Use of chemical shifts in macromolecular structure determination

PPM_One: a static protein structure based chemical shift predictor

We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM_One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs.

CSI 3.0: a web server for identifying secondary and super-secondary structure in proteins using NMR chemical shifts

The Chemical Shift Index or CSI 3.0 (http://csi3.wishartlab.com) is a web server designed to accurately identify the location of secondary and super-secondary structures in protein chains using only nuclear magnetic resonance (NMR) backbone chemical shifts and their corresponding protein sequence data. Unlike earlier versions of CSI, which only identified three types of secondary structure (helix, β-strand and coil), CSI 3.0 now identifies total of 11 types of secondary and super-secondary structures, including helices, β-strands, coil regions, five common β-turns (type I, II, I′, II′ and VIII), β hairpins as well as interior and edge β-strands. CSI 3.0 accepts experimental NMR chemical shift data in multiple formats (NMR Star 2.1, NMR Star 3.1 and SHIFTY) and generates colorful CSI plots (bar graphs) and secondary/super-secondary structure assignments. The output can be readily used as constraints for structure determination and refinement or the images may be used for presentations and publications. CSI 3.0 uses a pipeline of several well-tested, previously published programs to identify the secondary and super-secondary structures in protein chains. Comparisons with secondary and super-secondary structure assignments made via standard coordinate analysis programs such as DSSP, STRIDE and VADAR on high-resolution protein structures solved by X-ray and NMR show >90% agreement between those made with CSI 3.0.

Magic angle spinning NMR of viruses

Viruses, relatively simple pathogens, are able to replicate in many living organisms and to adapt to various environments. Conventional atomic-resolution structural biology techniques, X-ray crystallography and solution NMR spectroscopy provided abundant information on the structures of individual proteins and nucleic acids comprising viruses; however, viral assemblies are not amenable to analysis by these techniques because of their large size, insolubility, and inherent lack of long-range order. In this article, we review the recent advances in magic angle spinning NMR spectroscopy that enabled atomic-resolution analysis of structure and dynamics of large viral systems and give examples of several exciting case studies.

Application of data mining tools for classification of protein structural class from residue based averaged NMR chemical shifts

The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for protein structural information that is directly related to function. Nuclear magnetic resonance (NMR) provides powerful means to determine three-dimensional structures of proteins in the solution state. However, translation of the NMR spectral parameters to even low-resolution structural information such as protein class requires multiple time consuming steps. In this paper, we present an unorthodox method to predict the protein structural class directly by using the residue's averaged chemical shifts (ACS) based on machine learning algorithms. Experimental chemical shift information from 1491 proteins obtained from Biological Magnetic Resonance Bank (BMRB) and their respective protein structural classes derived from structural classification of proteins (SCOP) were used to construct a data set with 119 attributes and 5 different classes. Twenty four different classification schemes were evaluated using several performance measures. Overall the residue based ACS values can predict the protein structural classes with 80% accuracy measured by Matthew correlation coefficient. Specifically protein classes defined by mixed αβ or small proteins are classified with >90% correlation. Our results indicate that this NMR-based method can be utilized as a low-resolution tool for protein structural class identification without any prior chemical shift assignments.

NMR proton chemical shift prediction of C·C mismatches in B-DNA

Accurate prediction of DNA chemical shifts facilitates resonance assignment and allows recognition of different conformational features. Based on the nearest neighbor model and base pair replacement approach, we have determined a set of triplet chemical shift values and correction factors for predicting the proton chemical shifts of B-DNA containing an internal C·C mismatch. Our results provide a reliable chemical shift prediction with an accuracy of 0.07 ppm for non-labile protons and 0.09 ppm for labile protons. In addition, we have also shown that the correction factors for C·C mismatches can be used interchangeably with those for T·T mismatches. As a result, we have generalized a set of correction factors for predicting the flanking residue chemical shifts of pyrimidine·pyrimidine mismatches.

Using chemical shifts to generate structural ensembles for intrinsically disordered proteins with converged distributions of secondary structure

A short segment of the disordered p53 transactivation domain (p53TAD) forms an amphipathic helix when bound to the E3 ubiquitin ligase, MDM2. In the unbound p53TAD, this short segment has transient helical secondary structure. Using a method that combines broad sampling of conformational space with re-weighting, it is shown that it is possible to generate multiple, independent structural ensembles that have highly similar secondary structure distributions for both p53TAD and a P27A mutant. Fractional amounts of transient helical secondary structure were found at the MDM2 binding site that are very similar to estimates based directly on experimental observations. Structures were identified in these ensembles containing segments that are highly similar to short p53 peptides bound to MDM2, even though the ensembles were re-weighted using unbound experimental data. Ensembles were generated using chemical shift data (alpha carbon only, or in combination with other chemical shifts) and cross-validated by predicting residual dipolar couplings. We think this ensemble generator could be used to predict the bound state structure of protein interaction sites in IDPs if there are detectable amounts of matching transient secondary structure in the unbound state.

