Prediction of fluorine chemical shifts in proteins

Molecular dynamics calculations have been used in an effort to estimate the change in fluorine nmr shielding when a fluorine nucleus enters the tertiary structure of a protein. Considerations of the possible interactions that can define the shift parameter change suggest that van der Waals interactions are the leading determinant of fluorine shifts in proteins, although aromatic ring currents, other magnetic anisotropies, and electrostatic field effects could result in shift distinctions of 1 ppm or smaller. Results of our studies of a fluorine-containing analogue of the ribonuclease A S-protein/S-peptide complex indicate that static structures such as those implied by crystallographic data lead to overestimates of the magnitude of the van der Waals shielding term; molecular dynamics simulations provide indications of the effects of conformational averaging in defining this term. The treatment used predicts the correct direction of the shift change when the fluorine enters this protein environment from aqueous solution and, with an experimentally supported choice of adjustable parameters, gives agreement with the magnitude of the shift.     

NMR chemical shifts and structure refinement in proteins

Summary Computation of the ¹³C chemical shifts (or shieldings) of glycine, alanine and valine residues in bovine and Drosophila calmodulins and Staphylococcal nuclease, and comparison with experimental values, is reported using a gauge-including atomic orbital quantum-chemical approach. The full 24 ppm shielding range is reproduced (overall r.m.s.d.=1.4 ppm) using optimized protein structures, corrected for bond-length/bond-angle errors, and rovibrational effects.To whom correspondence should be addressed.     

Structure-based prediction of methyl chemical shifts in proteins

Protein methyl groups have recently been the subject of much attention in NMR spectroscopy because of the opportunities that they provide to obtain information about the structure and dynamics of proteins and protein complexes. With the advent of selective labeling schemes, methyl groups are particularly interesting in the context of chemical shift based protein structure determination, an approach that to date has exploited primarily the mapping between protein structures and backbone chemical shifts. In order to extend the scope of chemical shifts for structure determination, we present here the CH3Shift method of performing structure-based predictions of methyl chemical shifts. The terms considered in the predictions take account of ring current, magnetic anisotropy, electric field, rotameric type, and dihedral angle effects, which are considered in conjunction with polynomial functions of interatomic distances. We show that the CH3Shift method achieves an accuracy in the predictions that ranges from 0.133 to 0.198 ppm for ¹H chemical shifts for Ala, Thr, Val, Leu and Ile methyl groups. We illustrate the use of the method by assessing the accuracy of side-chain structures in structural ensembles representing the dynamics of proteins.     

Temperature dependence of 1H chemical shifts in proteins

Temperature coefficients have been measured by 2D NMR methods forthe amide and CH proton chemical shifts in two globularproteins, bovine pancreatic trypsin inhibitor and hen egg-white lysozyme.The temperature-dependent changes in chemical shift are generally linear upto about 15° below the global denaturation temperature, and the derivedcoefficients span a range of roughly –16 to +2 ppb/K for amide protonsand –4 to +3 ppb/K for CH. The temperaturecoefficients can be rationalized by the assumption that heating causesincreases in thermal motion in the protein. Precise calculations oftemperature coefficients derived from protein coordinates are not possible,since chemical shifts are sensitive to small changes in atomic coordinates.Amide temperature coefficients correlate well with the location of hydrogenbonds as determined by crystallography. It is concluded that a combined useof both temperature coefficients and exchange rates produces a far morereliable indicator of hydrogen bonding than either alone. If an amide protonexchanges slowly and has a temperature coefficient more positive than–4.5 ppb/K, it is hydrogen bonded, while if it exchanges rapidly andhas a temperature coefficient more negative than –4.5 ppb/K, it is nothydrogen bonded. The previously observed unreliability of temperaturecoefficients as measures of hydrogen bonding in peptides may arise fromlosses of peptide secondary structure on heating.     

Secondary-structure analysis of proteins by vacuum-ultraviolet circular dichroism spectroscopy

The vacuum ultraviolet circular dichroism (VUVCD) spectra of 15 globular proteins (myoglobin, hemoglobin, human serum albumin, cytochrome c, peroxidase, alpha-lactalbumin, lysozyme, ovalbumin, ribonuclease A, beta-lactoglobulin, pepsin, trypsinogen, alpha-chymotrypsinogen, soybean trypsin inhibitor, and concanavalin A) were measured in aqueous solutions at 25 degrees C in the wavelength region from 260 to 160 nm under a high vacuum, using a synchrotron-radiation VUVCD spectrophotometer. The VUVCD spectra below 190 nm revealed some characteristic bands corresponding to different secondary structures. The contents of alpha-helices, beta-strands, turns, and unordered structures were estimated using the SELCON3 program with VUVCD spectra data on the 15 proteins. Prediction of the secondary-structure contents was greatly improved by extending the circular dichroism spectra to 165 nm. The numbers of alpha-helix and beta-strand segments calculated from the distorted alpha-helix and beta-strand contents did not differ greatly from those obtained from X-ray crystal structures. These results demonstrate that synchrotron-radiation VUVCD spectroscopy is a powerful tool for analyzing the secondary structures of proteins.     

