Sequence correction of random coil chemical shifts: correlation between neighbor correction factors and changes in the Ramachandran distribution

Random coil chemical shifts are necessary for secondary chemical shift analysis, which is the main NMR method for identification of secondary structure in proteins. One of the largest challenges in the determination of random coil chemical shifts is accounting for the effect of neighboring residues. The contributions from the neighboring residues are typically removed by using neighbor correction factors determined based on each residue’s effect on glycine chemical shifts. Due to its unusual conformational freedom, glycine may be particularly unrepresentative for the remaining residue types. In this study, we use random coil peptides containing glutamine instead of glycine to determine the random coil chemical shifts and the neighbor correction factors. The resulting correction factors correlate to changes in the populations of the major wells in the Ramachandran plot, which demonstrates that changes in the conformational ensemble are an important source of neighbor effects in disordered proteins. Glutamine derived random coil chemical shifts and correction factors modestly improve our ability to predict ¹³C chemical shifts of intrinsically disordered proteins compared to existing datasets, and may thus improve the identification of small populations of transient structure in disordered proteins.     

Random coil chemical shift for intrinsically disordered proteins: effects of temperature and pH

Secondary chemical shift analysis is the main NMR method for detection of transiently formed secondary structure in intrinsically disordered proteins. The quality of the secondary chemical shifts is dependent on an appropriate choice of random coil chemical shifts. We report random coil chemical shifts and sequence correction factors determined for a GGXGG peptide series following the approach of Schwarzinger et al. (J Am Chem Soc 123(13):2970–2978, 2001). The chemical shifts are determined at neutral pH in order to match the conditions of most studies of intrinsically disordered proteins. Temperature has a non-negligible effect on the ¹³C random coil chemical shifts, so temperature coefficients are reported for the random coil chemical shifts to allow extrapolation to other temperatures. The pH dependence of the histidine random coil chemical shifts is investigated in a titration series, which allows the accurate random coil chemical shifts to be obtained at any pH. By correcting the random coil chemical shifts for the effects of temperature and pH, systematic biases of the secondary chemical shifts are minimized, which will improve the reliability of detection of transient secondary structure in disordered proteins.     

4D Non-uniformly sampled HCBCACON and 1 J(NCα)-selective HCBCANCO experiments for the sequential assignment and chemical shift analysis of intrinsically disordered proteins

A pair of 4D NMR experiments for the backbone assignment of disordered proteins is presented. The experiments exploit (13)C direct detection and non-uniform sampling of the indirectly detected dimensions, and provide correlations of the aliphatic proton (H(α), and H(β)) and carbon (C(α), C(β)) resonance frequencies to the protein backbone. Thus, all the chemical shifts regularly used to map the transient secondary structure motifs in the intrinsically disordered proteins (H(α), C(α), C(β), C', and N) can be extracted from each spectrum. Compared to the commonly used assignment strategy based on matching the C(α) and C(β) chemical shifts, inclusion of the H(α) and H(β) provides up to three extra resonance frequencies that decrease the chance of ambiguous assignment. The experiments were successfully applied to the original assignment of a 12.8 kDa intrinsically disordered protein having a high content of proline residues (26 %) in the sequence.     

A reduced dimensionality NMR pulse sequence and an efficient protocol for unambiguous assignment in intrinsically disordered proteins

Resonance assignment in intrinsically disordered proteins poses a great challenge because of poor chemical shift dispersion in most of the nuclei that are commonly monitored. Reduced dimensionality (RD) experiments where more than one nuclei are co-evolved simultaneously along one of the time axes of a multi-dimensional NMR experiment help to resolve this problem partially, and one can conceive of different combinations of nuclei for co-evolution depending upon the magnetization transfer pathways and the desired information content in the spectrum. Here, we present a RD experiment, (4,3)D-hNCOCAnH, which uses a combination of CO and CA chemical shifts along one of the axes of the 3-dimensional spectrum, to improve spectral dispersion on one hand, and provide information on four backbone atoms of every residue—HN, N, CA and CO chemical shifts—from a single experiment, on the other. The experiment provides multiple unidirectional sequential (i → i ? 1) amide ¹H correlations along different planes of the spectrum enabling easy assignment of most nuclei along the protein backbone. Occasional ambiguities that may arise due to degeneracy of amide proton chemical shifts are proposed to be resolved using the HNN experiment described previously (Panchal et al. in J Biomol NMR 20:135–147, 2001). Applications of the experiment and the assignment protocol have been demonstrated using intrinsically disordered α-synuclein (140 aa) protein.     