Fast and accurate resonance assignment of small-to-large proteins by combining automated and manual approaches

The process of resonance assignment is fundamental to most NMR studies of protein structure and dynamics. Unfortunately, the manual assignment of residues is tedious and time-consuming, and can represent a significant bottleneck for further characterization. Furthermore, while automated approaches have been developed, they are often limited in their accuracy, particularly for larger proteins. Here, we address this by introducing the software COMPASS, which, by combining automated resonance assignment with manual intervention, is able to achieve accuracy approaching that from manual assignments at greatly accelerated speeds. Moreover, by including the option to compensate for isotope shift effects in deuterated proteins, COMPASS is far more accurate for larger proteins than existing automated methods. COMPASS is an open-source project licensed under GNU General Public License and is available for download from http://www.liu.se/forskning/foass/tidigare-foass/patrik-lundstrom/software?l=en. Source code and binaries for Linux, Mac OS X and Microsoft Windows are available.

CSI 2.0: a significantly improved version of the Chemical Shift Index

Protein chemical shifts have long been used by NMR spectroscopists to assist with secondary structure assignment and to provide useful distance and torsion angle constraint data for structure determination. One of the most widely used methods for secondary structure identification is called the Chemical Shift Index (CSI). The CSI method uses a simple digital chemical shift filter to locate secondary structures along the protein chain using backbone (13)C and (1)H chemical shifts. While the CSI method is simple to use and easy to implement, it is only about 75-80% accurate. Here we describe a significantly improved version of the CSI (2.0) that uses machine-learning techniques to combine all six backbone chemical shifts ((13)Cα, (13)Cβ, (13)C, (15)N, (1)HN, (1)Hα) with sequence-derived features to perform far more accurate secondary structure identification. Our tests indicate that CSI 2.0 achieved an average identification accuracy (Q3) of 90.56% for a training set of 181 proteins in a repeated tenfold cross-validation and 89.35% for a test set of 59 proteins. This represents a significant improvement over other state-of-the-art chemical shift-based methods. In particular, the level of performance of CSI 2.0 is equal to that of standard methods, such as DSSP and STRIDE, used to identify secondary structures via 3D coordinate data. This suggests that CSI 2.0 could be used both in providing accurate NMR constraint data in the early stages of protein structure determination as well as in defining secondary structure locations in the final protein model(s). A CSI 2.0 web server (http://csi.wishartlab.com) is available for submitting the input queries for secondary structure identification.

Protein-ligand structure guided by backbone and side-chain proton chemical shift perturbations

The fragment-based drug design approach consists of screening libraries of fragment-like ligands, to identify hits that typically bind the protein target with weak affinity (100 μM-5 mM). The determination of the protein-fragment complex 3D structure constitutes a crucial step for uncovering the key interactions responsible for the protein-ligand recognition, and for growing the initial fragment into potent active compounds. The vast majority of fragments are aromatic compounds that induce chemical shift perturbations (CSP) on protein NMR spectra. These experimental CSPs can be quantitatively used to guide the ligand docking, through the comparison between experimental CSPs and CSP back-calculation based on the ring current effect. Here we implemented the CSP back-calculation into the scoring function of the program PLANTS. We compare the results obtained with CSPs measured either on amide or aliphatic protons of the human peroxiredoxin 5. We show that the different kinds of protons lead to different results for resolving the 3D structures of protein-fragment complexes, with the best results obtained with the Hα protons.

Performance of protein-ligand docking with simulated chemical shift perturbations

Protein chemical shift perturbations (CSPs) that result from the binding of a ligand to the protein contain structural information about the complex. Therefore, the CSP data, typically obtained during library screening from two-dimensional (2D) nuclear magnetic resonance (NMR) spectra, are often available before attempts to solve the experimental structure of the complex are started, and can be used to solve the complex structure with CSP-based docking. Here, we compare the performance of the post-docking filter and the guided-docking approaches using either amide or α-proton CSPs with 10 protein-ligand complexes. We show that the comparison of experimental CSPs with CSPs simulated for virtual ligand positions can be used to evidence protein conformational change upon binding and possibly improve the CSP-based docking.

A simple and fast approach for predicting (1)H and (13)C chemical shifts: toward chemical shift-guided simulations of RNA

We introduce a simple and fast approach for predicting RNA chemical shifts from interatomic distances that performs with an accuracy similar to existing predictors and enables the first chemical shift-restrained simulations of RNA to be carried out. Our analysis demonstrates that the applied restraints can effectively guide conformational sampling toward regions of space that are more consistent with chemical shifts than the initial coordinates used for the simulations. As such, our approach should be widely applicable in mapping the conformational landscape of RNAs via chemical shift-guided molecular dynamics simulations. The simplicity and demonstrated sensitivity to three-dimensional structure should also allow our method to be used in chemical shift-based RNA structure prediction, validation, and refinement.

