Resonance assignment strategies for the analysis of nmr spectra of proteins

Determination of the high resolution solution structure of a protein using nuclear magnetic resonance (NMR) spectroscopy requires that resonances observed in the NMR spectra be unequivocally assigned to individual nuclei of the protein. With the advent of modern, two-dimensional NMR techniques arose methodologies for assigning the¹H resonances based on 2D, homonuclear¹H NMR experiments. These include the sequential assignment strategy and the main chain directed strategy. These basic strategies have been extended to include newer 3D homonuclear experiments and 2D and 3D heteronuclear resolved and edited methods. Most recently a novel, conceptually new approach to the problem has been introduced that relies on heteronuclear, multidimensional so-called triple resonance experiments for both backbone and sidechain resonance assignments in proteins. This article reviews the evolution of strategies for the assignment of resonances of proteins.     

Fast Assignment of <Superscript>15</Superscript>N-HSQC Peaks using High-Resolution 3D HNcocaNH Experiments with Non-Uniform Sampling

We describe an efficient NMR triple resonance approach for fast assignment of backbone amide resonance peaks in the ¹⁵N-HSQC spectrum. The exceptionally high resolutions achieved in the 3D HncocaNH and hNcocaNH experiments together with non-uniform sampling facilitate error-free sequential connection of backbone amides. Data required for the complete backbone amide assignment of the 56-residue protein GB1 domain were obtained in 14 h. Data analysis was vastly streamlined using a ‘backbone NH walk’ method to determine sequential connectivities without the need for ¹³C chemical shifts comparison. Amino acid residues in the sequentially connected NH chains are classified into two groups by a simple variation of the NMR pulse sequence, and the resulting ‘ZeBra’ stripe patterns are useful for mapping these chains to the protein sequence. In addition to resolving ambiguous assignments derived from conventional backbone experiments, this approach can be employed to rapidly assign small proteins or flexible regions in larger proteins, and to transfer assignments to mutant proteins or proteins in different ligand-binding states.     

Use of biosynthetic fractional 13C-labeling for backbone NMR assignment of proteins

We describe a simple approach to classify amino acid residue types in NMR spectra of proteins for supporting the backbone resonance assignments. It makes use of the differences in biosynthetic pathways of the 20 amino acids in Escherichia coli. Therefore, it is distinct from the parameters routinely exploited in the backbone resonance assignment such as chemical shifts and spin topology information. The combination of biosynthetically directed fractional 13C-labeling and uniform 15N-labeling enables us to obtain both residue-type specific information and sequential connectivities from a single protein sample. The residue-type classification exploiting biosynthetic pathways can be used for accelerating the conventional backbone assignment procedure.     

Backbone assignment of proteins with known structure using residual dipolar couplings

A prerequisite for NMR studies of protein-ligand interactions or protein dynamics is the assignment of backbone resonances. Here we demonstrate that protein assignment can significantly be enhanced when experimental dipolar couplings (RDCs) are matched to values back-calculated from a known three-dimensional structure. In case of small proteins, the program MARS allows assignment of more than 90% of backbone resonances without the need for sequential connectivity information. For bigger proteins, we show that the combination of sequential connectivity information with RDC-matching enables more residues to be assigned reliably and backbone assignment to be more robust against missing data. Structural or dynamic deviations from the employed 3D coordinates do not lead to an increased error rate in RDC-supported assignment. RDC-enhanced assignment is particularly useful when chemical shifts and sequential connectivity only provide a few reliable assignments.     

Automatic assignment of protein backbone resonances by direct spectrum inspection in targeted acquisition of NMR data

The necessity to acquire large multidimensional datasets, a basis for assignment of NMR resonances, results in long data acquisition times during which substantial degradation of a protein sample might occur. Here we propose a method applicable for such a protein for automatic assignment of backbone resonances by direct inspection of multidimensional NMR spectra. In order to establish an optimal balance between completeness of resonance assignment and losses of cross-peaks due to dynamic processes/degradation of protein, assignment of backbone resonances is set as a stirring criterion for dynamically controlled targeted nonlinear NMR data acquisition. The result is demonstrated with the 12 kDa ¹³C,¹⁵ N-labeled apo-form of heme chaperone protein CcmE, where hydrolytic cleavage of 29 C-terminal amino acids is detected. For this protein, 90 and 98% of manually assignable resonances are automatically assigned within 10 and 40 h of nonlinear sampling of five 3D NMR spectra, respectively, instead of 600 h needed to complete the full time domain grid. In addition, resonances stemming from degradation products are identified. This study indicates that automatic resonance assignment might serve as a guiding criterion for optimal run-time allocation of NMR resources in applications to proteins prone to degradation. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Automated backbone assignment of labeled proteins using the threshold accepting algorithm