Conformational analysis of the full‐length M2 protein of the influenza A virus using solid‐state NMR

The influenza A M2 protein forms a proton channel for virus infection and mediates virus assembly and budding. While extensive structural information is known about the transmembrane helix and an adjacent amphipathic helix, the conformation of the N‐terminal ectodomain and the C‐terminal cytoplasmic tail remains largely unknown. Using two‐dimensional (2D) magic‐angle‐spinning solid‐state NMR, we have investigated the secondary structure and dynamics of full‐length M2 (M2FL) and found them to depend on the membrane composition. In 2D ¹³C DARR correlation spectra, 1,2‐dimyristoyl‐sn‐glycero‐3‐phosphocholine (DMPC)‐bound M2FL exhibits several peaks at β‐sheet chemical shifts, which result from water‐exposed extramembrane residues. In contrast, M2FL bound to cholesterol‐containing membranes gives predominantly α‐helical chemical shifts. Two‐dimensional J‐INADEQUATE spectra and variable‐temperature ¹³C spectra indicate that DMPC‐bound M2FL is highly dynamic while the cholesterol‐containing membranes significantly immobilize the protein at physiological temperature. Chemical‐shift prediction for various secondary‐structure models suggests that the β‐strand is located at the N‐terminus of the DMPC‐bound protein, while the cytoplasmic domain is unstructured. This prediction is confirmed by the 2D DARR spectrum of the ectodomain‐truncated M2(21–97), which no longer exhibits β‐sheet chemical shifts in the DMPC‐bound state. We propose that the M2 conformational change results from the influence of cholesterol, and the increased helicity of M2FL in cholesterol‐rich membranes may be relevant for M2 interaction with the matrix protein M1 during virus assembly and budding. The successful determination of the β‐strand location suggests that chemical‐shift prediction is a promising approach for obtaining structural information of disordered proteins before resonance assignment.     

The PROSECCO server for chemical shift predictions in ordered and disordered proteins

The chemical shifts measured in solution-state and solid-state nuclear magnetic resonance (NMR) are powerful probes of the structure and dynamics of protein molecules. The exploitation of chemical shifts requires methods to correlate these data with the protein structures and sequences. We present here an approach to calculate accurate chemical shifts in both ordered and disordered proteins using exclusively the information contained in their sequences. Our sequence-based approach, protein sequences and chemical shift correlations (PROSECCO), achieves the accuracy of the most advanced structure-based methods in the characterization of chemical shifts of folded proteins and improves the state of the art in the study of disordered proteins. Our analyses revealed fundamental insights on the structural information carried by NMR chemical shifts of structured and unstructured protein states.     

Network representation of protein interactions: Theory of graph description and analysis

A methodological framework is presented for the graph theoretical interpretation of NMR data of protein interactions. The proposed analysis generalizes the idea of network representations of protein structures by expanding it to protein interactions. This approach is based on regularization of residue‐resolved NMR relaxation times and chemical shift data and subsequent construction of an adjacency matrix that represents the underlying protein interaction as a graph or network. The network nodes represent protein residues. Two nodes are connected if two residues are functionally correlated during the protein interaction event. The analysis of the resulting network enables the quantification of the importance of each amino acid of a protein for its interactions. Furthermore, the determination of the pattern of correlations between residues yields insights into the functional architecture of an interaction. This is of special interest for intrinsically disordered proteins, since the structural (three‐dimensional) architecture of these proteins and their complexes is difficult to determine. The power of the proposed methodology is demonstrated at the example of the interaction between the intrinsically disordered protein osteopontin and its natural ligand heparin.     

Ultra-high field NMR studies of antibody binding and site-specific phosphorylation of alpha-synuclein

Although biological importance of intrinsically disordered proteins is becoming recognized, NMR analyses of this class of proteins remain as tasks with more challenge because of poor chemical shift dispersion. It is expected that ultra-high field NMR spectroscopy offers improved resolution to cope with this difficulty. Here, we report an ultra-high field NMR study of alpha-synuclein, an intrinsically disordered protein identified as the major component of the Lewy bodies. Based on NMR spectral data collected at a 920 MHz proton frequency, we performed epitope mapping of an anti-alpha-synuclein monoclonal antibody, and furthermore, characterized conformational effects of phosphorylation at Ser129 of alpha-synuclein.     

