CAMRA: Chemical shift based computer aided protein NMR assignments

A suite of programs called CAMRA (Computer Aided Magnetic Resonance Assignment) has been developed for computer assisted residue-specific assignments of proteins. CAMRA consists of three units: ORB, CAPTURE and PROCESS. ORB predicts NMR chemical shifts for unassigned proteins using a chemical shift database of previously assigned homologous proteins supplemented by a statistically derived chemical shift database in which the shifts are categorized according to their residue, atom and secondary structure type. CAPTURE generates a list of valid peaks from NMR spectra by filtering out noise peaks and other artifacts and then separating the derived peak list into distinct spin systems. PROCESS combines the chemical shift predictions from ORB with the spin systems identified by CAPTURE to obtain residue specific assignments. PROCESS ranks the top choices for an assignment along with scores and confidence values. In contrast to other auto-assignment programs, CAMRA does not use any connectivity information but instead is based solely on matching predicted shifts with observed spin systems. As such, CAMRA represents a new and unique approach for the assignment of protein NMR spectra. CAMRA will be particularly useful in conjunction with other assignment methods and under special circumstances, such as the assignment of flexible regions in proteins where sufficient NOE information is generally not available. CAMRA was tested on two medium-sized proteins belonging to the chemokine family. It was found to be effective in predicting the assignment providing a database of previously assigned proteins with at least 30% sequence identity is available. CAMRA is versatile and can be used to include and evaluate heteronuclear and three-dimensional experiments.     

Application of neural networks to automated assignment of NMR spectra of proteins

Summary Simulated neural networks are described which aid the assignment of protein NMR spectra. A network trained to recognize amino acid type from TOCSY data was trained on 148 assigned spin systems from E. coli acyl carrier proteins (ACPs) and tested on spin systems from spinach ACP, which has a 37% sequence homology with E. coli ACP and a similar secondary structure. The output unit corresponding to the correct amino acid is one of the four most activated units in 83% of the spin systems tested. The utility of this information is illustrated by a second network which uses a constraint satisfaction algorithm to find the best fit of the spin systems to the amino acid sequence. Application to a stretch of 20 amino acids in spinach ACP results in 75% correct sequential assignment. Since the output of the amino acid type identification network can be coupled with a variety of sequential assignment strategies, the approach offers substantial potential for expediting assignment of protein NMR spectra.     

Practical use of chemical shift databases for protein solid-state NMR: 2D chemical shift maps and amino-acid assignment with secondary-structure information

We introduce a Python-based program that utilizes the large database of ¹³C and ¹⁵N chemical shifts in the Biological Magnetic Resonance Bank to rapidly predict the amino acid type and secondary structure from correlated chemical shifts. The program, called PACSYlite Unified Query (PLUQ), is designed to help assign peaks obtained from 2D ¹³C–¹³C, ¹⁵N–¹³C, or 3D ¹⁵N–¹³C–¹³C magic-angle-spinning correlation spectra. We show secondary-structure specific 2D ¹³C–¹³C correlation maps of all twenty amino acids, constructed from a chemical shift database of 262,209 residues. The maps reveal interesting conformation-dependent chemical shift distributions and facilitate searching of correlation peaks during amino-acid type assignment. Based on these correlations, PLUQ outputs the most likely amino acid types and the associated secondary structures from inputs of experimental chemical shifts. We test the assignment accuracy using four high-quality protein structures. Based on only the Cα and Cβ chemical shifts, the highest-ranked PLUQ assignments were 40–60 % correct in both the amino-acid type and the secondary structure. For three input chemical shifts (CO–Cα–Cβ or N–Cα–Cβ), the first-ranked assignments were correct for 60 % of the residues, while within the top three predictions, the correct assignments were found for 80 % of the residues. PLUQ and the chemical shift maps are expected to be useful at the first stage of sequential assignment, for combination with automated sequential assignment programs, and for highly disordered proteins for which secondary structure analysis is the main goal of structure determination.     

