Influence of the completeness of chemical shift assignments on NMR structures obtained with automated NOE assignment

Reliable automated NOE assignment and structure calculation on the basis of a largely complete, assigned input chemical shift list and a list of unassigned NOESY cross peaks has recently become feasible for routine NMR protein structure calculation and has been shown to yield results that are equivalent to those of the conventional, manual approach. However, these algorithms rely on the availability of a virtually complete list of the chemical shifts. This paper investigates the influence of incomplete chemical shift assignments on the reliability of NMR structures obtained with automated NOESY cross peak assignment. The program CYANA was used for combined automated NOESY assignment with the CANDID algorithm and structure calculations with torsion angle dynamics at various degrees of completeness of the chemical shift assignment which was simulated by random omission of entries in the experimental ¹H chemical shift lists that had been used for the earlier, conventional structure determinations of two proteins. Sets of structure calculations were performed choosing the omitted chemical shifts randomly among all assigned hydrogen atoms, or among aromatic hydrogen atoms. For comparison, automated NOESY assignment and structure calculations were performed with the complete experimental chemical shift but under random omission of NOESY cross peaks. When heteronuclear-resolved three-dimensional NOESY spectra are available the current CANDID algorithm yields in the absence of up to about 10% of the experimental ¹H chemical shifts reliable NOE assignments and three-dimensional structures that deviate by less than 2 Å from the reference structure obtained using all experimental chemical shift assignments. In contrast, the algorithm can accommodate the omission of up to 50% of the cross peaks in heteronuclear- resolved NOESY spectra without producing structures with a RMSD of more than 2 Å to the reference structure. When only homonuclear NOESY spectra are available, the algorithm is slightly more susceptible to missing data and can tolerate the absence of up to about 7% of the experimental ¹H chemical shifts or of up to 30% of the NOESY peaks.Abbreviations: BmPBP^A – Bombyx mori pheromone binding protein form A; CYANA – combined assignment and dynamics algorithm for NMR applications; NMR – nuclear magnetic resonance; NOE – nuclear Overhauser effect; NOESY – NOE spectroscopy; RMSD – root-mean-square deviation; WmKT – Williopsis mrakii killer toxin     

An Empirical Correlation between Secondary Structure Content and Averaged Chemical Shifts in Proteins

It is shown that the averaged chemical shift (ACS) of a particular nucleus in the protein backbone empirically correlates well to its secondary structure content (SSC). Chemical shift values of more than 200 proteins obtained from the Biological Magnetic Resonance Bank are used to calculate ACS values, and the SSC is estimated from the corresponding three-dimensional coordinates obtained from the Protein Data Bank. ACS values of ¹H_α show the highest correlation to helical and sheet structure content (correlation coefficient of 0.80 and 0.75, respectively); ¹H_N exhibits less reliability (0.65 for both sheet and helix), whereas such correlations are poor for the heteronuclei. SSC estimated using this correlation shows a good agreement with the conventional chemical shift index-based approach for a set of proteins that only have chemical shift information but no NMR or x-ray determined three-dimensional structure. These results suggest that even chemical shifts averaged over the entire protein retain significant information about the secondary structure. Thus, the correlation between ACS and SSC can be used to estimate secondary structure content and to monitor large-scale secondary structural changes in protein, as in folding studies.     

Automatic <Superscript>13</Superscript>C chemical shift reference correction for unassigned protein NMR spectra

Poor chemical shift referencing, especially for ¹³C in protein Nuclear Magnetic Resonance (NMR) experiments, fundamentally limits and even prevents effective study of biomacromolecules via NMR, including protein structure determination and analysis of protein dynamics. To solve this problem, we constructed a Bayesian probabilistic framework that circumvents the limitations of previous reference correction methods that required protein resonance assignment and/or three-dimensional protein structure. Our algorithm named Bayesian Model Optimized Reference Correction (BaMORC) can detect and correct ¹³C chemical shift referencing errors before the protein resonance assignment step of analysis and without three-dimensional structure. By combining the BaMORC methodology with a new intra-peaklist grouping algorithm, we created a combined method called Unassigned BaMORC that utilizes only unassigned experimental peak lists and the amino acid sequence. Unassigned BaMORC kept all experimental three-dimensional HN(CO)CACB-type peak lists tested within ±?0.4 ppm of the correct ¹³C reference value. On a much larger unassigned chemical shift test set, the base method kept ¹³C chemical shift referencing errors to within ±?0.45 ppm at a 90% confidence interval. With chemical shift assignments, Assigned BaMORC can detect and correct ¹³C chemical shift referencing errors to within ±?0.22 at a 90% confidence interval. Therefore, Unassigned BaMORC can correct ¹³C chemical shift referencing errors when it will have the most impact, right before protein resonance assignment and other downstream analyses are started. After assignment, chemical shift reference correction can be further refined with Assigned BaMORC. These new methods will allow non-NMR experts to detect and correct ¹³C referencing error at critical early data analysis steps, lowering the bar of NMR expertise required for effective protein NMR analysis.     

