Rapid and accurate calculation of protein 1H, 13C and 15N chemical shifts

A computer program (SHIFTX) is described which rapidly and accurately calculates the diamagnetic ¹H, ¹³C and ¹⁵N chemical shifts of both backbone and sidechain atoms in proteins. The program uses a hybrid predictive approach that employs pre-calculated, empirically derived chemical shift hypersurfaces in combination with classical or semi-classical equations (for ring current, electric field, hydrogen bond and solvent effects) to calculate ¹H, ¹³C and ¹⁵N chemical shifts from atomic coordinates. The chemical shift hypersurfaces capture dihedral angle, sidechain orientation, secondary structure and nearest neighbor effects that cannot easily be translated to analytical formulae or predicted via classical means. The chemical shift hypersurfaces were generated using a database of IUPAC-referenced protein chemical shifts – RefDB (Zhang et al., 2003), and a corresponding set of high resolution (<2.1 Å) X-ray structures. Data mining techniques were used to extract the largest pairwise contributors (from a list of 20 derived geometric, sequential and structural parameters) to generate the necessary hypersurfaces. SHIFTX is rapid (< 1 CPU second for a complete shift calculation of 100 residues) and accurate. Overall, the program was able to attain a correlation coefficient (r) between observed and calculated shifts of 0.911 (¹H), 0.980 (¹³C), 0.996 (¹³C), 0.863 (¹³CO), 0.909 (¹⁵N), 0.741 (¹HN), and 0.907 (sidechain ¹H) with RMS errors of 0.23, 0.98, 1.10, 1.16, 2.43, 0.49, and 0.30 ppm, respectively on test data sets. We further show that the agreement between observed and SHIFTX calculated chemical shifts can be an extremely sensitive measure of the quality of protein structures. Our results suggest that if NMR-derived structures could be refined using heteronuclear chemical shifts calculated by SHIFTX, their precision could approach that of the highest resolution X-ray structures. SHIFTX is freely available as a web server at http://redpoll.pharmacy.ualberta.ca.     

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 .     

4D prediction of protein <Superscript>1</Superscript>H chemical shifts

A 4D approach for protein ¹H chemical shift prediction was explored. The 4th dimension is the molecular flexibility, mapped using molecular dynamics simulations. The chemical shifts were predicted with a principal component model based on atom coordinates from a database of 40 protein structures. When compared to the corresponding non-dynamic (3D) model, the 4th dimension improved prediction by 6–7%. The prediction method achieved RMS errors of 0.29 and 0.50 ppm for Hα and HN shifts, respectively. However, for individual proteins the RMS errors were 0.17–0.34 and 0.34–0.65 ppm for the Hα and HN shifts, respectively. X-ray structures gave better predictions than the corresponding NMR structures, indicating that chemical shifts contain invaluable information about local structures. The ¹H chemical shift prediction tool 4DSPOT is available from .     

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.     

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.     

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.     

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.     

Structure determination of proteins in <Superscript>2</Superscript>H<Subscript>2</Subscript>O solution aided by a deuterium-decoupled 3D HCA(N)CO experiment

We developed an NMR pulse sequence, 3D HCA(N)CO, to correlate the chemical shifts of protein backbone ¹Hα and ¹³Cα to those of ¹³C′ in the preceding residue. By applying ²H decoupling, the experiment was accomplished with high sensitivity comparable to that of HCA(CO)N. When combined with HCACO, HCAN and HCA(CO)N, the HCA(N)CO sequence allows the sequential assignment using backbone ¹³C′ and amide ¹⁵N chemical shifts without resort to backbone amide protons. This assignment strategy was demonstrated for ¹³C/¹⁵N-labeled GB1 dissolved in ²H₂O. The quality of the GB1 structure determined in ²H₂O was similar to that determined in H₂O in spite of significantly smaller number of NOE correlations. Thus this strategy enables the determination of protein structures in ²H₂O or H₂O at high pH values.     