CISA: combined NMR resonance connectivity information determination and sequential assignment

A nearly complete sequential resonance assignment is a key factor leading to successful protein structure determination via NMR spectroscopy. Assuming the availability of a set of NMR spectral peak lists, most of the existing assignment algorithms first use the differences between chemical shift values for common nuclei across multiple spectra to provide the evidence that some pairs of peaks should be assigned to sequentially adjacent amino acid residues in the target protein. They then use these connectivities as constraints to produce a sequential assignment. At various levels of success, these algorithms typically generate a large number of potential connectivity constraints, and it grows exponentially as the quality of spectral data decreases. A key observation used in our sequential assignment program, CISA, is that chemical shift residual signature information can be used to improve the connectivity determination, and thus to dramatically decrease the number of predicted connectivity constraints. Fewer connectivity constraints lead to less ambiguities in the sequential assignment. Extensive simulation studies on several large test datasets demonstrated that CISA is efficient and effective, compared to three most recently proposed sequential resonance assignment programs RANDOM, PACES, and MARS.     

Error tolerant NMR backbone resonance assignment and automated structure generation

Error tolerant backbone resonance assignment is the cornerstone of the NMR structure determination process. Although a variety of assignment approaches have been developed, none works sufficiently well on noisy fully automatically picked peaks to enable the subsequent automatic structure determination steps. We have designed an integer linear programming (ILP) based assignment system (IPASS) that has enabled fully automatic protein structure determination for four test proteins. IPASS employs probabilistic spin system typing based on chemical shifts and secondary structure predictions. Furthermore, IPASS extracts connectivity information from the inter-residue information and the (automatically picked) (15)N-edited NOESY peaks which are then used to fix reliable fragments. When applied to automatically picked peaks for real proteins, IPASS achieves an average precision and recall of 82% and 63%, respectively. In contrast, the next best method, MARS, achieves an average precision and recall of 77% and 36%, respectively. The assignments generated by IPASS are then fed into our protein structure calculation system, FALCON-NMR, to determine the 3D structures without human intervention. The final models have backbone RMSDs of 1.25?, 0.88?, 1.49?, and 0.67? to the reference native structures for proteins TM1112, CASKIN, VRAR, and HACS1, respectively. The web server is publicly available at http://monod.uwaterloo.ca/nmr/ipass.     

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.     

Identification and description of beta-structure in horse muscle acylphosphatase by nuclear magnetic resonance spectroscopy

Nuclear magnetic resonance spectra of acylphosphatase were searched for signs of beta-structure, i.e. characteristic nuclear Overhauser enhancement patterns displayed in the two-dimensional spectra, typical chemical shifts, coupling constants and slow 2H-H exchange. The results provided identification of the main-chain resonances of amino acid residues involved in the beta-structure. The full sequential assignment of this region was gained by identification of some amino acid spin systems and their alignment with the primary sequence. The assignment of the side-chains was virtually completed subsequently and a list produced of nuclear magnetic resonance (n.m.r.) constraints derived from the spectra. The beta-structure consists of a beta-sheet with four antiparallel chains, one attached parallel chain, three tight turns and a beta-bulge. The conformation of the beta-sheet was determined by distance geometry calculation using the n.m.r. constraints (174 intraresidual, 107 sequential and 226 long-range distances, 32 torsion angles, phi, and 28 hydrogen bonds) as input. Observation of some interactions between the sheet and previously identified alpha-helical regions made it possible to give an outline of the three-dimensional structure of the enzyme.     

Proton resonance assignments of horse ferrocytochrome c

Two-dimensional nuclear magnetic resonance (NMR) spectroscopy was used to assign the proton resonances of horse ferrocytochrome c. Assignments were based on the main chain directed (MCD) and sequential assignment procedures. The fundamental units of the MCD approach, the main-chain NH-C alpha H-C beta H J-coupled subspin systems of each amino acid residue (NAB sets), were defined by analysis of direct and relayed coherence transfer spectra. Recognition of main-chain NOE connectivity patterns specified in the MCD algorithm then allowed NAB sets to be aligned in their proper juxtaposition within secondary structural units. The units of secondary structure were placed within the polypeptide sequence of identification of a small number of side-chain J-coupled spin systems, found by direct recognition in 2D spectra of some J-coupled spin systems and by pairwise comparisons of the J-correlated spectra of six homologous cytochromes c having a small number of known amino acid differences. The placement of a given segment in this way defines the amino acid identity of all its NAB sets. This foreknowledge allowed the vast majority of the side-chain resonances to be discerned in J-correlated spectra. Extensive confirmation of the assignments derives internally from multiple main-chain NOE connectivities and their consistency following temperature-induced changes of the chemical shifts of NOE-correlated protons. The observed patterns of main-chain NOEs provide some structural information and suggest small but potentially significant differences between the solution structure observed by NMR and that defined earlier in crystallographic studies at 2.8-A resolution.     

