Backbone structure confirmation and side chain conformation refinement of a bradykinin mimic BKM-824 by comparing calculated (1)H, (13)C and (19)F chemical shifts with experiment

Calculated and experimental (1)H, (13)C and (19)F chemical shifts were compared in BKM-824, a cyclic bradykinin antagonist mimic, c[Ava(1)-Igl(2)-Ser(3)-DF5F(4)-Oic(5)-Arg(6)] (Ava=5-aminovaleric acid, Igl=alpha-(2-indanyl)glycine, DF5F=pentafluorophenylalanine, Oic=(2S,3aS,7aS)-octahydroindole-2-carboxylic acid). The conformation of BKM-824 has been studied earlier by NMR spectroscopy (M. Miskolzie et al., J. Biomolec. Struct. Dyn. 17, 947-955 (2000)). All NMR structures have qualitatively the same backbone structure but there is considerable variation in the side chain conformations. We have carried out quantum mechanical optimization for three representative NMR structures at the B3LYP/6-31G* level, constraining the backbone dihedral angles at their NMR structure values, followed by NMR chemical shift calculations at the optimized structures with the 6-311G** basis set. There is an intramolecular hydrogen bond at Ser(3) in the optimized structures. The experimental (13)C chemical shifts at five C(alpha) positions as well as at the Cbeta, Cgamma and Cdelta position of Ava(1), which forms part of the backbone, are well reproduced by the calculations, confirming the NMR backbone structure. A comparison between the calculated and experimental H(beta) chemical shifts in Igl(2) shows that the dominant conformation at this residue is gauche. Changes of proton chemical shifts with the scan of the chi(1) angle in DF5F(4) suggest that chi(1)180 degrees. The calculated (1)H and (13)C chemical shifts are in good agreement with experiment at the rigid residue Oic(5). None of the models gives accurate results for Arg(6), presumably because of its positive charge. Our study indicates that calculated NMR shifts can be used as additional constraints in conjunction with NMR data to determine protein conformations. However, to be computationally effective, a database of chemical shifts in small peptide fragments should be precalculated.     

An NMR Conformational Analysis of Cyclic Bradykinin Mimics. Evidence for a β-Turn

Abstract

A detailed NMR study is carried out in acetonitrile/water solutions on three novel cyclic bradykinin antagonist analogues, BKM-824, BKM-870, and BKM-872, to examine their solution structures, and to correlate the structures with bradykinin antagonist and anti-cancer activities. The solution structures of the cyclic peptides are correlated with the structural data for known linear bradykinin antagonists. The sequences are: BKM-824 c[Ava-Igl-Ser-DF5F-Oic- Arg] where Ava is 5-aminovaleric acid, Igl is α-(2-indanyl)glycine, F5F is pentafluorophenylalanine, and Oic is (2S,3aS,7aS)-octahydroindole-2-carboxylic acid; BKM-870; c[DArg-Arg-Add-DF5F-Oic-Arg] where Add is 12-aminododecanoic acid; and BKM-872; c[DArg-Arg-Eac-Ser-DF5F-Oic-Arg] where Eac is 6-aminocaproic acid. BKM-824 was the only peptide within this series that possessed a discernable solution structure. The NMR data indicate the presence of a type I β-turn between residues F5F⁴ and Ava¹, a C-terminal-like end. Molecular dynamics calculations show that a type I β-turn from DF5F⁴ to Ava¹ does exist although the turn was somewhat distorted. This result differs from the structures seen in linear bradykinin antagonists, which usually possess a type II II′β-turn at the C-terminal end and the presence of a defined turn is correlated with bradykinin antagonist activity. There is no solution structure for BKM-870 and BKM-872 but a correlation between the primary sequence Arg^terminal-DArg¹-Arg²-long chain aliphatic amino acid and anti-cancer activity is evident.     

An NMR conformational analysis of cyclic bradykinin mimics. Evidence for a beta-turn