Secondary-structure analysis of denatured proteins by vacuum-ultraviolet circular dichroism spectroscopy

To elucidate the structure of denatured proteins, we measured the vacuum-ultraviolet circular dichroism (VUVCD) spectra from 260 to 172 nm of three proteins (metmyoglobin, staphylococcal nuclease, and thioredoxin) in the native and the acid-, cold-, and heat-denatured states, using a synchrotron-radiation VUVCD spectrophotometer. The circular dichroism spectra of proteins fully unfolded by guanidine hydrochloride (GdnHCl) were also measured down to 197 nm for comparison. These denatured proteins exhibited characteristic VUVCD spectra that reflected a considerable amount of residual secondary structures. The contents of alpha-helices, beta-strands, turns, poly-L-proline type II (PPII), and unordered structures were estimated for each denatured state of the three proteins using the SELCON3 program with Protein Data Bank data and the VUVCD spectra of 31 reference proteins reported in our previous study. Based on these contents, the characteristics of the four types of denaturation were discussed for each protein. In all types of denaturation, a decrease in alpha-helices was accompanied by increases in beta-strands, PPII, and unordered structures. About 20% beta-strands were present even in the proteins fully unfolded by GdnHCl in which beta-sheets should be broken. From these results, we propose that denatured proteins constitute an ensemble of residual alpha-helices and beta-sheets, partly unfolded (or distorted) alpha-helices and beta-strands, PPII, and unordered structures.     

A new model for chemical shifts of amide hydrogens in proteins

We propose a new computational model to predict amide proton chemical shifts in proteins. In addition to the ring-current, susceptibility and electrostatic effects of earlier models, we add a hydrogen-bonding term based on density functional calculations of model peptide–peptide and peptide–water systems. Both distance and angular terms are included, and the results are rationalized in terms of natural bond orbital analysis of the interactions. Comparison to observed shifts for 15 proteins shows a significant improvement over existing structure-shift correlations. These additions are incorporated in a new version of the SHIFTS program.     

Fluorine chemical shifts in complexes of sodium trifluoralkylsulfates with reduced proteins

Equilibrium dialysis experiments were carried out for several proteins, reduced with dithioerythritol, in aqueous buffer and the anionic surfactants, sodium 12,12,12-trifluorododecylsulfate or sodium 13,13,13-triflourotridecylsulfate, with surfactant concentrations above the critical micelle concentration. Fluorine chemical shifts were determined for each retentate and dialysate solution. The results show that most of the proteins bind 3.2 ± 0.4 millimoles of fluorinates surfactant per gram. In every case the chemical shift of the bound detergent ions is very near that found for micelles, suggesting that the bound ions form micelle-like aggregates.     

Analysis of proton chemical shifts in regular secondary structure of proteins

Summary The contribution of peptide groups to H and H proton chemical shifts can be modeled with empirical equations that represent magnetic anisotropy and electrostatic interactions [Ösapay, K. and Case, D.A. (1991) J. Am. Chem. Soc., 113, 9436–9444]. Using these, a model for the random coil reference state can be generated by averaging a dipeptide over energetically allowed regions of torsion-angle space. Such calculations support the notion that the empirical constant used in earlier studies arises from neighboring peptide contributions in the reference state, and suggest that special values be used for glycine and proline residues, which differ significantly from other residues in their allowed ,-ranges. New constants for these residues are reported that provide significant improvements in predicted backbone shifts. To illustrate how secondary structure affects backbone chemical shifts we report calculations on oligopeptide models for helices, sheets and turns. In addition to suggesting a physical mechanism for the widely recognized average difference between and secondary structures, these models suggest several additional regularities that should be expected: (a) H protons at the edges of -sheets will have a two-residue periodicity; (b) the H² and H³ protons of glycine residues will exhibit different shifts, particularly in sheets; (c) H protons will also be sensitive to local secondary structure, but in different directions and to a smaller extent than H protons; (d) H protons in turns will generally be shifted upfield, except those in position 3 of type I turns. Examples of observed shift patterns in several proteins illustrate the application of these ideas.     

