SPARTA+: a modest improvement in empirical NMR chemical shift prediction by means of an artificial neural network

NMR chemical shifts provide important local structural information for proteins and are key in recently described protein structure generation protocols. We describe a new chemical shift prediction program, SPARTA+, which is based on artificial neural networking. The neural network is trained on a large carefully pruned database, containing 580 proteins for which high-resolution X-ray structures and nearly complete backbone and ¹³C^β chemical shifts are available. The neural network is trained to establish quantitative relations between chemical shifts and protein structures, including backbone and side-chain conformation, H-bonding, electric fields and ring-current effects. The trained neural network yields rapid chemical shift prediction for backbone and ¹³C^β atoms, with standard deviations of 2.45, 1.09, 0.94, 1.14, 0.25 and 0.49 ppm for δ¹⁵N, δ¹³C’, δ¹³C^α, δ¹³C^β, δ¹H^α and δ¹H^N, respectively, between the SPARTA+ predicted and experimental shifts for a set of eleven validation proteins. These results represent a modest but consistent improvement (2–10%) over the best programs available to date, and appear to be approaching the limit at which empirical approaches can predict chemical shifts.     

Improved pulse sequences for sequence specific assignment of aromatic proton resonances in proteins

Aromatic proton resonances of proteins are notoriously difficult to assign. Through-bond correlation experiments are preferable over experiments that rely on through-space interactions because they permit aromatic chemical shift assignments to be established independently of the structure determination process. Known experimental schemes involving a magnetization transfer across the C^β–C^γ bond in aromatic side chains either suffer from low efficiency for the relay beyond the C^δ position, use sophisticated ¹³C mixing schemes, require probe heads suitable for application of high ¹³C radio-frequency fields or rely on specialized isotopic labelling patterns. Novel methods are proposed that result in sequential assignment of all aromatic protons in uniformly ¹³C/¹⁵N labelled proteins using standard spectrometer hardware. Pulse sequences consist of routinely used building blocks and are therefore reasonably simple to implement. Ring protons may be correlated with β-carbons and, alternatively, with amide protons (and nitrogens) or carbonyls in order to take advantage of the superior dispersion of backbone resonances. It is possible to record spectra in a non-selective manner, yielding signals of all aromatic residues, or as amino-acid type selective versions to further reduce ambiguities. The new experiments are demonstrated with four different proteins with molecular weights ranging from 11 kDa to 23 kDa. Their performance is compared with that of (Hβ)Cβ(CγCδ)Hδ and (Hβ)Cβ(CγCδCɛ)Hɛ pulse sequences [Yamazaki et al. (1993) J Am Chem Soc 115:11054–11055]. Electronic Supplementary Material The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

Resonance assignments and secondary structure of a phytocystatin from Ananas comosus

A cDNA encoding a cysteine protease inhibitor, cystatin was cloned from pineapple (Ananas comosus L.) stem. This clone was constructed into an expression vector and expressed in E. coli and purified to homogeneous. The recombinant pineapple cystatins (AcCYS) showed effectively inhibitory activity toward cysteine proteases including papain, bromelain, and cathepsin B. In order to unravel its inhibitory action from structural point of view, multidimensional heteronuclear NMR techniques were used to characterize the structure of AcCYS. The full ¹H, ¹⁵N, and ¹³C resonance assignments of AcCYS were determined. The secondary structure of AcCYS was identified by using the assigned chemical shift of ¹Hα, ¹³Cα, ¹³Cβ, and ¹³CO through the consensus chemical shift index (CSI). The results of CSI analysis suggest 5 β–strands (residues 45–47, 84–91, 94–104, 106–117, and 123–130) and one α–helix (residues 55–73).     

Backbone assignments of the 34 kDa ketopantoate reductase from E. coli

Ketopantoate reductase is an essential enzyme for pantothenate (vitamin B₅) synthesis and a potential antibiotic target. Here we report the ¹⁵N and ¹HN, ¹³C′, ¹³C^α and ¹³C^β chemical shift assignments of the 34 kDa ketopantoate reductase in its apo state.     