Structural analysis of poly-SUMO chain recognition by the RNF4-SIMs domain

The E3 ubiquitin ligase RNF4 (RING finger protein 4) contains four tandem SIM [SUMO (small ubiquitin-like modifier)-interaction motif] repeats for selective interaction with poly-SUMO-modified proteins, which it targets for degradation. We employed a multi-faceted approach to characterize the structure of the RNF4-SIMs domain and the tetra-SUMO2 chain to elucidate the interaction between them. In solution, the SIM domain was intrinsically disordered and the linkers of the tetra-SUMO2 were highly flexible. Individual SIMs of the RNF4-SIMs domains bind to SUMO2 in the groove between the β2-strand and the α1-helix parallel to the β2-strand. SIM2 and SIM3 bound to SUMO with a high affinity and together constituted the recognition module necessary for SUMO binding. SIM4 alone bound to SUMO with low affinity; however, its contribution to tetra-SUMO2 binding avidity is comparable with that of SIM3 when in the RNF4-SIMs domain. The SAXS data of the tetra-SUMO2-RNF4-SIMs domain complex indicate that it exists as an ordered structure. The HADDOCK model showed that the tandem RNF4-SIMs domain bound antiparallel to the tetra-SUMO2 chain orientation and wrapped around the SUMO protamers in a superhelical turn without imposing steric hindrance on either molecule.

Comparing binding modes of analogous fragments using NMR in fragment-based drug design: application to PRDX5

Fragment-based drug design is one of the most promising approaches for discovering novel and potent inhibitors against therapeutic targets. The first step of the process consists of identifying fragments that bind the protein target. The determination of the fragment binding mode plays a major role in the selection of the fragment hits that will be processed into drug-like compounds. Comparing the binding modes of analogous fragments is a critical task, not only to identify specific interactions between the protein target and the fragment, but also to verify whether the binding mode is conserved or differs according to the fragment modification. While X-ray crystallography is the technique of choice, NMR methods are helpful when this fails. We show here how the ligand-observed saturation transfer difference (STD) experiment and the protein-observed 15N-HSQC experiment, two popular NMR screening experiments, can be used to compare the binding modes of analogous fragments. We discuss the application and limitations of these approaches based on STD-epitope mapping, chemical shift perturbation (CSP) calculation and comparative CSP sign analysis, using the human peroxiredoxin 5 as a protein model.

Prediction of four kinds of simple supersecondary structures in protein by using chemical shifts

Knowledge of supersecondary structures can provide important information about its spatial structure of protein. Some approaches have been developed for the prediction of protein supersecondary structure. However, the feature used by these approaches is primarily based on amino acid sequences. In this study, a novel model is presented to predict protein supersecondary structure by use of chemical shifts (CSs) information derived from nuclear magnetic resonance (NMR) spectroscopy. Using these CSs as inputs of the method of quadratic discriminant analysis (QD), we achieve the overall prediction accuracy of 77.3%, which is competitive with the same method for predicting supersecondary structures from amino acid compositions in threefold cross-validation. Moreover, our finding suggests that the combined use of different chemical shifts will influence the accuracy of prediction.

Structural characterization of the regulatory domain of brain carnitine palmitoyltransferase 1

Neurons contain a mammalian-specific isoform of the enzyme carnitine palmitoyltransferase 1 (CPT1C) that couples malonyl-CoA to ceramide levels thereby contributing to systemic energy homeostasis and feeding behavior. In contrast to CPT1A, which controls the rate-limiting step of long-chain fatty acid β-oxidation in all tissues, the biochemical context and regulatory mechanism of CPT1C are unknown. CPT1 enzymes are comprised of an N-terminal regulatory domain and a C-terminal catalytic domain (CD) that are separated by two transmembrane helices. In CPT1A, the regulatory domain, termed N, adopts an inhibitory and non-inhibitory state, Nα and Nβ, respectively, which differ in their association with the CD. To provide insight into the regulatory mechanism of CPT1C, we have determined the structure of its regulatory domain (residues Met1-Phe50) by NMR spectroscopy. In relation to CPT1A, the inhibitory Nα state was found to be structurally homologues whereas the non-inhibitory Nβ state was severely destabilized, suggesting a change in overall regulation. The destabilization of Nβ may contribute to the low catalytic activity of CPT1C relative to CPT1A and makes its association with the CD unlikely. In analogy to the stabilization of Nβ by the CPT1A CD, non-inhibitory interactions of N of CPT1C with another protein may exist.