Selectively 13C-enriched DNA: Dynamics of the C1′-H1′ vector in d(CGCAAATTTGCG)2

Summary In order to examine the internal dynamic processes of the dodecamer d(CGCAAATTTGCG)₂, the ¹³C-enriched oligonucleotide has been synthesized. The three central thymines were selectively ¹³C-labeled at the C1′ position and their spin-lattice relaxation parameters R(C_Z), R(C_X,Y), R(H_Z→C_Z), R(2H_ZC_Z), R(2H_ZC_X,Y) and R(H _infZ ^supC ) were measured. Density functions were computed for two models of internal motions. Comparisons of the experimental data were made with the spin-lattice relaxation rates rather than with the density functions, whose values were altered by accumulation of the uncertainties of each relaxation rate measurement. The spin-lattice relaxation rates were computed with respect to the motions of the sugar around the C1′-N1 bond. A two-state jump model between the anti- and syn-conformations with P(anti)/P(syn)=91/9 or a restricted rotation model with Δχ=28° and an internal diffusion coefficient of 30×10⁷ s^-1 gave a good fit with the experimental data. Twist, tilt or roll base motions have little effect on ¹³C1′ NMR relaxation. Simulation of spin-relaxation rates with the data obtained at several temperatures between 7 and 32 °C, where the dodecamer is double stranded, shows that the internal motion amplitude is independent of the temperature within this range, as expected for internal motion. Using the strong correlation which exists in a B-DNA structure between the χ and δ angle, we suggest that the change in the glycosidic angle value should be indicative of a sugar puckering between the C1′-exo and C2′-endo conformations.     

Pressure-dependent <Superscript>13</Superscript>C chemical shifts in proteins: origins and applications

Pressure-dependent ¹³C chemical shifts have been measured for aliphatic carbons in barnase and Protein G. Up to 200 MPa (2 kbar), most shift changes are linear, demonstrating pressure-independent compressibilities. CH₃, CH₂ and CH carbon shifts change on average by +0.23, −0.09 and −0.18 ppm, respectively, due to a combination of bond shortening and changes in bond angles, the latter matching one explanation for the γ-gauche effect. In addition, there is a residue-specific component, arising from both local compression and conformational change. To assess the relative magnitudes of these effects, residue-specific shift changes for protein G were converted into structural restraints and used to calculate the change in structure with pressure, using a genetic algorithm to convert shift changes into dihedral angle restraints. The results demonstrate that residual ¹³Cα shifts are dominated by dihedral angle changes and can be used to calculate structural change, whereas ¹³Cβ shifts retain significant dependence on local compression, making them less useful as structural restraints.     

Structure and dynamics of photosynthetic membrane-bound proteins in Rhodobacter Sphaeroides,studied with solid-state NMR spectroscopy

The photosynthetic purple bacteria such as Rb. sphaeroides possesses an intracytoplasmic membrane (ICM) and a variety of pigment-binding membrane proteins located in the ICM, acting as photoreceptor. Such photosynthetic apparatus is concentrated in the ICM. It is composed of three multimeric membrane-bound proteins; light-harvesting complexes (LH 1, LH 2), a reaction center (RC) and a cytochrome b/c1 complex. We have purified these membranes, which are called chromatophores, and characterized the structure and dynamics of the photosynthetic membrane-bound proteins by means of multi-nuclear solid state NMR. First, the isotropic chemical shift of carbonyl carbons in natural abundance and [1-¹³C] Phe labeled chromatophores indicates that the membrane-bound proteins take mainly the helical conformation. Second, the chemical shifts of side-chain resonances of uniformly ¹⁵N-labeled chromatophores indicate the side-chain histidine residue is mainly hydrogen bonded, whereas structural heterogeneity of arginine and lysine side-chains are probed by those wide distribution of ¹⁵N shifts. Thirdly, the [β-²H₃]Ala and [ε-²H₂]Tyr labeling of the chromatophores are performed and dynamics of the [β-²H]Ala and the [ε-²H₂]Tyr labeled chromatophores are studied by means of ²H solid state NMR. The dynamics of [β-²H₃]Ala is found to be a 10⁸Hz three-site jump motion with 10° liberation along the Cα-Cβ bond axis. The ²H-NMR powder pattern spectrum of [ε-²H₂] Tyr labeled chromatophores was interpreted with an averaged correlation time of 5×10⁵ Hz with 180° two-fold flips, the result of the averaging of two kinds of split spectra in terms of motional time scale. This revised version was published online in June 2006 with corrections to the Cover Date.     

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.     