Identification of Zinc-ligated Cysteine Residues Based on 13Cα and 13Cβ Chemical Shift Data

Although a significant number of proteins include bound metals as part of their structure, the identification of amino acid residues coordinated to non-paramagnetic metals by NMR remains a challenge. Metal ligands can stabilize the native structure and/or play critical catalytic roles in the underlying biochemistry. An atom’s chemical shift is exquisitely sensitive to its electronic environment. Chemical shift data can provide valuable insights into structural features, including metal ligation. In this study, we demonstrate that overlapped ¹³Cβ chemical shift distributions of Zn-ligated and non-metal-ligated cysteine residues are largely resolved by the inclusion of the corresponding ¹³Cα chemical shift information, together with secondary structural information. We demonstrate this with a bivariate distribution plot, and statistically with a multivariate analysis of variance (MANOVA) and hierarchical logistic regression analysis. Using 287 ¹³Cα/¹³Cβ shift pairs from 79 proteins with known three-dimensional structures, including 86 ¹³Cα and¹³Cβ shifts for 43 Zn-ligated cysteine residues, along with corresponding oxidation state and secondary structure information, we have built a logistic regression model that distinguishes between oxidized cystines, reduced (non-metal ligated) cysteines, and Zn-ligated cysteines. Classifying cysteines/cystines with a statisical model incorporating all three phenomena resulted in a predictor of Zn ligation with a recall, precision and F-measure of 83.7%, and an accuracy of 95.1%. This model was applied in the analysis of Bacillus subtilis IscU, a protein involved in iron–sulfur cluster assembly. The model predicts that all three cysteines of IscU are metal ligands. We confirmed these results by (i) examining the effect of metal chelation on the NMR spectrum of IscU, and (ii) inductively coupled plasma mass spectrometry analysis. To gain further insight into the frequency of occurrence of non-cysteine Zn ligands, we analyzed the Protein Data Bank and found that 78% of the Zn ligands are histidine and cysteine (with nearly identical frequencies), and 18% are acidic residues aspartate and glutamate. Electronic Supplementary Material Supplementary material is available for this article at and is accessible for authorized users.     

High resolution <Superscript>13</Superscript>C-detected solid-state NMR spectroscopy of a deuterated protein

High resolution ¹³C-detected solid-state NMR spectra of the deuterated beta-1 immunoglobulin binding domain of the protein G (GB1) have been collected to show that all ¹⁵N, ¹³C′, ¹³Cα and ¹³Cβ sites are resolved in ¹³C–¹³C and ¹⁵N–¹³C spectra, with significant improvement in T ₂ relaxation times and resolution at high magnetic field (750 MHz). The comparison of echo T ₂ values between deuterated and protonated GB1 at various spinning rates and under different decoupling schemes indicates that ¹³Cα T ₂′ times increase by almost a factor of two upon deuteration at all spinning rates and under moderate decoupling strength, and thus the deuteration enables application of scalar-based correlation experiments that are challenging from the standpoint of transverse relaxation, with moderate proton decoupling. Additionally, deuteration in large proteins is a useful strategy to selectively detect polar residues that are often important for protein function and protein–protein interactions.     

2DCSi: identification of protein secondary structure and redox state using 2D cluster analysis of NMR chemical shifts

Chemical shifts of amino acids in proteins are the most sensitive and easily obtainable NMR parameters that reflect the primary, secondary, and tertiary structures of the protein. In recent years, chemical shifts have been used to identify secondary structure in peptides and proteins, and it has been confirmed that ¹H^α, ¹³C^α, ¹³C^β, and ¹³C′ NMR chemical shifts for all 20 amino acids are sensitive to their secondary structure. Currently, most of the methods are purely based on one-dimensional statistical analyses of various chemical shifts for each residue to identify protein secondary structure. However, it is possible to achieve an increased accuracy from the two-dimensional analyses of these chemical shifts. The 2DCSi approach performs two-dimension cluster analyses of ¹H^α, ¹H^N, ¹³C^α, ¹³C^β, ¹³C′, and ¹⁵N^H chemical shifts to identify protein secondary structure and the redox state of cysteine residue. For the analysis of paired chemical shifts of 6 data sets, each of the 20 amino acids has its own 15 two-dimension cluster scattering diagrams. Accordingly, the probabilities for identifying helix and extended structure were calculated by using our scoring matrix. Compared with existing the chemical shift-based methods, it appears to improve the prediction accuracy of secondary structure identification, particularly in the extended structure. In addition, the probability of the given residue to be helix or extended structure is displayed, allows the users to make decisions by themselves. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users. Grant sponsor: National Science Council of ROC; Grant numbers: NSC-94-2323-B006- 001, NSC-93-2212-E-006.     