Structural and functional studies of Stf76 from the Sulfolobus islandicus plasmid-virus pSSVx: a novel peculiar member of the winged helix-turn-helix transcription factor family

The hybrid plasmid–virus pSSVx from Sulfolobus islandicus presents an open reading frame encoding a 76 amino acid protein, namely Stf76, that does not show significant sequence homology with any protein with known 3D structure. The recombinant protein recognizes specifically two DNA-binding sites located in its own promoter, thus suggesting an auto-regulated role of its expression. Circular dichroism, spectrofluorimetric, light scattering and isothermal titration calorimetry experiments indicated a 2:1 molar ratio (protein:DNA) upon binding to the DNA target containing a single site. Furthermore, the solution structure of Stf76, determined by nuclear magnetic resonance (NMR) using chemical shift Rosetta software, has shown that the protein assumes a winged helix–turn–helix fold. NMR chemical shift perturbation analysis has been performed for the identification of the residues responsible for DNA interaction. In addition, a model of the Stf76–DNA complex has been built using as template a structurally related homolog.

NMR determines transient structure and dynamics in the disordered C-terminal domain of WASp interacting protein

WASp-interacting protein (WIP) is a 503-residue proline-rich polypeptide expressed in human T cells. The WIP C-terminal domain binds to Wiskott-Aldrich syndrome protein (WASp) and regulates its activation and degradation, and the WIP-WASp interaction has been shown to be critical for actin polymerization and implicated in the onset of WAS and X-linked thrombocytopenia. WIP is predicted to be an intrinsically disordered protein, a class of polypeptides that are of great interest because they violate the traditional structure-function paradigm. In this first (to our knowledge) study of WIP in its unbound state, we used NMR to investigate the biophysical behavior of WIP(C), a C-terminal domain fragment of WIP that includes residues 407-503 and contains the WASp-binding site. In light of the poor spectral dispersion exhibited by WIP(C) and the high occurrence (25%) of proline residues, we employed 5D-NMR(13)C-detected NMR experiments with nonuniform sampling to accomplish full resonance assignment. Secondary chemical-shift analysis, (15)N relaxation rates, and protection from solvent exchange all concurred in detecting transient structure located in motifs that span the WASp-binding site. Residues 446-456 exhibited a propensity for helical conformation, and an extended conformation followed by a short, capped helix was observed for residues 468-478. The (13)C-detected approach allows chemical-shift assignment in the WIP(C) polyproline stretches and thus sheds light on their conformation and dynamics. The effects of temperature on chemical shifts referenced to a denatured sample of the polypeptide demonstrate that heating reduces the structural character of WIP(C). Thus, we conclude that the disordered WIP(C) fragment is comprised of regions with latent structure connected by flexible loops, an architecture with implications for binding affinity and function.

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.

Impact of the K24N mutation on the transactivation domain of p53 and its binding to murine double-minute clone 2

The level of the p53 transcription factor is negatively regulated by the E3 ubiquitin ligase murine double-minute clone 2 (MDM2). The interaction between p53 and MDM2 is essential for the maintenance of genomic integrity for most eukaryotes. Previous structural studies revealed that MDM2 binds to p53 transactivation domain (p53TAD) from residues 17 to 29. The K24N mutation of p53TAD changes a lysine at position 24 to an asparagine. This mutation occurs naturally in the bovine family and is also found in a rare form of human gestational cancer called choriocarcinoma. In this study, we have investigated how the K24N mutation affects the affinity, structure, and dynamics of p53TAD binding to MDM2. Nuclear magnetic resonance studies of p53TAD show that the K24N mutant is more flexible and has less transient helical secondary structure than the wild type. Isothermal titration calorimetry measurements demonstrate that these changes in structure and dynamics do not significantly change the binding affinity for p53TAD-MDM2. Finally, free-energy perturbation and standard molecular dynamic simulations suggest the negligible affinity change is due to a compensating interaction energy between the K24N mutant and the MDM2 when it is bound. Overall, the data suggest that the K24N-MDM2 complex is able to, at least partly, compensate for an increase in the conformational entropy in unbound K24N with an increase in the bound-state electrostatic interaction energy.

NMR proton chemical shift prediction of T·T mismatches in B-DNA duplexes

A proton chemical shift prediction scheme for B-DNA duplexes containing a T·T mismatch has been established. The scheme employs a set of T·T mismatch triplet chemical shift values, 5'- and 3'-correction factors extracted from reference sequences, and also the B-DNA chemical shift values predicted by Altona et al. The prediction scheme was tested by eight B-DNA duplexes containing T·T mismatches. Based on 560 sets of predicted and experimental proton chemical shift values, the overall prediction accuracy for non-labile protons was determined to be 0.07 ppm with an excellent correlation coefficient of 0.9996. In addition, the prediction accuracy for 96 sets of labile protons was found to be 0.22 ppm with a correlation coefficient of 0.9961. The prediction scheme developed herein can facilitate resonance assignments of B-DNA duplexes containing T·T mismatches and be generalized for the chemical shift prediction of other DNA mismatches. Our chemical shift data will also be useful for establishing structure-chemical shift information in B-DNA containing mismatches.