Empirical correlation between protein backbone <Superscript>15</Superscript>N and <Superscript>13</Superscript>C secondary chemical shifts and its application to nitrogen chemical shift re-referencing

The linear analysis of chemical shifts (LACS) has provided a robust method for identifying and correcting ¹³C chemical shift referencing problems in data from protein NMR spectroscopy. Unlike other approaches, LACS does not require prior knowledge of the three-dimensional structure or inference of the secondary structure of the protein. It also does not require extensive assignment of the NMR data. We report here a way of extending the LACS approach to ¹⁵N NMR data from proteins, so as to enable the detection and correction of inconsistencies in chemical shift referencing for this nucleus. The approach is based on our finding that the secondary ¹⁵N chemical shift of the backbone nitrogen atom of residue i is strongly correlated with the secondary chemical shift difference (experimental minus random coil) between the alpha and beta carbons of residue i − 1. Thus once alpha and beta ¹³C chemical shifts are available (their difference is referencing error-free), the ¹⁵N referencing can be validated, and an appropriate offset correction can be derived. This approach can be implemented prior to a structure determination and can be used to analyze potential referencing problems in database data not associated with three-dimensional structure. Application of the LACS algorithm to the current BMRB protein chemical shift database, revealed that nearly 35% of the BMRB entries have δ ¹⁵N values mis-referenced by over 0.7 ppm and over 25% of them have δ ¹H^N values mis-referenced by over 0.12 ppm. One implication of the findings reported here is that a backbone ¹⁵N chemical shift provides a better indicator of the conformation of the preceding residue than of the residue itself. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Protein Structure Validation and Refinement Using Amide Proton Chemical Shifts Derived from Quantum Mechanics

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (^h3 J_NC'') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to obtain this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.     

Reliability of exclusively NOESY-based automated resonance assignment and structure determination of proteins

Protein structure determination by NMR can in principle be speeded up both by reducing the measurement time on the NMR spectrometer and by a more efficient analysis of the spectra. Here we study the reliability of protein structure determination based on a single type of spectra, namely nuclear Overhauser effect spectroscopy (NOESY), using a fully automated procedure for the sequence-specific resonance assignment with the recently introduced FLYA algorithm, followed by combined automated NOE distance restraint assignment and structure calculation with CYANA. This NOESY-FLYA method was applied to eight proteins with 63–160 residues for which resonance assignments and solution structures had previously been determined by the Northeast Structural Genomics Consortium (NESG), and unrefined and refined NOESY data sets have been made available for the Critical Assessment of Automated Structure Determination of Proteins by NMR project. Using only peak lists from three-dimensional ¹³C- or ¹⁵N-resolved NOESY spectra as input, the FLYA algorithm yielded for the eight proteins 91–98 % correct backbone and side-chain assignments if manually refined peak lists are used, and 64–96 % correct assignments based on raw peak lists. Subsequent structure calculations with CYANA then produced structures with root-mean-square deviation (RMSD) values to the manually determined reference structures of 0.8–2.0 Å if refined peak lists are used. With raw peak lists, calculations for 4 proteins converged resulting in RMSDs to the reference structure of 0.8–2.8 Å, whereas no convergence was obtained for the four other proteins (two of which did already not converge with the correct manual resonance assignments given as input). These results show that, given high-quality experimental NOESY peak lists, the chemical shift assignments can be uncovered, without any recourse to traditional through-bond type assignment experiments, to an extent that is sufficient for calculating accurate three-dimensional structures.     