A detailed NMR study is carried out in acetonitrile/water solutions on three novel cyclic bradykinin antagonist analogues, BKM-824, BKM-870, and BKM-872, to examine their solution structures, and to correlate the structures with bradykinin antagonist and anti-cancer activities. The solution structures of the cyclic peptides are correlated with the structural data for known linear bradykinin antagonists. The sequences are: BKM-824 c[Ava-Ig1-Ser-DF5F-Oic-Arg] where Ava is 5-aminovaleric acid, Ig1 is alpha-(2-indanyl)glycine, F5F is pentafluorophenylalanine, and Oic is (2S,3aS,7aS)-octahydroindole-2-carboxylic acid; BKM-870; c[DArg-Arg-Add-DF5F-Oic-Arg] where Add is 12-aminododecanoic acid; and BKM-872; c[DArg-Arg-Eac-Ser-DF5F-Oic-Arg] where Eac is 6-aminocaproic acid. BKM-824 was the only peptide within this series that possessed a discernable solution structure. The NMR data indicate the presence of a type I beta-turn between residues F5F4 and Ava1, a C-terminal-like end. Molecular dynamics calculations show that a type I beta-turn from DF5F4 to Ava1 does exist although the turn was somewhat distorted. This result differs from the structures seen in linear bradykinin antagonists, which usually possess a type II'beta-turn at the C-terminal end and the presence of a defined turn is correlated with bradykinin antagonist activity. There is no solution structure for BKM-870 and BKM-872 but a correlation between the primary sequence Arg(terminal)-DArg1-Arg2-long chain aliphatic amino acid and anti-cancer activity is evident.     

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.     

Hash: a program to accurately predict protein Hα shifts from neighboring backbone shifts

Chemical shifts provide not only peak identities for analyzing nuclear magnetic resonance (NMR) data, but also an important source of conformational information for studying protein structures. Current structural studies requiring H^α chemical shifts suffer from the following limitations. (1) For large proteins, the H^α chemical shifts can be difficult to assign using conventional NMR triple-resonance experiments, mainly due to the fast transverse relaxation rate of C^α that restricts the signal sensitivity. (2) Previous chemical shift prediction approaches either require homologous models with high sequence similarity or rely heavily on accurate backbone and side-chain structural coordinates. When neither sequence homologues nor structural coordinates are available, we must resort to other information to predict H^α chemical shifts. Predicting accurate H^α chemical shifts using other obtainable information, such as the chemical shifts of nearby backbone atoms (i.e., adjacent atoms in the sequence), can remedy the above dilemmas, and hence advance NMR-based structural studies of proteins. By specifically exploiting the dependencies on chemical shifts of nearby backbone atoms, we propose a novel machine learning algorithm, called Hash, to predict H^α chemical shifts. Hash combines a new fragment-based chemical shift search approach with a non-parametric regression model, called the generalized additive model, to effectively solve the prediction problem. We demonstrate that the chemical shifts of nearby backbone atoms provide a reliable source of information for predicting accurate H^α chemical shifts. Our testing results on different possible combinations of input data indicate that Hash has a wide rage of potential NMR applications in structural and biological studies of proteins.     

Relationship between1H and13C NMR chemical shifts and the secondary and tertiary structure of a zinc finger peptide

Summary Essentially complete assignments have been obtained for the¹H and protonated¹³C NMR spectra of the zinc finger peptide Xfin-31 in the presence and absence of zinc. The patterns observed for the¹H and¹³C chemical shifts of the peptide in the presence of zinc, relative to the shifts in the absence of zinc, reflect the zinc-mediated folding of the unstructured peptide into a compact globular structure with distinct elements of secondary structure. Chemical shifts calculated from the 3D solution structure of the peptide in the presence of zinc and the observed shifts agree to within ca. 0.2 and 0.6 ppm for the backbone C^aH and NH protons, respectively. In addition, homologous zinc finger proteins exhibit similar correlations between their¹H chemical shifts and secondary structure.     

Accurate measurements of the effects of deuteration at backbone amide positions on the chemical shifts of 15N, 13Cα, 13Cβ, 13CO and 1Hα nuclei in proteins

An approach towards accurate NMR measurements of deuterium isotope effects on the chemical shifts of all backbone nuclei in proteins (¹⁵N, ¹³C_α, ¹³CO, ¹H_α) and ¹³C_β nuclei arising from ¹H-to-D substitutions at amide nitrogen positions is described. Isolation of molecular species with a defined protonation/deuteration pattern at successive backbone nitrogen positions in the polypeptide chain allows quantifying all deuterium isotope shifts of these nuclei from the first to the fourth order. Some of the deuterium isotope shifts measured in the proteins ubiquitin and GB1 can be interpreted in terms of backbone geometry via empirical relationships describing their dependence on (φ; ψ) backbone dihedral angles. Because of their relatively large variability and notable dependence on the protein secondary structure, the two- and three-bond ¹³C_α isotope shifts, ²ΔC_α(N_iD) and ³ΔC_α(N_i+1D), and three-bond ¹³C_β isotope shifts, ³ΔC_β(N_iD), are useful reporters of the local geometry of the protein backbone.     