NMR mapping of PCNA interaction with translesion synthesis DNA polymerase Rev1 mediated by Rev1-BRCT domain

Rev1 is a Y-family translesion synthesis (TLS) DNA polymerase involved in bypass replication across sites of DNA damage and postreplicational gap filling. In the process of TLS, high-fidelity replicative DNA polymerases stalled by DNA damage are replaced by error-prone TLS enzymes responsible for the majority of mutagenesis in eukaryotic cells. The polymerase exchange that gains low-fidelity TLS polymerases access to DNA is mediated by their interactions with proliferating cell nuclear antigen (PCNA). Rev1 stands alone from other Y-family TLS enzymes since it lacks the consensus PCNA-interacting protein box (PIP-box) motif, instead utilizing other modular domains for PCNA binding. Here we report solution NMR structure of an 11-kDa BRCA1 C-terminus (BRCT) domain from Saccharomyces cerevisiae Rev1 and demonstrate with the use of transverse relaxation optimized spectroscopy (TROSY) NMR methods that Rev1-BRCT domain directly interacts with an 87-kDa PCNA in solution. The domain adopts α/β fold (β1-α1-β2-β3-α2-β4-α3-α4) typical for BRCT domain superfamily. PCNA-binding interface of the Rev1-BRCT domain comprises conserved residues of the outer surface of the α1-helix and the α1-β1, β2-β3 and β3-α2 loops. On the other hand, Rev1-BRCT binds to the inter-domain region of PCNA that overlaps with the binding site for the PIP-box motif. Furthermore, Rev1-BRCT domain bound to PCNA can be displaced by increasing amounts of the PIP-box peptide from TLS DNA polymerase polη, suggesting that Rev1-BRCT and polη PIP-box interactions with the same PCNA monomer are mutually exclusive. These results provide structural insights into PCNA recognition by TLS DNA polymerases that help better understand TLS regulation in eukaryotes.

Mapping the Native Conformational Ensemble of Proteins from a Combination of Simulations and Experiments: New Insight into the src-SH3 Domain

The biological function of a protein is strongly tied to the ensemble of three-dimensional conformations populated at physiological temperature, and dynamically transforming into each other. Experimental techniques such as nuclear magnetic resonance spectroscopy (NMR) provide a wealth of structural and dynamical information, which, in combination with an accurate atomic-level computational modeling, can disclose the details of protein behavior. We here propose a fast and efficient protocol employing molecular dynamics (MD) simulations and NMR chemical shifts, which allows one to reconstruct the detailed conformational ensemble of small globular proteins. In the case of the well-studied src-SH3 domain, we are able to obtain new important insight including the existence of a helical state in the RT loop and a pathway for single-file water diffusion in and out of the core.

BcL-xL conformational changes upon fragment binding revealed by NMR

Protein-protein interactions represent difficult but increasingly important targets for the design of therapeutic compounds able to interfere with biological processes. Recently, fragment-based strategies have been proposed as attractive approaches for the elaboration of protein-protein surface inhibitors from fragment-like molecules. One major challenge in targeting protein-protein interactions is related to the structural adaptation of the protein surface upon molecular recognition. Methods capable of identifying subtle conformational changes of proteins upon fragment binding are therefore required at the early steps of the drug design process. In this report we present a fast NMR method able to probe subtle conformational changes upon fragment binding. The approach relies on the comparison of experimental fragment-induced Chemical Shift Perturbation (CSP) of amine protons to CSP simulated for a set of docked fragment poses, considering the ring-current effect from fragment binding. We illustrate the method by the retrospective analysis of the complex between the anti-apoptotic Bcl-xL protein and the fragment 4′-fluoro-[1,1′-biphenyl]-4-carboxylic acid that was previously shown to bind one of the Bcl-xL hot spots. The CSP-based approach shows that the protein undergoes a subtle conformational rearrangement upon interaction, for residues located in helices 2, 3 and the very beginning of 5. Our observations are corroborated by residual dipolar coupling measurements performed on the free and fragment-bound forms of the Bcl-xL protein. These NMR-based results are in total agreement with previous molecular dynamic calculations that evidenced a high flexibility of Bcl-xL around the binding site. Here we show that CSP of protein amine protons are useful and reliable structural probes. Therefore, we propose to use CSP simulation to assess protein conformational changes upon ligand binding in the fragment-based drug design approach.

Total synthesis of the peptaibols hypomurocin A3 and hypomurocin A5, and their conformation analysis

The total syntheses of hypomurocin A3 and hypomuricin A5 (HM A3 and HM A5, resp.) in solution phase are described. These syntheses have been successfully achieved by applying the 'azirine/oxazolone method' to introduce the two Aib-Pro units into the backbone of these undecapeptaibols in one step with methyl 2,2-dimethyl-2H-azirine-3-prolinate as the 'Aib-Pro synthon'. The coupling of Z-protected (Z=(benzyloxy)carbonyl) amino acids or peptide acids with amino acid tert-butyl esters and of peptide segments was carried out according to the TBTU (=O-(benzotriazol-1-yl)-N,N,N',N'-tetramethyluronium tetrafluoroborate) and HOBt (=1-hydroxybenzotriazole) protocol. Purification by reversed-phase HPLC gave the peptides in pure form. The products were characterized by optical rotation, NMR and IR spectroscopy, mass spectrometry, and elemental analysis. The crystal structures of HM A3 and of an octapeptide fragment of HM A5 could be obtained. An NMR analysis was also carried out with HM A3 and HM A5 to determine their conformations in solution. A global structural comparison between the three sequences of HM A1, HM A3, and HM A5 was performed, as well as the HPLC correlation of the natural HM A family and the synthetic samples.