Prospects for resonance assignments in multidimensional solid-state NMR spectra of uniformly labeled proteins

Summary The feasibility of assigning the backbone ¹⁵N and ¹³C NMR chemical shifts in multidimensional magic angle spinning NMR spectra of uniformly isotopically labeled proteins and peptides in unoriented solid samples is assessed by means of numerical simulations. The goal of these simulations is to examine how the upper limit on the size of a peptide for which unique assignments can be made depends on the spectral resolution, i.e., the NMR line widths. Sets of simulated three-dimensional chemical shift correlation spectra for artificial peptides of varying length are constructed from published liquid-state NMR chemical shift data for ubiquitin, a well-characterized soluble protein. Resonance assignments consistent with these spectra to within the assumed spectral resolution are found by a numerical search algorithm. The dependence of the number of consistent assignments on the assumed spectral resolution and on the length of the peptide is reported. If only three-dimensional chemical shift correlation data for backbone ¹⁵N and ¹³C nuclei are used, and no residue-specific chemical shift information, information from amino acid side-chain signals, and proton chemical shift information are available, a spectral resolution of 1 ppm or less is generally required for a unique assignment of backbone chemical shifts for a peptide of 30 amino acid residues.     

Automated NMR structure determination of stereo-array isotope labeled ubiquitin from minimal sets of spectra using the SAIL-FLYA system

Stereo-array isotope labeling (SAIL) has been combined with the fully automated NMR structure determination algorithm FLYA to determine the three-dimensional structure of the protein ubiquitin from different sets of input NMR spectra. SAIL provides a complete stereo- and regio-specific pattern of stable isotopes that results in sharper resonance lines and reduced signal overlap, without information loss. Here we show that as a result of the superior quality of the SAIL NMR spectra, reliable, fully automated analyses of the NMR spectra and structure calculations are possible using fewer input spectra than with conventional uniformly ¹³C/¹⁵N-labeled proteins. FLYA calculations with SAIL ubiquitin, using a single three-dimensional “through-bond” spectrum (and 2D HSQC spectra) in addition to the ¹³C-edited and ¹⁵N-edited NOESY spectra for conformational restraints, yielded structures with an accuracy of 0.83–1.15 Å for the backbone RMSD to the conventionally determined solution structure of SAIL ubiquitin. NMR structures can thus be determined almost exclusively from the NOESY spectra that yield the conformational restraints, without the need to record many spectra only for determining intermediate, auxiliary data of the chemical shift assignments. The FLYA calculations for this report resulted in 252 ubiquitin structure bundles, obtained with different input data but identical structure calculation and refinement methods. These structures cover the entire range from highly accurate structures to seriously, but not trivially, wrong structures, and thus constitute a valuable database for the substantiation of structure validation methods.     

Application of the random coil index to studying protein flexibility

Protein flexibility lies at the heart of many protein–ligand binding events and enzymatic activities. However, the experimental measurement of protein motions is often difficult, tedious and error-prone. As a result, there is a considerable interest in developing simpler and faster ways of quantifying protein flexibility. Recently, we described a method, called Random Coil Index (RCI), which appears to be able to quantitatively estimate model-free order parameters and flexibility in protein structural ensembles using only backbone chemical shifts. Because of its potential utility, we have undertaken a more detailed investigation of the RCI method in an attempt to ascertain its underlying principles, its general utility, its sensitivity to chemical shift errors, its sensitivity to data completeness, its applicability to other proteins, and its general strengths and weaknesses. Overall, we find that the RCI method is very robust and that it represents a useful addition to traditional methods of studying protein flexibility. We have implemented many of the findings and refinements reported here into a web server that allows facile, automated predictions of model-free order parameters, MD RMSF and NMR RMSD values directly from backbone ¹H, ¹³C and ¹⁵N chemical shift assignments. The server is available at . Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

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.     