Secondary-structure analysis of alcohol-denatured proteins by vacuum-ultraviolet circular dichroism spectroscopy

To elucidate the structural characteristics of alcohol-denatured proteins, we measured the vacuum-ultraviolet circular dichroism (VUVCD) spectra of six proteins-myoglobin, human serum albumin, α-lactalbumin, thioredoxin, β-lactoglobulin, and α-chymotrypsinogen A-down to 170 nm in trifluoroethanol solutions (TFE: 0-50%) and down to 175 nm in methanol solutions (MeOH: 0-70%) at pH 2.0 and 25°C, using a synchrotron-radiation VUVCD spectrophotometer. The contents of α-helices, β-strands, turns, poly-L-proline type II helices (PPIIs), and unordered structures of these proteins were estimated using the SELCON3 program, including the numbers of α-helix and β-strand segments. Furthermore, the positions of α-helices and β-strands on amino acid sequences were predicted by combining these secondary-structure data with a neural-network method. All alcohol-denatured proteins showed higher α-helix contents (up to ~ 90%) compared with the native states, and they consisted of several long helical segments. The helix-forming ability was higher in TFE than in MeOH, whereas small amounts of β-strands without sheets were formed in the MeOH solution. The produced α-helices were transformed dominantly from the β-strands and unordered structures, and slightly from the turns. The content and mean length of α-helix segments decreased as the number of disulfide bonds in the proteins increased, suggesting that disulfide bonds suppress helix formation by alcohols. These results demonstrate that alcohol-denatured proteins constitute an ensemble of many long α-helices, a few β-strands and PPIIs, turns, and unordered structures, depending on the types of proteins and alcohols involved.     

Toward the quantum chemical calculation of nuclear magnetic resonance chemical shifts of proteins

Despite the many protein structures solved successfully by nuclear magnetic resonance (NMR) spectroscopy, quality control of NMR structures is still by far not as well established and standardized as in crystallography. Therefore, there is still the need for new, independent, and unbiased evaluation tools to identify problematic parts and in the best case also to give guidelines that how to fix them. We present here, quantum chemical calculations of NMR chemical shifts for many proteins based on our fragment-based quantum chemical method: the adjustable density matrix assembler (ADMA). These results show that (13)C chemical shifts of reasonable accuracy can be obtained that can already provide a powerful measure for the structure validation. (1)H and even more (15)N chemical shifts deviate more strongly from experiment due to the insufficient treatment of solvent effects and conformational averaging.     

Nearest-neighbor effects on backbone alpha and beta carbon chemical shifts in proteins

We present a method for analyzing the chemical shift database to yield information on nearest-neighbor effects on carbon-13 chemical shift values for alpha and beta carbons of amino acids in proteins. For each amino acid sequence XYZ, we define two correction factors, Delta(XY) s and Delta(YZ) s , representing the effects on (delta13 Calpha-delta13 Cbeta) for residue Y from the preceding residue (X) and the following residue (Z), where X, Y, and Z represent one of the 20 naturally occurring amino acids, Delta designates the change in value or the correction factor (in ppm), and s is an index standing for one of three "pseudo secondary structure states" derived from chemical shift dispersions, which we show represent residues in primarily alpha-helix, beta-strand, and non-alphabeta(coil). The correction factors were obtained from maximum likelihood fitting of (delta13 Calpha-delta13 Cbeta) values from the chemical shifts of 651 proteins to a mixture of three Gaussians. These correction factors were derived strictly from the analysis of assigned chemical shifts, without regard to the three-dimensional structures of these proteins. The corrections factors were found to differ according to the secondary structural environment of the central residue (deduced from the chemical shift distribution) as well as by different identities of the nearest neighboring residues in the sequence. The areas subsumed by the sequence-dependent chemical shift distributions report on the relative energies of the sequences in different pseudo secondary structural environments, and the positions of the peaks indicate the chemical shifts of lowest energy conformations. As such, these results have potential applications to the determination of dihedral angle restraints from chemical shifts for structure determination and to more accurate predictions of chemical shifts in proteins of known structure. From a database of chemical shifts associated well-defined three-dimensional structures, comparisons were made between DSSP designations derived from three-dimensional structure and pseudo secondary structure designations derived from nearest-neighbor corrected chemical shift analysis. The high level of agreement between the two approaches to classifying secondary structure provides a measure of confidence in this chemical shift-based approach to the analysis of protein structure.     

Correlation between 15N NMR chemical shifts in proteins and secondary structure

Summary An empirical correlation between the peptide ¹⁵N chemical shift, ¹⁵N_i, and the backbone torsion angles _i, _i–1 is reported. By using two-dimensional shielding surfaces (_i1–1), it is possible in many cases to make reasonably accurate predictions of ¹⁵N chemical shifts for a given structure. On average, the rms error between experiment and prediction is about 3.5 ppm. Results for threonine, valine and isoleucine are worse (4.8 ppm), due presumably to ₁-distribution/-gauche effects. The rms errors for the other amino acids are 3 ppm, for a typical maximal chemical shift range of 15–20 ppm. Thus, there is a significant correlation between ¹⁵N chemical shift and secondary structure.     