Structural characterization of intrinsically disordered proteins by the combined use of NMR and SAXS

In recent years, IDPs (intrinsically disordered proteins) have emerged as pivotal actors in biology. Despite IDPs being present in all kingdoms of life, they are more abundant in eukaryotes where they are involved in the vast majority of regulation and signalling processes. The realization that, in some cases, functional states of proteins were partly or fully disordered was in contradiction to the traditional view where a well defined three-dimensional structure was required for activity. Several experimental evidences indicate, however, that structural features in IDPs such as transient secondary-structural elements and overall dimensions are crucial to their function. NMR has been the main tool to study IDP structure by probing conformational preferences at residue level. Additionally, SAXS (small-angle X-ray scattering) has the capacity to report on the three-dimensional space sampled by disordered states and therefore complements the local information provided by NMR. The present review describes how the synergy between NMR and SAXS can be exploited to obtain more detailed structural and dynamic models of IDPs in solution. These combined strategies, embedded into computational approaches, promise the elucidation of the structure-function properties of this important, but elusive, family of biomolecules.

Chemical shifts in biomolecules

NMR chemical shifts are sensitive probes of structure and dynamics in proteins. Empirical models, based on a large database of measured shifts, take an input structure and provide increasingly accurate estimates of the corresponding shifts. Quantum chemical calculations can provide the same information, with greater generality but (currently) with less accuracy. These methods are now providing new ways to approach NMR structure determination, and new insights into the conformational dynamics of proteins.

Utility of 1H NMR chemical shifts in determining RNA structure and dynamics

The development of methods for predicting NMR chemical shifts with high accuracy and speed is increasingly allowing use of these abundant, readily accessible measurements in determining the structure and dynamics of proteins. For nucleic acids, however, despite the availability of semiempirical methods for predicting (1)H chemical shifts, their use in determining the structure and dynamics has not yet been examined. Here, we show that (1)H chemical shifts offer powerful restraints for RNA structure determination, allowing discrimination of native structure from non-native states to within 2-4 Å, and <3 Å when highly flexible residues are ignored. Theoretical simulations shows that although (1)H chemical shifts can provide valuable information for constructing RNA dynamic ensembles, large uncertainties in the chemical shift predictions and inherent degeneracies lead to higher uncertainties as compared to residual dipolar couplings.

Protein structure prediction using global optimization by basin-hopping with NMR shift restraints

Computational methods that utilize chemical shifts to produce protein structures at atomic resolution have recently been introduced. In the current work, we exploit chemical shifts by combining the basin-hopping approach to global optimization with chemical shift restraints using a penalty function. For three peptides, we demonstrate that this approach allows us to find near-native structures from fully extended structures within 10,000 basin-hopping steps. The effect of adding chemical shift restraints is that the α and β secondary structure elements form within 1000 basin-hopping steps, after which the orientation of the secondary structure elements, which produces the tertiary contacts, is driven by the underlying protein force field. We further show that our chemical shift-restraint BH approach also works for incomplete chemical shift assignments, where the information from only one chemical shift type is considered. For the proper implementation of chemical shift restraints in the basin-hopping approach, we determined the optimal weight of the chemical shift penalty energy with respect to the CHARMM force field in conjunction with the FACTS solvation model employed in this study. In order to speed up the local energy minimization procedure, we developed a function, which continuously decreases the width of the chemical shift penalty function as the minimization progresses. We conclude that the basin-hopping approach with chemical shift restraints is a promising method for protein structure prediction.

Long-range effects and functional consequences of stabilizing mutations in the ankyrin repeat domain of IκBα

Protein domains containing three or more ankyrin repeats (ARs) are ubiquitous in all phyla. Sequence alignments previously identified certain conserved positions, which have been shown to stabilize AR domains and promote their folding. Consensus mutations [Y254L/T257A (YLTA) and C186P/A220P (CPAP)] stabilize the naturally occuring AR domain of human IκBα to denaturation; however, only the YLTA mutations stabilize the protein to proteasomal degradation. We present results from NMR experiments designed to probe the roles of these consensus mutations in IκBα. According to residual dipolar coupling analysis, the gross structures of the AR domains of both mutants appear to be similar to the wild type (WT). Comparison of chemical shifts of mutant and WT proteins reveals that the YLTA and CPAP consensus mutations cause unexpected long-range effects throughout the AR domains. Backbone dynamics experiments reveal that the YLTA mutations in the sixth AR order the C-terminal PEST sequence on the picosecond-to-nanosecond timescale, compared to either the WT or the CPAP mutant IκBαs. This property is likely the mechanism by which the half-life of YLTA IκBα is extended in vivo.