PPM: a side-chain and backbone chemical shift predictor for the assessment of protein conformational ensembles

The combination of the wide availability of protein backbone and side-chain NMR chemical shifts with advances in understanding of their relationship to protein structure makes these parameters useful for the assessment of structural-dynamic protein models. A new chemical shift predictor (PPM) is introduced, which is solely based on physical?Cchemical contributions to the chemical shifts for both the protein backbone and methyl-bearing amino-acid side chains. To explicitly account for the effects of protein dynamics on chemical shifts, PPM was directly refined against 100?ns long molecular dynamics (MD) simulations of 35 proteins with known experimental NMR chemical shifts. It is found that the prediction of methyl-proton chemical shifts by PPM from MD ensembles is improved over other methods, while backbone C??, C??, C??, N, and H^N chemical shifts are predicted at an accuracy comparable to the latest generation of chemical shift prediction programs. PPM is particularly suitable for the rapid evaluation of large protein conformational ensembles on their consistency with experimental NMR data and the possible improvement of protein force fields from chemical shifts.     

Reconstruction of non-uniformly sampled five-dimensional NMR spectra by signal separation algorithm

A method for five-dimensional spectral reconstruction of non-uniformly sampled NMR data sets is proposed. It is derived from the previously published signal separation algorithm, with major alterations to avoid unfeasible processing of an entire five-dimensional spectrum. The proposed method allows credible reconstruction of spectra from as little as a few hundred data points and enables sensitive resonance detection in experiments with a high dynamic range of peak intensities. The efficiency of the method is demonstrated on two high-resolution spectra for rapid sequential assignment of intrinsically disordered proteins, namely 5D HN(CA)CONH and 5D (HACA)CON(CO)CONH.     

VirtualSpectrum,a tool for simulating peak list for multi-dimensional NMR spectra

NMR spectroscopy is a widely used technique for characterizing the structure and dynamics of macromolecules. Often large amounts of NMR data are required to characterize the structure of proteins. To save valuable time and resources on data acquisition, simulated data is useful in the developmental phase, for data analysis, and for comparison with experimental data. However, existing tools for this purpose can be difficult to use, are sometimes specialized for certain types of molecules or spectra, or produce too idealized data. Here we present a fast, flexible and robust tool, VirtualSpectrum, for generating peak lists for most multi-dimensional NMR experiments for both liquid and solid state NMR. It is possible to tune the quality of the generated peak lists to include sources of artifacts from peak overlap, noise and missing signals. VirtualSpectrum uses an analytic expression to represent the spectrum and derive the peak positions, seamlessly handling overlap between signals. We demonstrate our tool by comparing simulated and experimental spectra for different multi-dimensional NMR spectra and analyzing systematically three cases where overlap between peaks is particularly relevant; solid state NMR data, liquid state NMR homonuclear ¹H and ¹⁵N-edited spectra, and 2D/3D heteronuclear correlation spectra of unstructured proteins. We analyze the impact of protein size and secondary structure on peak overlap and on the accuracy of structure determination based on data of different qualities simulated by VirtualSpectrum.     

Effects of NMR Spectral Resolution on Protein Structure Calculation

Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.     

Binding of intrinsically disordered proteins is not necessarily accompanied by a structural transition to a folded form

There are a large number of protein domains and even entire proteins, lacking ordered structure under physiological conditions. Intriguingly, a highly flexible, random coil-like conformation is the native and functional state for many proteins known to be involved in cell signaling. An example is a key component of immune signaling, the cytoplasmic region of the T cell receptor zeta subunit. This domain exhibits specific dimerization that is distinct from non-specific aggregation behavior seen in many systems. In this work, we use diffusion and chemical shift mapping NMR data to show that the protein does not undergo a transition between disordered and ordered states upon dimerization. This finding opposes the generally accepted view on the behavior of intrinsically disordered proteins, provides evidence for the existence of specific dimerization interactions for intrinsically disordered protein species and opens a new line of research in this new and quickly developing field.     

Four-dimensional 13C/13C-edited nuclear Overhauser enhancement spectroscopy of a protein in solution: application to interleukin 1 beta

A four-dimensional 13C/13C-edited NOESY experiment is described which dramatically improves the resolution of protein NMR spectra and enables the straightforward assignment of nuclear Overhauser effects involving aliphatic and/or aromatic protons in larger proteins. The experiment is demonstrated for uniformly (greater than 95%) 13C-labeled interleukin 1 beta, a protein of 153 residues and 17.4 kDa, which plays a key role in the immune response. NOEs between aliphatic and/or aromatic protons are first spread out into a third dimension by the 13C chemical shift of the carbon atom attached to the originating proton and subsequently into a fourth dimension by the 13C chemical shift of the carbon atom attached to the destination proton. Thus, each NOE cross peak is labeled by four chemical shifts. By this means, ambiguities in the assignment of NOEs that arise from chemical shift overlap and degeneracy are completely removed. Further, NOEs between protons with the same chemical shifts can readily be detected providing their attached carbon atoms have different 13C chemical shifts. The design of the pulse sequence requires special care to minimize the level of artifacts arising from undesired coherence transfer pathways, and in particular those associated with "diagonal" peaks which correspond to magnetization that has not been transferred from one proton to another.(ABSTRACT TRUNCATED AT 250 WORDS)     