Assignment strategies for aliphatic protons in the solid-state in randomly protonated proteins

Biological solid-state nuclear magnetic resonance spectroscopy developed rapidly in the past two decades and emerged as an important tool for structural biology. Resonance assignment is an essential prerequisite for structure determination and the characterization of motional properties of a molecule. Experiments, which rely on carbon or nitrogen detection, suffer, however, from low sensitivity. Recently, we introduced the RAP (Reduced Adjoining Protonation) labeling scheme, which allows to detect backbone and sidechain protons with high sensitivity and resolution. We present here a ¹H-detected 3D (H)CCH experiment for assignment of backbone and sidechain proton resonances. Resolution is significantly improved by employing simultaneous ¹³CO and ¹³Cβ J-decoupling during evolution of the ¹³Cα chemical shift. In total, ~90% of the ¹Hα-¹³Cα backbone resonances of chicken α-spectrin SH3 could be assigned.     

Direct methods and residue type specific isotope labeling in NMR structure determination and model-driven sequential assignment

Direct methods in NMR based structure determination start from an unassigned ensemble of unconnected gaseous hydrogen atoms. Under favorable conditions they can produce low resolution structures of proteins. Usually a prohibitively large number of NOEs is required, to solve a protein structure ab-initio, but even with a much smaller set of distance restraints low resolution models can be obtained which resemble a protein fold. One problem is that at such low resolution and in the absence of a force field it is impossible to distinguish the correct protein fold from its mirror image. In a hybrid approach these ambiguous models have the potential to aid in the process of sequential backbone chemical shift assignment when ¹³C^β and ¹³C′ shifts are not available for sensitivity reasons. Regardless of the overall fold they enhance the information content of the NOE spectra. These, combined with residue specific labeling and minimal triple-resonance data using ¹³C^α connectivity can provide almost complete sequential assignment. Strategies for residue type specific labeling with customized isotope labeling patterns are of great advantage in this context. Furthermore, this approach is to some extent error-tolerant with respect to data incompleteness, limited precision of the peak picking, and structural errors caused by misassignment of NOEs. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Extension of the HA-detection based approach: (HCA)CON(CA)H and (HCA)NCO(CA)H experiments for the main-chain assignment of intrinsically disordered proteins

Extensive resonance overlap exacerbates assignment of intrinsically disordered proteins (IDPs). This issue can be circumvented by utilizing ¹⁵N, ¹³C′ and ¹H^N spins, where the chemical shift dispersion is mainly dictated by the characteristics of consecutive amino acid residues. Especially ¹⁵N and ¹³C′ spins offer superior chemical shift dispersion in comparison to ¹³C^α and ¹³C^β spins. However, HN-detected experiments suffer from exchange broadening of amide proton signals on IDPs especially under alkali conditions. To that end, we propose here two novel HA-detected experiments, (HCA)CON(CA)H and (HCA)NCO(CA)H and a new assignment protocol based on panoply of unidirectional HA-detected experiments that enable robust backbone assignment of IDPs also at high pH. The new approach was tested at pH 6.5 and pH 8.5 on cancer/testis antigen CT16, a 110-residue IDP, and virtually complete backbone assignment of CT16 was obtained by employing the novel HA-detected experiments together with the previously introduced iH(CA)NCO scheme. Remarkably, also those 10 N-terminal residues that remained unassigned in our earlier HN-detection based assignment approach even at pH 6.5 were now readily assigned. Moreover, theoretical calculations and experimental results suggest that overall sensitivity of the new experiments is also applicable to small or medium sized globular proteins that require alkaline conditions.     