3D-TROSY-based backbone and ILV-methyl resonance assignments of a 319-residue homodimer from a single protein sample

The feasibility of practically complete backbone and ILV methyl chemical shift assignments from a single [U-(2)H,(15)N,(13)C; Ileδ1-{(13)CH(3)}; Leu,Val-{(13)CH(3)/(12)CD(3)}]-labeled protein sample of the truncated form of ligand-free Bst-Tyrosyl tRNA Synthetase (Bst-ΔYRS), a 319-residue predominantly helical homodimer, is established. Protonation of ILV residues at methyl positions does not appreciably detract from the quality of TROSY triple resonance data. The assignments are performed at 40 °C to improve the sensitivity of the measurements and alleviate the overlap of (1)H-(15)N correlations in the abundant α-helical segments of the protein. A number of auxiliary approaches are used to assist in the assignment process: (1) selection of (1)H-(15)N amide correlations of certain residue types (Ala, Thr/Ser) that simplifies 2D (1)H-(15)N TROSY spectra, (2) straightforward identification of ILV residue types from the methyl-detected 'out-and-back' HMCM(CG)CBCA experiment, and (3) strong sequential HN-HN NOE connectivities in the helical regions. The two subunits of Bst-YRS were predicted earlier to exist in two different conformations in the absence of ligands. In agreement with our earlier findings (Godoy-Ruiz in J Am Chem Soc 133:19578-195781, 2011), no evidence of dimer asymmetry has been observed in either amide- or methyl-detected experiments.

Using NMR chemical shifts to calculate the propensity for structural order and disorder in proteins

NMR spectroscopy offers the unique possibility to relate the structural propensities of disordered proteins and loop segments of folded peptides to biological function and aggregation behaviour. Backbone chemical shifts are ideally suited for this task, provided that appropriate reference data are available and idiosyncratic sensitivity of backbone chemical shifts to structural information is treated in a sensible manner. In the present paper, we describe methods to detect structural protein changes from chemical shifts, and present an online tool [ncSPC (neighbour-corrected Structural Propensity Calculator)], which unites aspects of several current approaches. Examples of structural propensity calculations are given for two well-characterized systems, namely the binding of α-synuclein to micelles and light activation of photoactive yellow protein. These examples spotlight the great power of NMR chemical shift analysis for the quantitative assessment of protein disorder at the atomic level, and further our understanding of biologically important problems.

A peptide study of the relationship between the collagen triple-helix and amyloid

Type XXV collagen, or collagen-like amyloidogenic component, is a component of amyloid plaques, and recent studies suggest this collagen affects amyloid fibril elongation and has a genetic association with Alzheimer's disease. The relationship between the collagen triple helix and amyloid fibrils was investigated by studying peptide models, including a very stable triple helical peptide (Pro-Hyp-Gly)₁₀ , an amyloidogenic peptide GNNQQNY, and a hybrid peptide where the GNNQQNY sequence was incorporated between (GPO)(n) domains. Circular dichroism and nuclear magnetic resonance (NMR) spectroscopy showed the GNNQQNY peptide formed a random coil structure, whereas the hybrid peptide contained a central disordered GNNQQNY region transitioning to triple-helical ends. Light scattering confirmed the GNNQQNY peptide had a high propensity to form amyloid fibrils, whereas amyloidogenesis was delayed in the hybrid peptide. NMR data suggested the triple-helix constraints on the GNNQQNY sequence within the hybrid peptide may disfavor the conformational change necessary for aggregation. Independent addition of a triple-helical peptide to the GNNQQNY peptide under aggregating conditions delayed nucleation and amyloid fibril growth. The inhibition of amyloid nucleation depended on the Gly-Xaa-Yaa sequence and required the triple-helix conformation. The inhibitory effect of the collagen triple-helix on an amyloidogenic sequence, when in the same molecule or when added separately, suggests Type XXV collagen, and possibly other collagens, may play a role in regulating amyloid fibril formation.

A strong 13C chemical shift signature provides the coordination mode of histidines in zinc-binding proteins

Zinc is the second most abundant metal ion incorporated in proteins, and is in many cases a crucial component of protein three-dimensional structures. Zinc ions are frequently coordinated by cysteine and histidine residues. Whereas cysteines bind to zinc via their unique S(γ) atom, histidines can coordinate zinc with two different coordination modes, either N(δ1) or N(ε2) is coordinating the zinc ion. The determination of this coordination mode is crucial for the accurate structure determination of a histidine-containing zinc-binding site by NMR. NMR chemical shifts contain a vast amount of information on local electronic and structural environments and surprisingly their utilization for the determination of the coordination mode of zinc-ligated histidines has been limited so far to (15)N nuclei. In the present report, we observed that the (13)C chemical shifts of aromatic carbons in zinc-ligated histidines represent a reliable signature of their coordination mode. Using a statistical analysis of (13)C chemical shifts, we show that (13)C(δ2) chemical shift is sensitive to the histidine coordination mode and that the chemical shift difference δ{(13)C(ε1)} - δ{(13)C(δ2)} provides a reference-independent marker of this coordination mode. The present approach allows the direct determination of the coordination mode of zinc-ligated histidines even with non-isotopically enriched protein samples and without any prior structural information.