Protein backbone and sidechain torsion angles predicted from NMR chemical shifts using artificial neural networks

A new program, TALOS-N, is introduced for predicting protein backbone torsion angles from NMR chemical shifts. The program relies far more extensively on the use of trained artificial neural networks than its predecessor, TALOS+. Validation on an independent set of proteins indicates that backbone torsion angles can be predicted for a larger, ≥90 % fraction of the residues, with an error rate smaller than ca 3.5 %, using an acceptance criterion that is nearly two-fold tighter than that used previously, and a root mean square difference between predicted and crystallographically observed (?, ψ) torsion angles of ca 12º. TALOS-N also reports sidechain χ¹ rotameric states for about 50 % of the residues, and a consistency with reference structures of 89 %. The program includes a neural network trained to identify secondary structure from residue sequence and chemical shifts.     

A NMR experiment for simultaneous correlations of valine and leucine/isoleucine methyls with carbonyl chemical shifts in proteins

A methyl-detected ‘out-and-back’ NMR experiment for obtaining simultaneous correlations of methyl resonances of valine and isoleucine/leucine residues with backbone carbonyl chemical shifts, SIM-HMCM(CGCBCA)CO, is described. The developed pulse-scheme serves the purpose of convenience in recording a single data set for all Ile^δ1, Leu^δ and Val^γ (ILV) methyl positions instead of acquiring two separate spectra selective for valine or leucine/isoleucine residues. The SIM-HMCM(CGCBCA)CO experiment can be used for ILV methyl assignments in moderately sized protein systems (up to ~100 kDa) where the backbone chemical shifts of ¹³C^α, ¹³C_β and ¹³CO are known from prior NMR studies and where some losses in sensitivity can be tolerated for the sake of an overall reduction in NMR acquisition time.     

Prediction of Xaa-Pro peptide bond conformation from sequence and chemical shifts

We present a program, named Promega, to predict the Xaa-Pro peptide bond conformation on the basis of backbone chemical shifts and the amino acid sequence. Using a chemical shift database of proteins of known structure together with the PDB-extracted amino acid preference of cis Xaa-Pro peptide bonds, a cis/trans probability score is calculated from the backbone and ¹³C^β chemical shifts of the proline and its neighboring residues. For an arbitrary number of input chemical shifts, which may include Pro-¹³C^γ, Promega calculates the statistical probability that a Xaa-Pro peptide bond is cis. Besides its potential as a validation tool, Promega is particularly useful for studies of larger proteins where Pro-¹³C^γ assignments can be challenging, and for on-going efforts to determine protein structures exclusively on the basis of backbone and ¹³C^β chemical shifts.     

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.     

Comparative analysis of 13C chemical shifts of β-sheet amyloid proteins and outer membrane proteins

Cross-β amyloid fibrils and membrane-bound β-barrels are two important classes of β-sheet proteins. To investigate whether there are systematic differences in the backbone and sidechain conformations of these two families of proteins, here we analyze the ¹³C chemical shifts of 17 amyloid proteins and 7 β-barrel membrane proteins whose high-resolution structures have been determined by NMR. These 24 proteins contain 373 β-sheet residues in amyloid fibrils and 521 β-sheet residues in β-barrel membrane proteins. The ¹³C chemical shifts are shown in 2D ¹³C–¹³C correlation maps, and the amino acid residues are categorized by two criteria: (1) whether they occur in β-strand segments or in loops and turns; (2) whether they are water-exposed or dry, facing other residues or lipids. We also examine the abundance of each amino acid in amyloid proteins and β-barrels and compare the sidechain rotameric populations. The ¹³C chemical shifts indicate that hydrophobic methyl-rich residues and aromatic residues exhibit larger static sidechain conformational disorder in amyloid fibrils than in β-barrels. In comparison, hydroxyl- and amide-containing polar residues have more ordered sidechains and more ordered backbones in amyloid fibrils than in β-barrels. These trends can be explained by steric zipper interactions between β-sheet planes in cross-β fibrils, and by the interactions of β-barrel residues with lipid and water in the membrane. These conformational trends should be useful for structural analysis of amyloid fibrils and β-barrels based principally on NMR chemical shifts.

     

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 .     