HA-detected experiments for the backbone assignment of intrinsically disordered proteins

We propose a new alpha proton detection based approach for the sequential assignment of natively unfolded proteins. The proposed protocol superimposes on following features: HA-detection (1) enables assignment of natively unfolded proteins at any pH, i.e., it is not sensitive to rapid chemical exchange undergoing in natively unfolded proteins even at moderately high pH. (2) It allows straightforward assignment of proline-rich polypeptides without additional proline-customized experiments. (3) It offers more streamlined and less ambiguous assignment based on solely intraresidual ¹⁵N(i)-¹³C′(i)-H^α(i) (or ¹⁵N(i)-¹³C^α(i)-H^α(i)) and sequential ¹⁵N(i + 1)-¹³C′(i)-H^α(i) (or ¹⁵N(i + 1)-¹³C^α(i)-H^α(i)) correlation experiments together with efficient use of chemical shifts of ¹⁵N and ¹³C′ nuclei, which show smaller dependence on residue type. We have tested the proposed protocol on two proteins, small globular 56-residue GB1, and highly disordered, proline-rich 47-residue fifth repeat of EspF_U. Using the proposed approach, we were able to assign 90% of ¹H^α, ¹³C^α, ¹³C′, ¹⁵N chemical shifts in EspF_U. We reckon that the HA-detection based strategy will be very useful in the assignment of natively unfolded proline-rich proteins or polypeptide chains.     

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.     

Measuring <Superscript>13</Superscript>C<Superscript>β</Superscript> chemical shifts of invisible excited states in proteins by relaxation dispersion NMR spectroscopy

A labeling scheme is introduced that facilitates the measurement of accurate ¹³C^β chemical shifts of invisible, excited states of proteins by relaxation dispersion NMR spectroscopy. The approach makes use of protein over-expression in a strain of E. coli in which the TCA cycle enzyme succinate dehydrogenase is knocked out, leading to the production of samples with high levels of ¹³C enrichment (30–40%) at C^β side-chain carbon positions for 15 of the amino acids with little ¹³C label at positions one bond removed (≈5%). A pair of samples are produced using [1-¹³C]-glucose/NaH¹²CO₃ or [2-¹³C]-glucose as carbon sources with isolated and enriched (>30%) ¹³C^β positions for 11 and 4 residues, respectively. The efficacy of the labeling procedure is established by NMR spectroscopy. The utility of such samples for measurement of ¹³C^β chemical shifts of invisible, excited states in exchange with visible, ground conformations is confirmed by relaxation dispersion studies of a protein–ligand binding exchange reaction in which the extracted chemical shift differences from dispersion profiles compare favorably with those obtained directly from measurements on ligand free and fully bound protein samples.     

Uncovering symmetry-breaking vector and reliability order for assigning secondary structures of proteins from atomic NMR chemical shifts in amino acids

Unravelling the complex correlation between chemical shifts of ¹³ C ^α, ¹³ C ^β, ¹³ C′, ¹ H ^α, ¹⁵ N, ¹ H ^N atoms in amino acids of proteins from NMR experiment and local structural environments of amino acids facilitates the assignment of secondary structures of proteins. This is an important impetus for both determining the three-dimensional structure and understanding the biological function of proteins. The previous empirical correlation scores which relate chemical shifts of ¹³ C ^α, ¹³ C ^β, ¹³ C′, ¹ H ^α, ¹⁵ N, ¹ H ^N atoms to secondary structures resulted in progresses toward assigning secondary structures of proteins. However, the physical-mathematical framework for these was elusive partly due to both the limited and orthogonal exploration of higher-dimensional chemical shifts of hetero-nucleus and the lack of physical-mathematical understanding underlying those correlation scores. Here we present a simple multi-dimensional hetero-nuclear chemical shift score function (MDHN-CSSF) which captures systematically the salient feature of such complex correlations without any references to a random coil state of proteins. We uncover the symmetry-breaking vector and its reliability order not only for distinguishing different secondary structures of proteins but also for capturing the delicate sensitivity interplayed among chemical shifts of ¹³ C ^α, ¹³ C ^β, ¹³ C′, ¹ H ^α, ¹⁵ N, ¹ H ^N atoms simultaneously, which then provides a straightforward framework toward assigning secondary structures of proteins. MDHN-CSSF could correctly assign secondary structures of training (validating) proteins with the favourable (comparable) Q3 scores in comparison with those from the previous correlation scores. MDHN-CSSF provides a simple and robust strategy for the systematic assignment of secondary structures of proteins and would facilitate the de novo determination of three-dimensional structures of proteins.     