In-Cell NMR Characterization of the Secondary Structure Populations of a Disordered Conformation of α-Synuclein within E. coli Cells

α-Synuclein is a small protein strongly implicated in the pathogenesis of Parkinson’s disease and related neurodegenerative disorders. We report here the use of in-cell NMR spectroscopy to observe directly the structure and dynamics of this protein within E. coli cells. To improve the accuracy in the measurement of backbone chemical shifts within crowded in-cell NMR spectra, we have developed a deconvolution method to reduce inhomogeneous line broadening within cellular samples. The resulting chemical shift values were then used to evaluate the distribution of secondary structure populations which, in the absence of stable tertiary contacts, are a most effective way to describe the conformational fluctuations of disordered proteins. The results indicate that, at least within the bacterial cytosol, α-synuclein populates a highly dynamic state that, despite the highly crowded environment, has the same characteristics as the disordered monomeric form observed in aqueous solution.     

The interplay between transient α-helix formation and side chain rotamer distributions in disordered proteins probed by methyl chemical shifts

The peptide backbones of disordered proteins are routinely characterized by NMR with respect to transient structure and dynamics. Little experimental information is, however, available about the side chain conformations and how structure in the backbone affects the side chains. Methyl chemical shifts can in principle report the conformations of aliphatic side chains in disordered proteins and in order to examine this two model systems were chosen: the acid denatured state of acyl-CoA binding protein (ACBP) and the intrinsically disordered activation domain of the activator for thyroid hormone and retinoid receptors (ACTR). We find that small differences in the methyl carbon chemical shifts due to the γ-gauche effect may provide information about the side chain rotamer distributions. However, the effects of neighboring residues on the methyl group chemical shifts obscure the direct observation of γ-gauche effect. To overcome this, we reference the chemical shifts to those in a more disordered state resulting in residue specific random coil chemical shifts. The (13)C secondary chemical shifts of the methyl groups of valine, leucine, and isoleucine show sequence specific effects, which allow a quantitative analysis of the ensemble of χ(2)-angles of especially leucine residues in disordered proteins. The changes in the rotamer distributions upon denaturation correlate to the changes upon helix induction by the co-solvent trifluoroethanol, suggesting that the side chain conformers are directly or indirectly related to formation of transient α-helices.     

Microtubule-associated protein (MAP) 4 interacts with microtubules in an intrinsically disordered manner

We previously used nuclear magnetic resonance (NMR) to analyze the structure of a synthetic tricosapeptide corresponding to an active site of microtubule-associated protein 4 (MAP4). To further the structural analysis, we have constructed a minimal active domain fragment of MAP4, encompassing the entire active site, and obtained its NMR spectra. The secondary structure prediction using partially assigned NMR data suggested that the fragment is largely unfolded. Two other independent techniques also demonstrated its unfolded nature, indicating that MAP4 belongs to the class of intrinsically disordered proteins (IDPs). The NMR spectra of the fragment-microtubule mixture revealed that the fragment binds to the microtubule using multiple binding sites, apparently contradicting our previous quantitative studies. Given that MAP4 is intrinsically disordered, we propose a mechanism in which any one of the binding sites is active at a time, which is one of the typical interaction mechanisms proposed for IDPs.     

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.     

Peak picking multidimensional NMR spectra with the contour geometry based algorithm CYPICK

The automated identification of signals in multidimensional NMR spectra is a challenging task, complicated by signal overlap, noise, and spectral artifacts, for which no universally accepted method is available. Here, we present a new peak picking algorithm, CYPICK, that follows, as far as possible, the manual approach taken by a spectroscopist who analyzes peak patterns in contour plots of the spectrum, but is fully automated. Human visual inspection is replaced by the evaluation of geometric criteria applied to contour lines, such as local extremality, approximate circularity (after appropriate scaling of the spectrum axes), and convexity. The performance of CYPICK was evaluated for a variety of spectra from different proteins by systematic comparison with peak lists obtained by other, manual or automated, peak picking methods, as well as by analyzing the results of automated chemical shift assignment and structure calculation based on input peak lists from CYPICK. The results show that CYPICK yielded peak lists that compare in most cases favorably to those obtained by other automated peak pickers with respect to the criteria of finding a maximal number of real signals, a minimal number of artifact peaks, and maximal correctness of the chemical shift assignments and the three-dimensional structure obtained by fully automated assignment and structure calculation.