NMR study of thymulin, a lymphocyte differentiating thymic nonapeptide. Conformational states of free peptide in solution

The nonapeptide less than Glu-Ala-Lys-Ser-Gln-Gly-Gly-Ser-Asn (formerly called serum thymic factor) is a factor produced by the thymic epithelium, which needs a zinc ion to express its immunoregulatory properties. We report here on 1H and 13C NMR investigation of the conformational properties of the free peptide in aqueous medium and in dimethyl sulfoxide-d6 solution by a combination of homo- and heteronuclear one- and two-dimensional experiments. The various resonances have been assigned in a straightforward manner on the basis of 1H,1H COSY spectroscopy for the recognition of the proton spin systems; two-dimensional NOESY spectra with the correlation peaks across amide bonds and for the amino acid sequence assignment; amide bonds and for the amino acid sequence assignment; 13C,1H COSY experiments using selective polarization transfer from 1H- to 13C-nucleus via the 13C,1H long-range couplings for the attribution of the carboxyl and carbonyl groups; and 13C,1H COSY experiments with selective polarization transfer via the 13C,1H direct couplings for the assignment of all the aliphatic carbons. Other experiments such as pH-dependent chemical shifts, combined use of multiple and selective proton-decoupled 1H and 13C NMR spectra, the temperature and the concentration dependence of the proton shifts of the amide resonances, the solvent dependences of peptide carbonyl carbon resonances, and comparison of the spectra with three different analogues were performed. In aqueous solution, the data are compatible with the assumption of a highly mobile dynamic equilibrium among different conformations, whereas in dimethyl sulfoxide-d6, a more rigid structure is found involving three internal hydrogen bonds. These observations provide an insight into the conformational tendencies of this peptidic hormone in two different media.     

CSSI-PRO: a method for secondary structure type editing,assignment and estimation in proteins using linear combination of backbone chemical shifts

Estimation of secondary structure in polypeptides is important for studying their structure, folding and dynamics. In NMR spectroscopy, such information is generally obtained after sequence specific resonance assignments are completed. We present here a new methodology for assignment of secondary structure type to spin systems in proteins directly from NMR spectra, without prior knowledge of resonance assignments. The methodology, named Combination of Shifts for Secondary Structure Identification in Proteins (CSSI-PRO), involves detection of specific linear combination of backbone ¹H^α and ¹³C′ chemical shifts in a two-dimensional (2D) NMR experiment based on G-matrix Fourier transform (GFT) NMR spectroscopy. Such linear combinations of shifts facilitate editing of residues belonging to α-helical/β-strand regions into distinct spectral regions nearly independent of the amino acid type, thereby allowing the estimation of overall secondary structure content of the protein. Comparison of the predicted secondary structure content with those estimated based on their respective 3D structures and/or the method of Chemical Shift Index for 237 proteins gives a correlation of more than 90% and an overall rmsd of 7.0%, which is comparable to other biophysical techniques used for structural characterization of proteins. Taken together, this methodology has a wide range of applications in NMR spectroscopy such as rapid protein structure determination, monitoring conformational changes in protein-folding/ligand-binding studies and automated resonance assignment. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming

Despite significant advances in automated nuclear magnetic resonance-based protein structure determination, the high numbers of false positives and false negatives among the peaks selected by fully automated methods remain a problem. These false positives and negatives impair the performance of resonance assignment methods. One of the main reasons for this problem is that the computational research community often considers peak picking and resonance assignment to be two separate problems, whereas spectroscopists use expert knowledge to pick peaks and assign their resonances at the same time. We propose a novel framework that simultaneously conducts slice picking and spin system forming, an essential step in resonance assignment. Our framework then employs a genetic algorithm, directed by both connectivity information and amino acid typing information from the spin systems, to assign the spin systems to residues. The inputs to our framework can be as few as two commonly used spectra, i.e., CBCA(CO)NH and HNCACB. Different from the existing peak picking and resonance assignment methods that treat peaks as the units, our method is based on ‘slices’, which are one-dimensional vectors in three-dimensional spectra that correspond to certain ( \(N, H\) ) values. Experimental results on both benchmark simulated data sets and four real protein data sets demonstrate that our method significantly outperforms the state-of-the-art methods while using a less number of spectra than those methods. Our method is freely available at http://sfb.kaust.edu.sa/Pages/Software.aspx.     

Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment

Reliable automated NOE assignment and structure calculation on the basis of a largely complete, assigned input chemical shift list and a list of unassigned NOESY cross peaks has recently become feasible for routine NMR protein structure calculation and has been shown to yield results that are equivalent to those of the conventional, manual approach. However, these algorithms rely on the availability of a virtually complete list of the chemical shifts. This paper investigates the influence of incomplete chemical shift assignments on the reliability of NMR structures obtained with automated NOESY cross peak assignment. The program CYANA was used for combined automated NOESY assignment with the CANDID algorithm and structure calculations with torsion angle dynamics at various degrees of completeness of the chemical shift assignment which was simulated by random omission of entries in the experimental ¹H chemical shift lists that had been used for the earlier, conventional structure determinations of two proteins. Sets of structure calculations were performed choosing the omitted chemical shifts randomly among all assigned hydrogen atoms, or among aromatic hydrogen atoms. For comparison, automated NOESY assignment and structure calculations were performed with the complete experimental chemical shift but under random omission of NOESY cross peaks. When heteronuclear-resolved three-dimensional NOESY spectra are available the current CANDID algorithm yields in the absence of up to about 10% of the experimental ¹H chemical shifts reliable NOE assignments and three-dimensional structures that deviate by less than 2 Å from the reference structure obtained using all experimental chemical shift assignments. In contrast, the algorithm can accommodate the omission of up to 50% of the cross peaks in heteronuclear- resolved NOESY spectra without producing structures with a RMSD of more than 2 Å to the reference structure. When only homonuclear NOESY spectra are available, the algorithm is slightly more susceptible to missing data and can tolerate the absence of up to about 7% of the experimental ¹H chemical shifts or of up to 30% of the NOESY peaks.Abbreviations: BmPBP^A – Bombyx mori pheromone binding protein form A; CYANA – combined assignment and dynamics algorithm for NMR applications; NMR – nuclear magnetic resonance; NOE – nuclear Overhauser effect; NOESY – NOE spectroscopy; RMSD – root-mean-square deviation; WmKT – Williopsis mrakii killer toxin     

Systematic application of high-resolution, phase-sensitive two-dimensional 1H-NMR techniques for the identification of the amino-acid-proton spin systems in proteins. Rabbit metallothionein-2

Novel strategies for elucidation and classification of amino acid 1H-NMR spin systems in proteins were developed exploiting recently introduced two-dimensional NMR techniques such as phase-sensitive double-quantum-filtered correlated spectroscopy, relayed coherence transfer spectroscopy, double quantum spectroscopy and nuclear Overhauser spectroscopy. Due to the improved resolution in phase-sensitive spectra, the fine structure of cross peaks could be exploited as a powerful source of information for establishing 1H-1H connectivities. Principles for the interpretation of multiplet structures of absorption mode cross peaks are discussed. With these methods the 1H spin systems of rabbit liver metallothionein-2 were elucidated and classified according to amino acid types. Despite the intrinsically difficult situation arising from the unusual amino acid composition of this protein, a more complete characterization of the 1H spin systems prior to the step of sequential resonance assignments was achieved with the presently introduced methodology than was possible in earlier studies of proteins of similar size.     