Sequential nearest-neighbor effects on computed <Superscript>13</Superscript>C<Superscript>α</Superscript> chemical shifts

To evaluate sequential nearest-neighbor effects on quantum-chemical calculations of ¹³C^α chemical shifts, we selected the structure of the nucleic acid binding (NAB) protein from the SARS coronavirus determined by NMR in solution (PDB id 2K87). NAB is a 116-residue α/β protein, which contains 9 prolines and has 50% of its residues located in loops and turns. Overall, the results presented here show that sizeable nearest-neighbor effects are seen only for residues preceding proline, where Pro introduces an overestimation, on average, of 1.73 ppm in the computed ¹³C^α chemical shifts. A new ensemble of 20 conformers representing the NMR structure of the NAB, which was calculated with an input containing backbone torsion angle constraints derived from the theoretical ¹³C^α chemical shifts as supplementary data to the NOE distance constraints, exhibits very similar topology and comparable agreement with the NOE constraints as the published NMR structure. However, the two structures differ in the patterns of differences between observed and computed ¹³C^α chemical shifts, Δ _ca,i , for the individual residues along the sequence. This indicates that the Δ _ca,i -values for the NAB protein are primarily a consequence of the limited sampling by the bundles of 20 conformers used, as in common practice, to represent the two NMR structures, rather than of local flaws in the structures.     

Secondary structural analysis of proteins based on 13C chemical shift assignments in unresolved solid-state NMR spectra enhanced by fragmented structure database

Magic-angle-spinning solid-state ¹³C NMR spectroscopy is useful for structural analysis of non-crystalline proteins. However, the signal assignments and structural analysis are often hampered by the signal overlaps primarily due to minor structural heterogeneities, especially for uniformly-¹³C,¹⁵N labeled samples. To overcome this problem, we present a method for assigning ¹³C chemical shifts and secondary structures from unresolved two-dimensional ¹³C–¹³C MAS NMR spectra by spectral fitting, named reconstruction of spectra using protein local structures (RESPLS). The spectral fitting was conducted using databases of protein fragmented structures related to ¹³C^α, ¹³C^β, and ¹³C′ chemical shifts and cross-peak intensities. The experimental ¹³C–¹³C inter- and intra-residue correlation spectra of uniformly isotope-labeled ubiquitin in the lyophilized state had a few broad peaks. The fitting analysis for these spectra provided sequence-specific C^α, C^β, and C′ chemical shifts with an accuracy of about 1.5 ppm, which enabled the assignment of the secondary structures with an accuracy of 79 %. The structural heterogeneity of the lyophilized ubiquitin is revealed from the results. Test of RESPLS analysis for simulated spectra of five different types of proteins indicated that the method allowed the secondary structure determination with accuracy of about 80 % for the 50–200 residue proteins. These results demonstrate that the RESPLS approach expands the applicability of the NMR to non-crystalline proteins exhibiting unresolved ¹³C NMR spectra, such as lyophilized proteins, amyloids, membrane proteins and proteins in living cells.     

Subunit-specific backbone NMR assignments of a 64 kDa trp repressor/DNA complex: A role for N-terminal residues in tandem binding

Deuterium decoupled, triple resonance NMR spectroscopy was used to analyze complexes of ²H,¹⁵N,¹³C labelled intact and (des2–7) trp repressor (2–7 trpR) from E. coli bound in tandem to an idealized 22 basepair trp operator DNA fragment and the corepressor 5-methyltryptophan. The DNA sequence used here binds two trpR dimers in tandem resulting in chemically nonequivalent environments for the two subunits of each dimer. Sequence- and subunit-specific NMR resonance assignments were made for backbone ¹HN, ¹⁵N, ¹³C positions in both forms of the protein and for¹³ C in the intact repressor. The differences in backbone chemical shifts between the two subunits within each dimer of 2–7 trpR reflect dimer-dimer contacts involving the helix-turn-helix domains and N-terminal residues consistent with a previously determined crystal structure [Lawson and Carey (1993) Nature, 366, 178–182]. Comparison of the backbone chemical shifts of DNA-bound 2–7 trpR with those of DNA-bound intact trpR reveals significant changes for those residues involved in N-terminal-mediated interactions observed in the crystal structure. In addition, our solution NMR data contain three sets of resonances for residues 2–12 in intact trpR suggesting that the N-terminus has multiple conformations in the tandem complex. Analysis of C chemical shifts using a chemical shift index (CSI) modified for deuterium isotope effects has allowed a comparison of the secondary structure of intact and 2–7 tprR. Overall these data demonstrate that NMR backbone chemical shift data can be readily used to study specific structural details of large protein complexes.     