Recoupling and decoupling of nuclear spin interactions at high MAS frequencies: numerical design of CN<Stack><Subscript><Emphasis Type="Italic">n</Emphasis></Subscript><Superscript>ν</Superscript></Stack> symmetry-based RF pulse schemes

The CN _n ^ν class of RF pulse schemes, commonly employed for recoupling and decoupling of nuclear spin interactions in magic angle spinning solid state NMR studies of biological systems, involves the application of a basic “C” element corresponding to an RF cycle with unity propagator. In this study, the design of CN _n ^ν symmetry-based RF pulse sequences for achieving ¹³C–¹³C double-quantum dipolar recoupling and through bond scalar coupling mediated ¹³C–¹³C chemical shift correlation has been examined at high MAS frequencies employing broadband, constant-amplitude, phase-modulated basic “C” elements. The basic elements were implemented as a sandwich of a small number of short pulses of equal duration with each pulse characterised by an RF phase value. The phase-modulation profile of the “C” element was optimised numerically so as to generate efficient RF pulse sequences. The performances of the sequences were evaluated via numerical simulations and experimental measurements and are presented here. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Combining NMR ensembles and molecular dynamics simulations provides more realistic models of protein structures in solution and leads to better chemical shift prediction

While chemical shifts are invaluable for obtaining structural information from proteins, they also offer one of the rare ways to obtain information about protein dynamics. A necessary tool in transforming chemical shifts into structural and dynamic information is chemical shift prediction. In our previous work we developed a method for 4D prediction of protein ¹H chemical shifts in which molecular motions, the 4th dimension, were modeled using molecular dynamics (MD) simulations. Although the approach clearly improved the prediction, the X-ray structures and single NMR conformers used in the model cannot be considered fully realistic models of protein in solution. In this work, NMR ensembles (NMRE) were used to expand the conformational space of proteins (e.g. side chains, flexible loops, termini), followed by MD simulations for each conformer to map the local fluctuations. Compared with the non-dynamic model, the NMRE+MD model gave 6–17% lower root-mean-square (RMS) errors for different backbone nuclei. The improved prediction indicates that NMR ensembles with MD simulations can be used to obtain a more realistic picture of protein structures in solutions and moreover underlines the importance of short and long time-scale dynamics for the prediction. The RMS errors of the NMRE+MD model were 0.24, 0.43, 0.98, 1.03, 1.16 and 2.39 ppm for ¹Hα, ¹HN, ¹³Cα, ¹³Cβ, ¹³CO and backbone ¹⁵N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at .     

Effects of side-chain orientation on the <Superscript>13</Superscript>C chemical shifts of antiparallel β-sheet model peptides

The dependence of the ¹³C chemical shift on side-chain orientation was investigated at the density functional level for a two-strand antiparallel β-sheet model peptide represented by the amino acid sequence Ac-(Ala)₃-X-(Ala)₁₂-NH₂ where X represents any of the 17 naturally occurring amino acids, i.e., not including alanine, glycine and proline. The dihedral angles adopted for the backbone were taken from, and fixed at, observed experimental values of an antiparallel β-sheet. We carried out a cluster analysis of the ensembles of conformations generated by considering the side-chain dihedral angles for each residue X as variables, and use them to compute the ¹³C chemical shifts at the density functional theory level. It is shown that the adoption of the locally-dense basis set approach for the quantum chemical calculations enabled us to reduce the length of the chemical-shift calculations while maintaining good accuracy of the results. For the 17 naturally occurring amino acids in an antiparallel β-sheet, there is (i) good agreement between computed and observed ¹³C^α and ¹³C^β chemical shifts, with correlation coefficients of 0.95 and 0.99, respectively; (ii) significant variability of the computed ¹³C^α and ¹³C^β chemical shifts as a function of χ¹ for all amino acid residues except Ser; and (iii) a smaller, although significant, dependence of the computed ¹³C^α chemical shifts on χ^ξ (with ξ ≥ 2) compared to χ¹ for eleven out of seventeen residues. Our results suggest that predicted ¹³C^α and ¹³C^β chemical shifts, based only on backbone (φ,ψ) dihedral angles from high-resolution X-ray structure data or from NMR-derived models, may differ significantly from those observed in solution if the dihedral-angle preferences for the side chains are not taken into account. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