The sequential assignment of backbone resonances is the first step in the structure determination of proteins by heteronuclear NMR. For larger proteins, an assignment strategy based on proton side-chain information is no longer suitable for the use in an automated procedure. Our program PASTA (Protein ASsignment by Threshold Accepting) is therefore designed to partially or fully automate the sequential assignment of proteins, based on the analysis of NMR backbone resonances plus C information. In order to overcome the problems caused by peak overlap and missing signals in an automated assignment process, PASTA uses threshold accepting, a combinatorial optimization strategy, which is superior to simulated annealing due to generally faster convergence and better solutions. The reliability of this algorithm is shown by reproducing the complete sequential backbone assignment of several proteins from published NMR data. The robustness of the algorithm against misassigned signals, noise, spectral overlap and missing peaks is shown by repeating the assignment with reduced sequential information and increased chemical shift tolerances. The performance of the program on real data is finally demonstrated with automatically picked peak lists of human nonpancreatic synovial phospholipase A₂, a protein with 124 residues.     

Assignments of backbone 1H, 13C, and 15N resonances and secondary structure of ribonuclease H from Escherichia coli by heteronuclear three-dimensional NMR spectroscopy.

The assignments of individual magnetic resonances of backbone nuclei of a larger protein, ribonuclease H from Escherichia coli, which consists of 155 amino acid residues and has a molecular mass of 17.6 kDa are presented. To remove the problem of degenerate chemical shifts, which is inevitable in proteins of this size, three-dimensional NMR was applied. The strategy for the sequential assignment was, first, resonance peaks of amides were classified into 15 amino acid types by 1H-15N HMQC experiments with samples in which specific amino acids were labeled with 15N. Second, the amide 1H-15N peaks were connected along the amino acid sequence by tracing intraresidue and sequential NOE cross peaks. In order to obtain unambiguous NOE connectivities, four types of heteronuclear 3D NMR techniques, 1H-15N-1H 3D NOESY-HMQC, 1H-15N-1H 3D TOCSY-HMQC, 13C-1H-1H 3D HMQC-NOESY, and 13C-1H-1H 3D HMQC-TOCSY, were applied to proteins uniformly labeled either with 15N or with 13C. This method gave a systematic way to assign backbone nuclei (N, NH, C alpha H, and C alpha) of larger proteins. Results of the sequential assignments and identification of secondary structure elements that were revealed by NOE cross peaks among backbone protons are reported.     

Automated amino acid side-chain NMR assignment of proteins using <Superscript>13</Superscript>C- and <Superscript>15</Superscript>N-resolved 3D [<Superscript>1</Superscript>H,<Superscript>1</Superscript>H]-NOESY

ASCAN is a new algorithm for automatic sequence-specific NMR assignment of amino acid side-chains in proteins, which uses as input the primary structure of the protein, chemical shift lists of (1)H(N), (15)N, (13)C(alpha), (13)C(beta) and possibly (1)H(alpha) from the previous polypeptide backbone assignment, and one or several 3D (13)C- or (15)N-resolved [(1)H,(1)H]-NOESY spectra. ASCAN has also been laid out for the use of TOCSY-type data sets as supplementary input. The program assigns new resonances based on comparison of the NMR signals expected from the chemical structure with the experimentally observed NOESY peak patterns. The core parts of the algorithm are a procedure for generating expected peak positions, which is based on variable combinations of assigned and unassigned resonances that arise for the different amino acid types during the assignment procedure, and a corresponding set of acceptance criteria for assignments based on the NMR experiments used. Expected patterns of NOESY cross peaks involving unassigned resonances are generated using the list of previously assigned resonances, and tentative chemical shift values for the unassigned signals taken from the BMRB statistics for globular proteins. Use of this approach with the 101-amino acid residue protein FimD(25-125) resulted in 84% of the hydrogen atoms and their covalently bound heavy atoms being assigned with a correctness rate of 90%. Use of these side-chain assignments as input for automated NOE assignment and structure calculation with the ATNOS/CANDID/DYANA program suite yielded structure bundles of comparable quality, in terms of precision and accuracy of the atomic coordinates, as those of a reference structure determined with interactive assignment procedures. A rationale for the high quality of the ASCAN-based structure determination results from an analysis of the distribution of the assigned side chains, which revealed near-complete assignments in the core of the protein, with most of the incompletely assigned residues located at or near the protein surface.     