NMR assignment of the nonstructural protein nsp3(1066–1181) from SARS-CoV

Sequence-specific NMR assignments of the globular core comprising the residues 1066–1181 within the non-structural protein nsp3e from the SARS coronavirus have been obtained using triple-resonance NMR experiments with the uniformly [¹³C, ¹⁵N]-labeled protein. The backbone and side chain assignments are nearly complete, providing the basis for the ongoing NMR structure determination. A preliminary identification of regular secondary structures has been derived from the ¹³C chemical shifts.     

A 4D HCC(CO)NNH experiment for the correlation of aliphatic side-chain and backbone resonances in 13C/15N-labelled proteins

Summary We recently proposed a novel four-dimensional (4D) NMR strategy for the assignment of backbone nuclei in spectra of ¹³C/¹⁵N-labelled proteins (Boucher et al. (1992) J. Am. Chem. Soc., 114, 2262–2264 and J. Biomol. NMR, 2, 631–637). In this paper we extend this approach with a new constant time 4D HCC(CO)NNH experiment that also correlates the chemical shifts of the aliphatic sidechain (¹H and ¹³C) and backbone (¹H, ¹³C and ¹⁵N) nuclei. It separates the sidechain resonances, which may heavily overlap in spectra of proteins with large numbers of similar residues, according to the backbone nitrogen and amide proton chemical shifts. When used in conjunction with a 4D HCANNH or HNCAHA experiment it allows, in principle, complete assignment of aliphatic sidechain and backbone resonances with just two 4D NMR experiments.     

Predicting <Superscript>13</Superscript>C<Superscript>α</Superscript> chemical shifts for validation of protein structures

The ¹³C^α chemical shifts for 16,299 residues from 213 conformations of four proteins (experimentally determined by X-ray crystallography and Nuclear Magnetic Resonance methods) were computed by using a combination of approaches that includes, but is not limited to, the use of density functional theory. Initially, a validation test of this methodology was carried out by a detailed examination of the correlation between computed and observed ¹³C^α chemical shifts of 10,564 (of the 16,299) residues from 139 conformations of the human protein ubiquitin. The results of this validation test on ubiquitin show agreement with conclusions derived from computation of the chemical shifts at the ab initio Hartree–Fock level. Further, application of this methodology to 5,735 residues from 74 conformations of the three remaining proteins that differ in their number of amino acid residues, sequence and three-dimensional structure, together with a new scoring function, namely the conformationally averaged root-mean-square-deviation, enables us to: (a) offer a criterion for an accurate assessment of the quality of NMR-derived protein conformations; (b) examine whether X-ray or NMR-solved structures are better representations of the observed ¹³C^α chemical shifts in solution; (c) provide evidence indicating that the proposed methodology is more accurate than automated predictors for validation of protein structures; (d) shed light as to whether the agreement between computed and observed ¹³C^α chemical shifts is influenced by the identity of an amino acid residue or its location in the sequence; and (e) provide evidence confirming the presence of dynamics for proteins in solution, and hence showing that an ensemble of conformations is a better representation of the structure in solution than any single conformation. Electronic Supplementary Material The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

A unified NMR strategy for high-throughput determination of backbone fold of small proteins

An efficient semi-automated strategy called PFBD (i.e. Protein Fold from Backbone Data only) has been presented for rapid backbone fold determination of small proteins. It makes use of NMR parameters involving backbone atoms only. These include chemical shifts, amide?Camide NOEs and H-bonds. The backbone chemical shifts are obtained in an automated manner from the orthogonal 2D projections of variants of HNN and HN(C)N experiments (Kumar et al., in Magn Reson Chem 50(5):357?C363, 2012) using AUTOBA (Borkar et al. in J Biomol NMR 50(3):285?C297, 2011); backbone H-bonds are manually derived from constant time long-range 2D-HnCO spectrum (Cordier and Grzesiek in J Am Chem Soc 121:1601?C1602, 1999); and amide?Camide NOEs are derived from 3D HNCO NOESY experiment which provides NOEs along the direct ¹H dimension that has maximum resolution (Lohr and Ruterjans in J Biomol NMR 9(1):371?C388, 1997). All the experiments needed for the execution of PFBD can be recorded and analyzed in about 24?C48?h depending upon the concentration of the protein and dispersion of amide cross-peaks in the ¹H?C¹⁵N correlation spectrum. Thus, we believe that the strategy, because of its speed and simplicity will be very valuable in Biomolecular NMR community for high-throughput structural proteomics of small folded proteins of MW?<?10?C12?kDa, the regime where NMR is generally preferred over X-ray crystallography. The strategy has been validated and demonstrated here on two small globular proteins: human ubiquitin (76 aa) and chicken SH3 domain (62 aa).