provide more accurate results, but also that the original published structures often are reported with an inappropriately high estimation of precision. Both of these articles address key aspects of the challenge for assessing the precision and accuracy of protein structures derived from NMR data. This editorial addresses the general issues of estimating precision and accuracy of protein NMR structures, and presents recent progress in the field, with the aim of stimulating discussion, and eventually resolution, of these challenges by the scientific community.

Accurate automated protein NMR structure determination using unassigned NOESY data.

Conventional NMR structure determination requires nearly complete assignment of the cross peaks of a refined NOESY peak list. Depending on the size of the protein and quality of the spectral data, this can be a time-consuming manual process requiring several rounds of peak list refinement and structure determination. Programs such as Aria, CYANA, and AutoStructure can generate models using unassigned NOESY data but are very sensitive to the quality of the input peak lists and can converge to inaccurate structures if the signal-to-noise of the peak lists is low. Here, we show that models with high accuracy and reliability can be produced by combining the strengths of the high-resolution structure prediction program Rosetta with global measures of the agreement between structure models and experimental data. A first round of models generated using CS-Rosetta (Rosetta supplemented with backbone chemical shift information) are filtered on the basis of their goodness-of-fit with unassigned NOESY peak lists using the DP-score, and the best fitting models are subjected to high resolution refinement with the Rosetta rebuild-and-refine protocol. This hybrid approach uses both local backbone chemical shift and the unassigned NOESY data to direct Rosetta trajectories toward the native structure and produces more accurate models than AutoStructure/CYANA or CS-Rosetta alone, particularly when using raw unedited NOESY peak lists. We also show that when accurate manually refined NOESY peak lists are available, Rosetta refinement can consistently increase the accuracy of models generated using CYANA and AutoStructure.

Construct optimization for protein NMR structure analysis using amide hydrogen/deuterium exchange mass spectrometry

Disordered or unstructured regions of proteins, while often very important biologically, can pose significant challenges for resonance assignment and three‐dimensional structure determination of the ordered regions of proteins by NMR methods. In this article, we demonstrate the application of 1H/2H exchange mass spectrometry (DXMS) for the rapid identification of disordered segments of proteins and design of protein constructs that are more suitable for structural analysis by NMR. In this benchmark study, DXMS is applied to five NMR protein targets chosen from the Northeast Structural Genomics project. These data were then used to design optimized constructs for three partially disordered proteins. Truncated proteins obtained by deletion of disordered N‐ and C‐terminal tails were evaluated using 1H‐15N HSQC and 1H‐15N heteronuclear NOE NMR experiments to assess their structural integrity. These constructs provide significantly improved NMR spectra, with minimal structural perturbations to the ordered regions of the protein structure. As a representative example, we compare the solution structures of the full length and DXMS‐based truncated construct for a 77‐residue partially disordered DUF896 family protein YnzC from Bacillus subtilis, where deletion of the disordered residues (ca. 40% of the protein) does not affect the native structure. In addition, we demonstrate that throughput of the DXMS process can be increased by analyzing mixtures of up to four proteins without reducing the sequence coverage for each protein. Our results demonstrate that DXMS can serve as a central component of a process for optimizing protein constructs for NMR structure determination. Proteins 2009.

The structure of vimentin linker 1 and rod 1B domains characterized by site-directed spin-labeling electron paramagnetic resonance (SDSL-EPR) and X-ray crystallography.

Background: The complete structure is not known for any intermediate filament (IF) protein. Results: Linker 1 and rod 1B in human vimentin were characterized using electron paramagnetic resonance spectroscopy and x-ray crystallography. Conclusion: The rod 1B adopts two functional conformations that mediate formation of an anti-parallel “A11” tetramer. Significance: Understanding vimentin structure provides insight into all IFs and the related human pathologies. Despite the passage of ∼30 years since the complete primary sequence of the intermediate filament (IF) protein vimentin was reported, the structure remains unknown for both an individual protomer and the assembled filament. In this report, we present data describing the structure of vimentin linker 1 (L1) and rod 1B. Electron paramagnetic resonance spectra collected from samples bearing site-directed spin labels demonstrate that L1 is not a flexible segment between coiled-coils (CCs) but instead forms a rigid, tightly packed structure. An x-ray crystal structure of a construct containing L1 and rod 1B shows that it forms a tetramer comprising two equivalent parallel CC dimers that interact with one another in the form of a symmetrical anti-parallel dimer. Remarkably, the parallel CC dimers are themselves asymmetrical, which enables them to tetramerize rather than undergoing higher order oligomerization. This functionally vital asymmetry in the CC structure, encoded in the primary sequence of rod 1B, provides a striking example of evolutionary exploitation of the structural plasticity of proteins. EPR and crystallographic data consistently suggest that a very short region within L1 represents a minor local distortion in what is likely to be a continuous CC from the end of rod 1A through the entirety of rod 1B. The concordance of this structural model with previously published cross-linking and spectral data supports the conclusion that the crystallographic oligomer represents a native biological structure.