Automated Resonance Assignment of Proteins: 6 DAPSY-NMR

The 6-dimensional (6D) APSY-seq-HNCOCANH NMR experiment correlates two sequentially neighboring amide moieties in proteins via the C′ and C^α nuclei, with efficient suppression of the back transfer from C^α to the originating amide moiety. The automatic analysis of two-dimensional (2D) projections of this 6D experiment with the use of GAPRO (Hiller et al., 2005) provides a high-precision 6D peak list, which permits automated sequential assignments of proteins with the assignment software GARANT (Bartels et al., 1997). The procedure was applied to two proteins, the 63-residue 434-repressor(1–63) and the 115-residue TM1290. For both proteins, complete sequential assignments for all NMR-observable backbone resonances were obtained, and the polypeptide segments thus identified could be unambiguously located in the amino acid sequence. These results demonstrate that APSY-NMR spectroscopy in combination with a suitable assignment algorithm can provide fully automated sequence-specific backbone assignments of small proteins.Francesco Fiorito and Sebastian Hiller - Both authors contributed equally to this work     

Assignment of protein NMR spectra based on projections,multi-way decomposition and a fast correlation approach

We present an approach for the assignment of protein NMR resonances that combines established and new concepts: (a) Based on published reduced dimensionality methods, two 5-dimensional experiments are proposed. (b) Multi-way decomposition (PRODECOMP) applied simultaneously to all acquired NMR spectra provides the assignment of resonance frequencies under conditions of very low signal-to-noise. (c) Each resulting component characterizes all spin (1/2) nuclei in a (doubly-labeled) CbetaH(n)-CalphaH-C'-NH-CalphaH-CbetaH(n) fragment in an unambiguous manner, such that sequentially neighboring components have about four atoms in common. (d) A new routine (SHABBA) determines correlations for all component pairs based on the common nuclei; high correlation values yield sequential chains of a dozen or more components. (e) The potentially error-prone peak picking is delayed to the last step, where it helps to place the component chains within the protein sequence, and thus to achieve the final backbone assignment. The approach was validated by achieving complete backbone resonance assignments for ubiquitin.     

Computer assignment of the backbone resonances of labelled proteins using two-dimensional correlation experiments

Summary We present ALPS (Assignment for Labelled Protein Spectra), a flexible computer program for the automatic assignment of backbone NMR resonances of ¹⁵N/¹³C-labelled proteins. The program constructs pseudoresidues from peak-picking lists of a set of two-dimensional triple resonance experiments and uses either a systematic search or a simulated annealing-based optimization to perform the assignment. This method has been successfully tested on two-dimensional triple resonance spectra of Rhodobacter capsulatus ferrocytochrome c ₂ (116 amino acids).     

Efficient side-chain and backbone assignment in large proteins: Application to tGCN5

In determining the structure of large proteins by NMR, it would be desirable to obtain complete backbone, side-chain, and NOE assignments efficiently, with a minimum number of experiments and samples. Although new strategies have made backbone assignment highly efficient, side-chain assignment has remained more difficult. Faced with the task of assigning side-chains in a protein with poor relaxation properties, the Tetrahymena histone acetyltransferase tGCN5, we have developed an assignment strategy that would provide complete side-chain assignments in cases where fast ¹³C transverse relaxation causes HCCH-TOCSY experiments to fail. Using the strategy presented here, the majority of aliphatic side-chain proton and carbon resonances can be efficiently obtained using optimized H(CC-CO)NH-TOCSY and (H)C(C-CO)NH-TOCSY experiments on a partially deuterated protein sample. Assignments can be completed readily using additional information from a ¹³ C-dispersed NOESY-HSQC spectrum. Combination of these experiments with H(CC)NH-TOCSY and (H)C(C)NH-TOCSY may provide complete backbone and side-chain assignments for large proteins using only one or two samples.     

Sequential assignment of 1H, 13C and 15N resonances of human carbonic anhydrase I by triple-resonance NMR techniques and extensive amino acid-specific 15N-labeling

Summary The backbone NMR resonances of human carbonic anhydase I (HCA I) have been assigned. This protein is one of the largest monomeric proteins assigned so far. The assignment was enabled by a combination of 3D triple-resonance experiments and extensive use of amino acid-specific ¹⁵N-labeling. The obtained resonance assignment has been used to evaluate the secondary structure elements present in solution. The solution structure appears to be very similar to the crystal structure, although some differences can be observed. Proton-deuteron exchange experiments have shown that the assignments provide probes that can be used in future folding studies of HCA I.The chemical shift data have been deposited in the BioMagResBank in Madison, WI, U.S.A.     