Correlating calcium binding, Förster resonance energy transfer, and conformational change in the biosensor TN-XXL

Genetically encoded calcium indicators have become instrumental in imaging signaling in complex tissues and neuronal circuits in vivo. Despite their importance, structure-function relationships of these sensors often remain largely uncharacterized due to their artificial and multimodular composition. Here, we describe a combination of protein engineering and kinetic, spectroscopic, and biophysical analysis of the Förster resonance energy transfer (FRET)-based calcium biosensor TN-XXL. Using fluorescence spectroscopy of engineered tyrosines, we show that two of the four calcium binding EF-hands dominate the FRET output of TN-XXL and that local conformational changes of these hands match the kinetics of FRET change. Using small-angle x-ray scattering and NMR spectroscopy, we show that TN-XXL changes from a flexible elongated to a rigid globular shape upon binding calcium, thus resulting in FRET signal output. Furthermore, we compare calcium titrations using fluorescence lifetime spectroscopy with the ratiometric approach and investigate potential non-FRET effects that may affect the fluorophores. Thus, our data characterize the biophysics of TN-XXL in detail and may form a basis for further rational engineering of FRET-based biosensors.

Assigning backbone NMR resonances for full length tau isoforms: efficient compromise between manual assignments and reduced dimensionality

Tau protein is the longest disordered protein for which nearly complete backbone NMR resonance assignments have been reported. Full-length tau protein was initially assigned using a laborious combination of bootstrapping assignments from shorter tau fragments and conventional triple resonance NMR experiments. Subsequently it was reported that assignments of comparable quality could be obtained in a fully automated fashion from data obtained using reduced dimensionality NMR (RDNMR) experiments employing a large number of indirect dimensions. Although the latter strategy offers many advantages, it presents some difficulties if manual intervention, confirmation, or correction of the assignments is desirable, as may often be the case for long disordered and degenerate polypeptide sequences. Here we demonstrate that nearly complete backbone resonance assignments for full-length tau isoforms can be obtained without resorting either to bootstrapping from smaller fragments or to very high dimensionality experiments and automation. Instead, a set of RDNMR triple resonance experiments of modest dimensionality lend themselves readily to efficient and unambiguous manual assignments. An analysis of the backbone chemical shifts obtained in this fashion indicates several regions in full length tau with a notable propensity for helical or strand-like structure that are in good agreement with previous observations.

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 (1)H 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 (1)Hα, (1)HN, (13)Cα, (13)Cβ, (13)CO and backbone (15)N chemical shifts, respectively. The model is implemented in the prediction program 4DSPOT, available at http://www.uef.fi/4dspot.

Quantifying millisecond exchange dynamics in proteins by CPMG relaxation dispersion NMR using side-chain 1H probes

A Carr-Purcell-Meiboom-Gill relaxation dispersion experiment is presented for quantifying millisecond time-scale chemical exchange at side-chain (1)H positions in proteins. Such experiments are not possible in a fully protonated molecule because of magnetization evolution from homonuclear scalar couplings that interferes with the extraction of accurate transverse relaxation rates. It is shown, however, that by using a labeling strategy whereby proteins are produced using {(13)C,(1)H}-glucose and D(2)O a significant number of 'isolated' side-chain (1)H spins are generated, eliminating such effects. It thus becomes possible to record (1)H dispersion profiles at the β positions of Asx, Cys, Ser, His, Phe, Tyr, and Trp as well as the γ positions of Glx, in addition to the methyl side-chain moieties. This brings the total of amino acid side-chain positions that can be simultaneously probed using a single (1)H dispersion experiment to 16. The utility of the approach is demonstrated with an application to the four-helix bundle colicin E7 immunity protein, Im7, which folds via a partially structured low populated intermediate that interconverts with the folded, ground state on the millisecond time-scale. The extracted (1)H chemical shift differences at side-chain positions provide valuable restraints in structural studies of invisible, excited states, complementing backbone chemical shifts that are available from existing relaxation dispersion experiments.

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 (13)C NMR data of RNAs. Our procedure uses five (13)C 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 (13)C calibration and detect errors or inconsistencies in RNA (13)C 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-(13)C chemical shift relationship has emerged for RNA so far. We were able to recalibrate or correct 17 datasets resulting in 39 usable (13)C 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 (13)C chemical shift data. This is demonstrated by a clear relationship between ribose (13)C 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.