Spectral fitting for signal assignment and structural analysis of uniformly <Superscript>13</Superscript>C-labeled solid proteins by simulated annealing based on chemical shifts and spin dynamics

We describe an approach for the signal assignment and structural analysis with a suite of two-dimensional (13)C-(13)C magic-angle-spinning solid-state NMR spectra of uniformly (13)C-labeled peptides and proteins. We directly fit the calculated spectra to experimental ones by simulated annealing in restrained molecular dynamics program CNS as a function of atomic coordinates. The spectra are calculated from the conformation dependent chemical shift obtained with SHIFTX and the cross-peak intensities computed for recoupled dipolar interactions. This method was applied to a membrane-bound 14-residue peptide, mastoparan-X. The obtained C', C(alpha) and C(beta) chemical shifts agreed with those reported previously at the precisions of 0.2, 0.7 and 0.4 ppm, respectively. This spectral fitting program also provides backbone dihedral angles with a precision of about 50 degrees from the spectra even with resonance overlaps. The restraints on the angles were improved by applying protein database program TALOS to the obtained chemical shifts. The peptide structure provided by these restraints was consistent with the reported structure at the backbone RMSD of about 1 A.     

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.     

Conformational changes of colicin Ia channel-forming domain upon membrane binding: a solid-state NMR study

Channel-forming colicins are bactericidal proteins that spontaneously insert into hydrophobic lipid bilayers. We have used magic-angle spinning solid-state nuclear magnetic resonance spectroscopy to examine the conformational differences between the water-soluble and the membrane-bound states of colicin Ia channel domain, and to study the effect of bound colicin on lipid bilayer structure and dynamics. We detected ¹³C and ¹⁵N isotropic chemical shift differences between the two forms of the protein, which indicate structural changes of the protein due to membrane binding. The Val Cα signal, unambiguously assigned by double-quantum experiments, gave a 0.6 ppm downfield shift in the isotropic position and a 4 ppm reduction in the anisotropic chemical shift span after membrane binding. These suggest that the α-helices in the membrane-bound colicin adopt more ideal helical torsion angles as they spread onto the membrane. Colicin binding significantly reduced the lipid chain order, as manifested by ²H quadrupolar couplings. These results are consistent with the model that colicin Ia channel domain forms an extended helical array at the membrane-water interface upon membrane binding.     

Chemical shift optimization in multidimensional NMR spectra by AUREMOL-SHIFTOPT

A problem often encountered in multidimensional NMR-spectroscopy is that an existing chemical shift list of a protein has to be used to assign an experimental spectrum but does not fit sufficiently well for a safe assignment. A similar problem occurs when temperature or pressure series of n-dimensional spectra are to be evaluated automatically. We have developed two different algorithms, AUREMOL-SHIFTOPT1 and AUREMOL-SHIFTOPT2 that fulfill this task. In the present contribution their performance is analyzed employing a set of simulated and experimental two-dimensional and three-dimensional spectra obtained from three different proteins. A new z-score based on atom and amino acid specific chemical shift distributions is introduced to weight the chemical shift contributions in different dimensions properly.     

Application of sparse NMR restraints to large-scale protein structure prediction

The protein structure prediction algorithm TOUCHSTONEX that uses sparse distance restraints derived from NMR nuclear Overhauser enhancement (NOE) data to predict protein structures at low-to-medium resolution was evaluated as follows: First, a representative benchmark set of the Protein Data Bank library consisting of 1365 proteins up to 200 residues was employed. Using N/8 simulated long-range restraints, where N is the number of residues, 1023 (75%) proteins were folded to a C(alpha) root-mean-square deviation (RMSD) from native <6.5 A in one of the top five models. The average RMSD of the models for all 1365 proteins is 5.0 A. Using N/4 simulated restraints, 1206 (88%) proteins were folded to a RMSD <6.5 A and the average RMSD improved to 4.1 A. Then, 69 proteins with experimental NMR data were used. Using long-range NOE-derived restraints, 47 proteins were folded to a RMSD <6.5 A with N/8 restraints and 61 proteins were folded to a RMSD <6.5 A with N/4 restraints. Thus, TOUCHSTONEX can be a tool for NMR-based rapid structure determination, as well as used in other experimental methods that can provide tertiary restraint information.     