GFT projection NMR based resonance assignment of membrane proteins: application to subunit c of <Emphasis Type="Italic">E. coli</Emphasis> F<Subscript>1</Subscript>F<Subscript>0</Subscript> ATP synthase in LPPG micelles

G-matrix FT projection NMR spectroscopy was employed for resonance assignment of the 79-residue subunit c of the Escherichia coli F₁F₀ ATP synthase embedded in micelles formed by lyso palmitoyl phosphatidyl glycerol (LPPG). Five GFT NMR experiments, that is, (3,2)D HNNCO, L-(4,3)D HNNC ^αβ C ^α, L-(4,3)D HNN(CO)C ^αβ C ^α, (4,2)D HACA(CO)NHN and (4,3)D HCCH, were acquired along with simultaneous 3D ¹⁵N, ¹³C^aliphatic, ¹³C^aromatic-resolved [¹H,¹H]-NOESY with a total measurement time of ∼43 h. Data analysis resulted in sequence specific assignments for all routinely measured backbone and ¹³C^β shifts, and for 97% of the side chain shifts. Moreover, the use of two G²FT NMR experiments, that is, (5,3)D HN{N,CO}{C ^αβ C ^α} and (5,3)D {C ^αβ C ^α}{CON}HN, was explored to break the very high chemical shift degeneracy typically encountered for membrane proteins. It is shown that the 4D and 5D spectral information obtained rapidly from GFT and G²FT NMR experiments enables one to efficiently obtain (nearly) complete resonance assignments of membrane proteins. Qi Zhang, Hanudatta S. Atreya, Douglas E. Kamen, Mark E. Girvin and Thomas Szyperski—New York Consortium on Membrane Protein Structure.     

Temperature dependence of fast carbonyl backbone dynamics in chicken villin headpiece subdomain

Temperature-dependence of protein dynamics can provide information on details of the free energy landscape by probing the characteristics of the potential responsible for the fluctuations. We have investigated the temperature-dependence of picosecond to nanosecond backbone dynamics at carbonyl carbon sites in chicken villin headpiece subdomain protein using a combination of three NMR relaxation rates: ¹³C′ longitudinal rate, and two cross-correlated rates involving dipolar and chemical shift anisotropy (CSA) relaxation mechanisms, ¹³C′/¹³C′-¹³C^α CSA/dipolar and ¹³C′/¹³C′–¹⁵N CSA/dipolar. Order parameters have been extracted using the Lipari-Szabo model-free approach assuming a separation of the time scales of internal and molecular motions in the 2–16°C temperature range. There is a gradual deviation from this assumption from lower to higher temperatures, such that above 16°C the separation of the time scales is inconsistent with the experimental data and, thus, the Lipari-Szabo formalism can not be applied. While there are variations among the residues, on the average the order parameters indicate a markedly steeper temperature dependence at backbone carbonyl carbons compared to that probed at amide nitrogens in an earlier study. This strongly advocates for probing sites other than amide nitrogen for accurate characterization of the potential and other thermodynamics characteristics of protein backbone.     

CACA-TOCSY with alternate <Superscript>13</Superscript>C–<Superscript>12</Superscript>C labeling: a <Superscript>13</Superscript>C<Superscript>α</Superscript> direct detection experiment for mainchain resonance assignment,dihedral angle information,and amino acid type identification

We present a ¹³C direct detection CACA-TOCSY experiment for samples with alternate ¹³C–¹²C labeling. It provides inter-residue correlations between ¹³C^α resonances of residue i and adjacent C^αs at positions i − 1 and i + 1. Furthermore, longer mixing times yield correlations to C^α nuclei separated by more than one residue. The experiment also provides C^α-to-sidechain correlations, some amino acid type identifications and estimates for ψ dihedral angles. The power of the experiment derives from the alternate ¹³C–¹²C labeling with [1,3-¹³C] glycerol or [2-¹³C] glycerol, which allows utilizing the small scalar ³J_CC couplings that are masked by strong ¹J_CC couplings in uniformly ¹³C labeled samples.