Structure determination of protein-peptide complexes from NMR chemical shift data using MELD.

Intrinsically disordered regions of proteins often mediate important protein-protein interactions. However, the folding upon binding nature of many polypeptide-protein interactions limits the ability of modeling tools to predict structures of such complexes. To address this problem, we have taken a tandem approach combining NMR chemical shift data and molecular simulations to determine structures of peptide-protein complexes. Here, we demonstrate this approach for polypeptide com-plexes formed with the extraterminal (ET) domain of bromo and extraterminal domain (BET) proteins, which exhibit a high degree of binding plasticity. This system is particularly challenging as the binding process includes allosteric changes across the ET receptor upon binding, and the polypeptide binding partners can form different conformations (e.g., helices and hair-pins) in the complex. In a blind study, the new approach successfully modeled bound-state conformations and binding pos-es, using only backbone chemical shift data, in excellent agreement with experimentally-determined structures. The approach also predicts relative binding affinities of different peptides. This hybrid MELD-NMR approach provides a powerful new tool for structural analysis of protein-polypeptide complexes in the low NMR information content regime, which can be used successfully for flexible systems where one polypeptide binding partner folds upon complex formation.

Swapping the Positions in a Cross-Strand Lateral Ion-Pairing Interaction between Ammonium- and Carboxylate-Containing Residues in a β-Hairpin

Cross-strand lateral ion-pairing interactions are important for antiparallel β-sheet stability. Statistical studies suggested that swapping the position of cross-strand lateral residues should not significantly affect the interaction. Herein, we swapped the position of ammonium- and carboxylate-containing residues with different side-chain lengths in a cross-strand lateral ion-pairing interaction in a β-hairpin. The peptides were analyzed by 2D-NMR. The fraction folded population and folding free energy were derived from the chemical shift data. The ion-pairing interaction energy was derived using double mutant cycle analysis. The general trends for the fraction folded population and interaction energetics remained similar upon swapping the position of the interacting charged residues. The most stabilizing cross-strand interactions were between short residues, similar to the unswapped study. However, the fraction folded populations for most of the swapped peptides were higher compared to the corresponding unswapped peptides. Furthermore, subtle differences in the ion-pairing interaction energy upon swapping were observed, most likely due to the “unleveled” relative positioning of the interacting residues created by the inherent right-handed twist of the structure. These results should be useful for developing functional peptides that rely on lateral ion-pairing interactions across antiparallel β-strands.

ODiNPred: comprehensive prediction of protein order and disorder

Structural disorder is widespread in eukaryotic proteins and is vital for their function in diverse biological processes. It is therefore highly desirable to be able to predict the degree of order and disorder from amino acid sequence. It is, however, notoriously difficult to predict the degree of local flexibility within structured domains and the presence and nuances of localized rigidity within intrinsically disordered regions. To identify such instances, we used the CheZOD database, which encompasses accurate, balanced, and continuous-valued quantification of protein (dis)order at amino acid resolution based on NMR chemical shifts. To computationally forecast the spectrum of protein disorder in the most comprehensive manner possible, we constructed the sequence-based protein order/disorder predictor ODiNPred, trained on an expanded version of CheZOD. ODiNPred applies a deep neural network comprising 157 unique sequence features to 1325 protein sequences together with the experimental NMR chemical shift data. Cross-validation for 117 protein sequences shows that ODiNPred better predicts the continuous variation in order along the protein sequence, suggesting that contemporary predictors are limited by the quality of training data. The inclusion of evolutionary features reduces the performance gap between ODiNPred and its peers, but analysis shows that it retains greater accuracy for the more challenging prediction of intermediate disorder.

Manifesto for the routine use of NMR for the liquid product analysis of aqueous CO2 reduction: from comprehensive chemical shift data to formaldehyde quantification in water

In the quest for developing CO2 reduction processes, we show the efficiency and applicability of 1H NMR as powerful technique for liquid phase products analysis.