The 13C chemical shifts of amino acids in aqueous solution containing organic solvents: Application to the secondary structure characterization of peptides in aqueous trifluoroethanol solution

Summary The ¹³C chemical shifts for all of the protonated carbons of the 20 common amino acid residues in the protected linear pentapeptide Gly-Gly-X-Gly-Gly have been obtained in water at low pH as well as in aqueous solution containing 10, 20 and 30% acetonitrile or trifluoroethanol. Dioxane was used as an internal reference and its carbon chemical shift value was found to be 66.6 ppm relative to external TMS in water. Comparison of the different referencing methods for ¹³C chemical shifts in organic cosolvent mixtures showed that an external standard (either TMS or TSP capillary) was the most appropriate. In the present study, external TSP was chosen to define the 0 ppm of the ¹³C chemical shift scale. When the difference in referencing the dioxane carbon resonance is taken into account, the carbon chemical shift values of the amino acids in aqueous solution are similar to those previously reported (Richarz and Wüthrich (1978) Biopolymers, 17, 2133–2141; Howarth and Lilley (1979) Prog. NMR Spectrosc., 12, 1–40). The pentapeptides studied were assumed to be in a random coil conformation and the measured ¹³C chemical shifts were used as reference values to correlate carbon chemical shifts with the secondary structure of two well-characterized peptides, bombesin and the 1–29 amino acid fragment of Nle²⁷ human growth hormone-releasing factor. In both cases, the C chemical shifts exhibited a characteristic positive deviation from the random coil values, which indicates the presence of -helices.     

Stereospecific assignment of the asparagine and glutamine sidechain amide protons in proteins from chemical shift analysis

Side chain amide protons of asparagine and glutamine residues in random-coil peptides are characterized by large chemical shift differences and can be stereospecifically assigned on the basis of their chemical shift values only. The bimodal chemical shift distributions stored in the biological magnetic resonance data bank (BMRB) do not allow such an assignment. However, an analysis of the BMRB shows, that a substantial part of all stored stereospecific assignments is not correct. We show here that in most cases stereospecific assignment can also be done for folded proteins using an unbiased artificial chemical shift data base (UACSB). For a separation of the chemical shifts of the two amide resonance lines with differences ≥0.40 ppm for asparagine and differences ≥0.42 ppm for glutamine, the downfield shifted resonance lines can be assigned to H^δ21 and H^ε21, respectively, at a confidence level >95%. A classifier derived from UASCB can also be used to correct the BMRB data. The program tool AssignmentChecker implemented in AUREMOL calculates the Bayesian probability for a given stereospecific assignment and automatically corrects the assignments for a given list of chemical shifts.     

13C-nmr chemical shift and conformation of L-alanine residues incorporated into poly(β-benzyl L-aspartate) in the solid state

¹³C-nmr spectra of poly(β-benzyl L-aspartate) containing ¹³C-enriched [3-¹³C]L -alanine residues in the solid state were recorded by the cross polarization–magic angle spinning method, in order to elucidate the conformation-dependent ¹³C chemical shifts of L -alanine residues taking various conformations such as the antiparallel β-sheet, the right-handed α-helix, the left-handed α-helix, and the left-handed ω-helix forms obtained by appropriate treatment. The latter two conformations for L -alanine residues are achieved when L -alanine residues are incorporated into poly(β-benzyl L -aspartate). We found that the alanine C_β carbon show significant ¹³C chemical shift displacement depending on conformational change, and gave the ¹³C chemical shift values at about 17 ppm for the left-handed ω-helix, 14 ppm for the left-handed α-helix, 15.5 ppm for the right-handed α-helix, and 21.0 ppm for the antiparallel β-sheet relative to tetramethylsilane.     

Three-dimensional experiment for solid-state NMR of aligned protein samples in high field magnets

A pulse sequence that yields three-dimensional ¹H chemical shift / ¹H-¹⁵N heteronuclear dipolar coupling / ¹⁵N chemical shift solid-state NMR spectra is demonstrated on a uniformly ¹⁵N labeled membrane protein in magnetically aligned phospholipid bilayers. Based on SAMPI4, the pulse sequence yields high resolution in all three dimensions at a ¹H resonance frequency of 900 MHz with the relatively low rf field strength (33 kHz) available for a lossy aqueous sample with a commercial spectrometer and probe. The ¹H chemical shift frequency dimension is shown to select among amide resonances, which will be useful in studies of larger polytopic membrane proteins where the resonances overlap in two-dimensional spectra. Moreover, the ¹H chemical shift, which can be measured from these spectra, provides an additional orientationally dependent frequency as input for structure calculations. Both Alexander A. Nevzorov and Sang Ho Park contributed equally to this work.     

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.