Specific assignment of resonances in the 1H nuclear magnetic resonance spectrum of the polypeptide cardiac stimulant anthopleurin-A

The specific assignment of resonances in the 300-MHz 1H nuclear magnetic resonance (NMR) spectrum of anthopleurin-A, a polypeptide cardiac stimulant from the sea anemone Anthopleura xanthogrammica, is described. Assignments have been made using two-dimensional NMR techniques, in particular the method of sequential assignments, where through-bond and through-space connectivities to the peptide backbone NH resonances are used to identify the spin systems of residues adjacent in the amino acid sequence. Complete assignments have been made of the resonances from 33 residues out of a total of 49, and partial assignments of a further 3. The resonances from several of the remaining residues have been identified but not yet specifically assigned. A complicating factor in making these assignments is the conformational heterogeneity exhibited by anthopleurin-A in solution. The resonances from a number of amino acid residues in the minor conformer have also been assigned. These assignments contribute towards identification of the origin of this heterogeneity, and permit some preliminary conclusions to be drawn regarding the secondary structure of the polypeptide.     

PASA – A Program for Automated Protein NMR Backbone Signal Assignment by Pattern-Filtering Approach

We present a new program, PASA (Program for Automated Sequential Assignment), for assigning protein backbone resonances based on multidimensional heteronuclear NMR data. Distinct from existing programs, PASA emphasizes a per-residue-based pattern-filtering approach during the initial stage of the automated ¹³C^α and/or ¹³C^β chemical shift matching. The pattern filter employs one or multiple constraints such as ¹³C^α/C^β chemical shift ranges for different amino acid types and side-chain spin systems, which helps to rule out, in a stepwise fashion, improbable assignments as resulted from resonance degeneracy or missing signals. Such stepwise filtering approach substantially minimizes early false linkage problems that often propagate, amplify, and ultimately cause complication or combinatorial explosion of the automation process. Our program (http://www.lerner.ccf.org/moleccard/qin/) was tested on four representative small-large sized proteins with various degrees of resonance degeneracy and missing signals, and we show that PASA achieved the assignments efficiently and rapidly that are fully consistent with those obtained by laborious manual protocols. The results demonstrate that PASA may be a valuable tool for NMR-based structural analyses, genomics, and proteomics. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

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, (13)C-, (15)N-enriched protein samples with selective protonation of side-chain methyl groups ((13)CH(3)). Data collection includes acquiring NMR spectra for automatically determining assignments of backbone and side-chain (15)N, H(N) resonances, and side-chain (13)CH(3) 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 (1)H/(2)H 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.     

Automated assignment of NMR chemical shifts using peak-particle dynamics simulation with the DYNASSIGN algorithm

A new algorithm, DYNASSIGN, for the automated assignment of NMR chemical shift resonances was developed in which expected cross peaks in multidimensional NMR spectra are represented by peak-particles and assignment restraints are translated into a potential energy function. Molecular dynamics simulation techniques are used to calculate a trajectory of the system of peak-particles subjected to the potential function in order to find energetically optimal configurations that correspond to correct assignments. Peak-particle dynamics-based simulated annealing was combined with the Hungarian algorithm for local optimization, and a residue-based score was introduced to distinguish between reliable assignments and “unassigned” resonances for which no reliable assignment can be established. The DYNASSIGN algorithm was implemented in the program CYANA and tested with data sets obtained from the experimental NMR data of nine small proteins. With a set of 10 commonly used NMR spectra, on average 82.5% of all backbone and side-chain ¹H, ¹³C and ¹⁵N resonances could be assigned with an average error rate of 3.5%.     

Evaluation of an algorithm for the automated sequential assignment of protein backbone resonances: A demonstration of the connectivity tracing assignment tools (CONTRAST) software package

Summary The peptide sequential assignment algorithm presented here was implemented as a macro within the CONnectivity TRacing ASsignment Tools (CONTRAST) computer software package. The algorithm provides a semi- or fully automated global means of sequentially assigning the NMR backbone resonances of proteins. The program's performance is demonstrated here by its analysis of realistic computer-generated data for III^Glc, a 168-residue signal-transducing protein of Escherichia coli [Pelton et al. (1991) Biochemistry, 30, 10043–10057]. Missing experimental data (19 resonances) were generated so that a complete assignment set could be tested. The algorithm produces sequential assignments from appropriate peak lists of nD NMR data. It quantifies the ambiguity of each assignment and provides ranked alternatives. A best first approach, in which high-scoring local assignments are made before and in preference to lower scoring assignments, is shown to be superior (in terms of the current set of CONTRAST scoring routines) to approaches such as simulated annealing that seek to maximize the combined scores of the individual assignments. The robustness of the algorithm was tested by evaluating the effects of imposed frequency imprecision (scatter), added false signals (noise), missing peaks (incomplete data), and variation in userdefined tolerances on the performance of the algorithm.