An evaluation of chemical shift index-based secondary structure determination in proteins: Influence of random coil chemical shifts

Random coil chemical shifts are commonly used to detect protein secondary structural elements in chemical shift index (CSI) calculations. Though this technique is widely used and seems reliable for folded proteins, the choice of reference random coil chemical shift values can significantly alter the outcome of secondary structure estimation. In order to evaluate these effects, we present a comparison of secondary structure content calculated using CSI, based on five different reference random coil chemical shift value sets, to that derived from three-dimensional structures.Our results show that none of the reference random coil data sets chosen for evaluation fully reproduces the actual secondary structures. Among the reference values generally available to date, most tend to be good estimators only of helices. Based on our evaluation, we recommend the experimental values measured by Schwarzinger et al.(2000), and statistical values obtained by Lukin et al. (1997), as good estimators of both helical and sheet content.     

Heme methyl 1H chemical shifts as structural parameters in some low-spin ferriheme proteins

 The different paramagnetic shifts of the four methyl groups in ferriheme proteins have been described as being due to the effect of the axial ligand nodal plane orientation. An equation, heuristically found and theoretically explained, describing the relation between contact and pseudocontact shifts and the position of the axial ligand(s) has been derived for bis-histidine ferriheme proteins and for cyanide-histidine ferriheme proteins. The values of the heuristic parameters contained in the equations were found by fitting the shifts of bovine cytochrome b ₅ and several bis-histidine cytochromes c ₃ and histidine-cyanide systems. The agreement between the observed and the calculated shifts was found to be good. Therefore, by taking advantage of this study, information on the position of the axial ligands, that can be used as a constraint for structure determination, can be obtained from the shifts of the methyl protons. Received: 13 April 1999 / Accepted: 4 June 1999     

Proton chemical shifts in fluorocinnamate-chymotrypsin complexes

Binding of cinnamate or fluorocinnamate anions to α-chymotrypsin is accompanied by chemical shift changes at each proton of the cinnamate structure. The direction and magnitude of these shifts are consistent with the expected binding of these inhibitors at the active site of the enzyme. The protein-induced fluorine chemical shift effects at each position in the aromatic ring are compared to the shift effects observed when a hydrogen occupies the same position. There is no discernible relation between the proton and fluorine chemical shifts, leading to the conclusion that those factors dominantly responsible for the shift effects are different for the two sets of data.     

C alpha and C beta carbon-13 chemical shifts in proteins from an empirical database

We have constructed an extensive database of 13C C and C chemical shifts in proteins of solution, for proteins of which a high-resolution crystal structure exists, and for which the crystal structure has been shown to be essentially identical to the solution structure. There is no systematic effect of temperature, reference compound, or pH on reported shifts, but there appear to be differences in reported shifts arising from referencing differences of up to 4.2 ppm. The major factor affecting chemical shifts is the backbone geometry, which causes differences of ca. 4 ppm between typical - helix and -sheet geometries for C, and of ca. 2 ppm for C. The side-chain dihedral angle 1 has an effect of up to 0.5 ppm on the C shift, particularly for amino acids with branched side-chains at C. Hydrogen bonding to main-chain atoms has an effect of up to 0.9 ppm, which depends on the main- chain conformation. The sequence of the protein and ring-current shifts from aromatic rings have an insignificant effect (except for residues following proline). There are significant differences between different amino acid types in the backbone geometry dependence; the amino acids can be grouped together into five different groups with different , shielding surfaces. The overall fit of individual residues to a single non-residue-specific surface, incorporating the effects of hydrogen bonding and 1 angle, is 0.96 ppm for both C and C. The results from this study are broadly similar to those from ab initio studies, but there are some differences which could merit further attention.     

POTENCI: prediction of temperature,neighbor and pH-corrected chemical shifts for intrinsically disordered proteins

Chemical shifts contain important site-specific information on the structure and dynamics of proteins. Deviations from statistical average values, known as random coil chemical shifts (RCCSs), are extensively used to infer these relationships. Unfortunately, the use of imprecise reference RCCSs leads to biased inference and obstructs the detection of subtle structural features. Here we present a new method, POTENCI, for the prediction of RCCSs that outperforms the currently most authoritative methods. POTENCI is parametrized using a large curated database of chemical shifts for protein segments with validated disorder; It takes pH and temperature explicitly into account, and includes sequence-dependent nearest and next-nearest neighbor corrections as well as second-order corrections. RCCS predictions with POTENCI show root-mean-square values that are lower by 25–78%, with the largest improvements observed for ¹Hα and ¹³C′. It is demonstrated how POTENCI can be applied to analyze subtle deviations from RCCSs to detect small populations of residual structure in intrinsically disorder proteins that were not discernible before. POTENCI source code is available for download, or can be deployed from the URL http://www.protein-nmr.org.