Chemical shift correlation at high MAS frequencies employing low-power symmetry-based mixing schemes

An approach for conveniently implementing low-power CN _n ^ν and RN _n ^ν symmetry-based band-selective mixing sequences for generating homo- and heteronuclear chemical shift correlation NMR spectra of low γ nuclei in biological solids is demonstrated. Efficient magnetisation transfer characteristics are achieved by selecting appropriate symmetries requiring the application of basic RF elements of relatively long duration and numerically tailoring the RF field modulation profile of the basic element. The efficacy of the approach is experimentally shown by the acquisition of ¹⁵N–¹³C dipolar and ¹³C–¹³C scalar and dipolar coupling mediated chemical shift correlation spectra at representative MAS frequencies.     

Probabilistic Approach to Determining Unbiased Random-coil Carbon-13 Chemical Shift Values from the Protein Chemical Shift Database

We describe a probabilistic model for deriving, from the database of assigned chemical shifts, a set of random coil chemical shift values that are “unbiased” insofar as contributions from detectable secondary structure have been minimized (RCCS_u). We have used this approach to derive a set of RCCS_u values for ¹³C^α and ¹³C^β for 17 of the 20 standard amino acid residue types by taking advantage of the known opposite conformational dependence of these parameters. We present a second probabilistic approach that utilizes the maximum entropy principle to analyze the database of ¹³C^α and ¹³C^β chemical shifts considered separately; this approach yielded a second set of random coil chemical shifts (RCCS). Both new approaches analyze the chemical shift database without reference to known structure. Prior approaches have used either the chemical shifts of small peptides assumed to model the random coil state (RCCS_peptide) or statistical analysis of chemical shifts associated with structure not in helical or strand conformation (RCCS). We show that the RCCS values are strikingly similar to published RCCS_peptide and RCCS values. By contrast, the RCCS_u values differ significantly from both published types of random coil chemical shift values. The differences (RCCS_peptide−RCCS_u) for individual residue types show a correlation with known intrinsic conformational propensities. These results suggest that random coil chemical shift values from both prior approaches are biased by conformational preferences. RCCS_u values appear to be consistent with the current concept of the “random coil” as the state in which the geometry of the polypeptide ensemble samples the allowed region of (ϕ,ψ)-space in the absence of any dominant stabilizing interactions and thus represent an improved basis for the detection of secondary structure. Coupled with the growing database of chemical shifts, this probabilistic approach makes it possible to refine relationships among chemical shifts, their conformational propensities, and their dependence on pH, temperature, or neighboring residue type.Electronic Supplementary Material Supplementary material is available to authorised users in the online version of this article at .     

A procedure to validate and correct the 13C chemical shift calibration of RNA datasets

Chemical shifts reflect the structural environment of a certain nucleus and can be used to extract structural and dynamic information. Proper calibration is indispensable to extract such information from chemical shifts. Whereas a variety of procedures exist to verify the chemical shift calibration for proteins, no such procedure is available for RNAs to date. We present here a procedure to analyze and correct the calibration of ¹³C NMR data of RNAs. Our procedure uses five ¹³C chemical shifts as a reference, each of them found in a narrow shift range in most datasets deposited in the Biological Magnetic Resonance Bank. In 49 datasets we could evaluate the ¹³C calibration and detect errors or inconsistencies in RNA ¹³C chemical shifts based on these chemical shift reference values. More than half of the datasets (27 out of those 49) were found to be improperly referenced or contained inconsistencies. This large inconsistency rate possibly explains that no clear structure–¹³C chemical shift relationship has emerged for RNA so far. We were able to recalibrate or correct 17 datasets resulting in 39 usable ¹³C datasets. 6 new datasets from our lab were used to verify our method increasing the database to 45 usable datasets. We can now search for structure–chemical shift relationships with this improved list of ¹³C chemical shift data. This is demonstrated by a clear relationship between ribose ¹³C shifts and the sugar pucker, which can be used to predict a C2′- or C3′-endo conformation of the ribose with high accuracy. The improved quality of the chemical shift data allows statistical analysis with the potential to facilitate assignment procedures, and the extraction of restraints for structure calculations of RNA.     