Automated combined assignment of NOESY spectra and three-dimensional protein structure determination

A procedure for automated protein structure determination is presented that is based on an iterative procedure during which the NOESY peak list assignment and the structure calculation are performed simultaneously. The input consists of a list of NOESY peak positions and a list of chemical shifts as obtained from sequence-specific resonance assignment. For the present applications of this approach the previously introduced NOAH routine was implemented in the distance geometry program DIANA. As an illustration, experimental 2D and 3D NOESY cross-peak lists of six proteins have been analyzed, for which complete sequence-specific ¹H assignments are available for the polypeptide backbone and the amino acid side chains. The automated method assigned 70–90% of all NOESY cross peaks, which is on average 10% less than with the interactive approach, and only between 0.8% and 2.4% of the automatically assigned peaks had a different assignment than in the corresponding manually assigned peak lists. The structures obtained with NOAH/DIANA are in close agreement with those from manually assigned peak lists, and with both approaches the residual constraint violations correspond to high-quality NMR structure determinations. Systematic comparisons of the bundles of conformers that represent corresponding automatically and interactively determined structures document the absence of significant bias in either approach, indicating that an important step has been made towards automation of structure determination from NMR spectra.     

Application of the two-dimensional nmr techniques on a des(Ala,Gly)-somatostatin analog

Two-dimensional nmr techniques have been carried out for the peak assignment of the spectrum of a somatostatin analog. Two-dimensional J-resolved spectroscopy simplified the rather broad and complicated spectrum to show the center of chemical shifts of each resonance and gave information on the coupling profiles. Another technique, two-dimensional spin-echo correlated spectroscopy, revealed the connectivities between protons which are correlated by weak spin–spin couplings. The combination of the results of these two complementary techniques made it possible for us to assign almost all peaks of the spectrum of the 11-residue somatostatin analog.     

Resolution and sensitivity of high field nuclear magnetic resonance spectroscopy

NMR frequency assignments are usually considered a prerequisite for the analysis of NOESY spectra, in turn required for the calculation of biomolecular structures. In contrast, as we propose here, relatively high numbers of unambiguous NOE identities can be consistently achieved in an automated manner by relying only on grouping resonances into connected spin systems. To achieve this goal, we have developed for proteins two protocols, SPI and BACUS, based on Bayesian inference. SPI (Grishaev and Llinás, 2002c) produces a list of the (1)H resonance frequencies from homo- and hetero-nuclear multidimensional spectra, grouped into effective spin systems. BACUS automatically establishes probabilistic identities of NOESY cross-peaks in terms of the chemical shifts provided by SPI. BACUS requires neither assignment of resonances nor an initial structural model. It successfully copes with chemical shift overlap and does so without cycling through 3D structure calculations. The method exploits the self-consistency of the NOESY graph by taking advantage of a network of J- as well as NOE-connected "reporter" protons sorted via SPI. BACUS was validated by tests on experimental NOESY data recorded for the col 2 and kringle 2 domains.     

A general method for assigning NMR spectra of denatured proteins using 3D HC(CO)NH-TOCSY triple resonance experiments

Summary A general approach for assigning the resonances of uniformly ¹⁵N- and ¹³C-labeled proteins in their unfolded state is presented. The assignment approach takes advantage of the spectral dispersion of the amide nitrogen chemical shifts in denatured proteins by correlating side chain and backbone carbon and proton frequencies with the amide resonances of the same and adiacent residues. The ¹H resonances of the individual amino acid spin systems are correlated with their intraresidue amide in a 3D ¹⁵N-edited ¹H, ¹H-TOCSY-HSQC experiment, which allows the spin systems to be assigned to amino acid type. The spin systems are then linked to the adjacent i-1 spin system using the 3D H(C)(CO)NH-TOCSY experiment. Complete ¹³C assignments are obtained from the 3D (H)C(CO)NH-TOCSY experiment. Unlike other methods for assigning denatured proteins, this approach does not require previous knowledge of the native state assignments or specific interconversion rates between the native and denatured forms. The strategy is demonstrated by assigning the ¹H, ¹³C, and ¹⁵N resonances of the FK506 binding protein denatured in 6.3 M urea.     

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.