Molecular Dynamics model of peptide-protein conjugation: case study of covalent complex between Sos1 peptide and N-terminal SH3 domain from Grb2

We have investigated covalent conjugation of VPPPVPPRRRX′ peptide (where X′ denotes Nε-chloroacetyl lysine) to N-terminal SH3 domain from adapter protein Grb2. Our experimental results confirmed that the peptide first binds to the SH3 domain noncovalently before establishing a covalent linkage through reaction of X′ with the target cysteine residue C32. We have also confirmed that this reaction involves a thiolate-anion form of C32 and follows the SN2 mechanism. For this system, we have developed a new MD-based protocol to model the formation of covalent conjugate. The simulation starts with the known coordinates of the noncovalent complex. When two reactive groups come into contact during the course of the simulation, the reaction is initiated. The reaction is modeled via gradual interpolation between the two sets of force field parameters that are representative of the noncovalent and covalent complexes. The simulation proceeds smoothly, with no appreciable perturbations to temperature, pressure or volume, and results in a high-quality MD model of the covalent complex. The validity of this model is confirmed using the experimental chemical shift data. The new MD-based approach offers a valuable tool to explore the mechanics of protein-peptide conjugation and build accurate models of covalent complexes.

NMR resonance assignments of the four isoforms of the hazelnut allergen Cor a 1.04

In large parts of Europe, Northern America and China people are suffering from allergies after consuming certain kinds of fruits and vegetables. Typical allergic symptoms range from scratching and itching of the throat to severe symptoms like rhino conjunctivitis and anaphylaxis. For hazelnuts (Corylus avellana), these allergies result from initial sensitization to the birch (Betula verrucosa) pollen allergen Bet v 1 and subsequent development of allergic cross-reactions to proteins that are similar in their three-dimensional structure to the sensitizing protein Bet v 1. The cross-reactive proteins in hazelnut are the four isoforms Cor a 1.04 with a molecular weight of about 17.5 kDa. Significant differences regarding the immunologic behavior of these proteins have been reported. In this work we assigned backbone and side chain 1H, 13C, and 15N chemical shifts of these four isoforms, Cor a 1.0401, Cor a 1.0402, Cor a 1.0403, and Cor a 1.0404 by solution NMR spectroscopy. The chemical shift data confirm the characteristic Bet v onefold for all four isoforms, consisting of seven β-strands that are separated by two short α-helices, along with a long C-terminal α-helix. These data provide the basis for a comparative structural and dynamic analysis of these proteins by NMR in order to characterize their different immunologic cross-reactivities on a molecular level.

Bayesian-Maximum-Entropy Reweighting of IDP Ensembles Based on NMR Chemical Shifts

Bayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of a validation-set method to determine the balance, and thus the amount of fitting. We apply the method to synthetic NMR chemical shift data of an intrinsically disordered protein. We show that the method gives consistent results even when other methods to assess the amount of fitting cannot be applied. Finally, we also describe how the errors in the chemical shift predictor can lead to an incorrect fitting and how using secondary chemical shifts could alleviate this problem.

Bayesian-Maximum-Entropy reweighting of IDP ensembles based on NMR chemical shifts

Bayesian and Maximum Entropy approaches allow for a statistically sound and systematic fitting of experimental and computational data. Unfortunately, assessing the relative confidence in these two types of data remains difficult as several steps add unknown error. Here we propose the use of a validation-set method to determine the balance, and thus the amount of fitting. We apply the method to synthetic NMR chemical shift data of an intrinsically disordered protein. We show that the method gives consistent results even when other methods to assess the amount of fitting cannot be applied. Finally, we also describe how the errors in the chemical shift predictor can lead to an incorrect fitting and how using secondary chemical shifts could alleviate this problem.

Guaianolides from Ormenis mixta: Structural Insights and Evaluation of Their Anti-inflammatory Profile

In this paper, the isolation of five new guaianolides (1 – 5) and four (6 – 9) known sesquiterpenes from Ormenis mixta aerial parts is reported. The structural determination of the guaianolides was obtained by NMR spectroscopic data, as well as MS experiments. Their relative configurations were assigned by a combined quantum mechanical/NMR approach, comparing the experimental 13C/1H NMR chemical shift data and 1 J H-H homonuclear coupling constants with the related predicted values. The isolates were assayed for their anti-inflammatory potential evaluating nitric oxide release and cyclooxygenase-2 expression in J774A.1 macrophages treated with lipopolysaccharide from Escherichia coli. Our results indicated that, among the tested compounds, 1 – 3, and 7 were able to inhibit nitric oxide release, while all were able to inhibit cyclooxygenase-2 expression with different potencies.