RefDB: a database of uniformly referenced protein chemical shifts

RefDB is a secondary database of reference-corrected protein chemical shifts derived from the BioMagResBank (BMRB). The database was assembled by using a recently developed program (SHIFTX) to predict protein ¹H, ¹³C and ¹⁵N chemical shifts from X-ray or NMR coordinate data of previously assigned proteins. The predicted shifts were then compared with the corresponding observed shifts and a variety of statistical evaluations performed. In this way, potential mis-assignments, typographical errors and chemical referencing errors could be identified and, in many cases, corrected. This approach allows for an unbiased, instrument-independent solution to the problem of retrospectively re-referencing published protein chemical shifts. Results from this study indicate that nearly 25% of BMRB entries with ¹³C protein assignments and 27% of BMRB entries with ¹⁵N protein assignments required significant chemical shift reference readjustments. Additionally, nearly 40% of protein entries deposited in the BioMagResBank appear to have at least one assignment error. From this study it evident that protein NMR spectroscopists are increasingly adhering to recommended IUPAC ¹³C and ¹⁵N chemical shift referencing conventions, however, approximately 20% of newly deposited protein entries in the BMRB are still being incorrectly referenced. This is cause for some concern. However, the utilization of RefDB and its companion programs may help mitigate this ongoing problem. RefDB is updated weekly and the database, along with its associated software, is freely available at http://redpoll.pharmacy.ualberta.ca and the BMRB website.     

Conformational dependence of <Superscript>13</Superscript>C shielding and coupling constants for methionine methyl groups

Methionine residues fulfill a broad range of roles in protein function related to conformational plasticity, ligand binding, and sensing/mediating the effects of oxidative stress. A high degree of internal mobility, intrinsic detection sensitivity of the methyl group, and low copy number have made methionine labeling a popular approach for NMR investigation of selectively labeled protein macromolecules. However, selective labeling approaches are subject to more limited information content. In order to optimize the information available from such studies, we have performed DFT calculations on model systems to evaluate the conformational dependence of ³ J _CSCC, ³ J _CSCH, and the isotropic shielding, σ_iso. Results have been compared with experimental data reported in the literature, as well as data obtained on [methyl-¹³C]methionine and on model compounds. These studies indicate that relative to oxygen, the presence of the sulfur atom in the coupling pathway results in a significantly smaller coupling constant, ³ J _CSCC/³ J _COCC ~ 0.7. It is further demonstrated that the ³ J _CSCH coupling constant depends primarily on the subtended CSCH dihedral angle, and secondarily on the CSCC dihedral angle. Comparison of theoretical shielding calculations with the experimental shift range of the methyl group for methionine residues in proteins supports the conclusion that the intra-residue conformationally-dependent shift perturbation is the dominant determinant of δ¹³Cε. Analysis of calmodulin data based on these calculations indicates that several residues adopt non-standard rotamers characterized by very large ~100° χ³ values. The utility of the δ¹³Cε as a basis for estimating the gauche/trans ratio for χ³ is evaluated, and physical and technical factors that limit the accuracy of both the NMR and crystallographic analyses are discussed.     

13C–13C NOESY spectra of a 480 kDa protein: solution NMR of ferritin

Molecular size has limited solution NMR analyses of proteins. We report ¹³C–¹³C NOESY experiments on a 480 kDa protein, the multi-subunit ferritin nanocage with gated pores. By exploiting ¹³C-resonance-specific chemical shifts and spin diffusion effects, we identified 75% of the amino acids, with intraresidue C–C connectivities between nuclei separated by 1–4 bonds. These results show the potential of ¹³C–¹³C NOESY for solution studies of molecular assemblies >100 kDa.     

Refinement of protein structure against non-redundant carbonyl <Superscript>13</Superscript>C NMR relaxation

Carbonyl ¹³C′ relaxation is dominated by the contribution from the ¹³C′ chemical shift anisotropy (CSA). The relaxation rates provide useful and non-redundant structural information in addition to dynamic parameters. It is straightforward to acquire, and offers complimentary structural information to the ¹⁵N relaxation data. Furthermore, the non-axial nature of the ¹³C′ CSA tensor results in a T₁/T₂ value that depends on an additional angular variable even when the diffusion tensor of the protein molecule is axially symmetric. This dependence on an extra degree of freedom provides new geometrical information that is not available from the NH dipolar relaxation. A protocol that incorporates such structural restraints into NMR structure calculation was developed within the program Xplor-NIH. Its application was illustrated with the yeast Fis1 NMR structure. Refinement against the ¹³C′ T₁/T₂ improved the overall quality of the structure, as evaluated by cross-validation against the residual dipolar coupling as well as the ¹⁵N relaxation data. In addition, possible variations of the CSA tensor were addressed. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.