Using mass spectrometry-based methods to understand amyloid formation and inhibition of alpha-synuclein and amyloid beta

Amyloid fibrils, insoluble β-sheets structures that arise from protein misfolding, are associated with several neurodegenerative disorders. Many small molecules have been investigated to prevent amyloid fibrils from forming; however, there are currently no therapeutics to combat these diseases. Mass spectrometry (MS) is proving to be effective for studying the high order structure (HOS) of aggregating proteins and for determining structural changes accompanying protein-inhibitor interactions. When combined with native MS (nMS), gas-phase ion mobility, protein footprinting, and chemical cross-linking, MS can afford regional and sometimes amino acid spatial resolution of the aggregating protein. The spatial resolution is greater than typical low-resolution spectroscopic, calorimetric, and the traditional ThT fluorescence methods used in amyloid research today. High-resolution approaches can struggle when investigating protein aggregation, as the proteins exist as complex oligomeric mixtures of many sizes and several conformations or polymorphs. Thus, MS is positioned to complement both high- and low-resolution approaches to studying amyloid fibril formation and protein-inhibitor interactions. This review covers basics in MS paired with ion mobility, continuous hydrogen-deuterium exchange (continuous HDX), pulsed hydrogen-deuterium exchange (pulsed HDX), fast photochemical oxidation of proteins (FPOP) and other irreversible labeling methods, and chemical cross-linking. We then review the applications of these approaches to studying amyloid-prone proteins with a focus on amyloid beta and alpha-synuclein. Another focus is the determination of protein-inhibitor interactions. The expectation is that MS will bring new insights to amyloid formation and thereby play an important role to prevent their formation.

A Novel Method for Identification of Glutarylation Sites Combining Borderline-SMOTE With Tomek Links Technique in Imbalanced Data

Glutarylation is a type of post-translational modification that occurs on lysine residues. It plays an irreplaceable role in various cellular functions. Therefore, identification of glutarylation sites is significant for understanding the molecular mechanism of glutarylation. In this study, we proposed a method named DEXGB_Glu to identify lysine glutarylation sites using XGBoost as classifier which was optimized by differential evolution algorithm. Aiming at the imbalance between positive samples and negative samples, Borderline-SMOTE method was employed to synthesize positive samples, increasing their amount equal to negative samples. Then, Tomek links technique was applied to filter out noise data. Analysis of this method and its results showed that differential evolution algorithm obviously improved the performance and the combination of Borderline-SMOTE and Tomek links effectively solved the imbalance between positive samples and negative samples. Finally, the performance of this method was much better than other methods in prediction of glutarylation sites. The data and code are available on https://github.com/ningq669/DEXGB_Glu.

NMR Spectroscopy in the Conformational Analysis of Peptides: An Overview

BACKGROUND

NMR spectroscopy is one of the most powerful tools to study the structure and interaction properties of peptides and proteins from a dynamic perspective. Knowing the bioactive conformations of peptides is crucial in the drug discovery field to design more efficient analogue ligands and inhibitors of protein-protein interactions targeting therapeutically relevant systems.

OBJECTIVE

This review provides a toolkit to investigate peptide conformational properties by NMR.

METHODS

Articles cited herein, related to NMR studies of peptides and proteins were mainly searched through PubMed and the web. More recent and old books on NMR spectroscopy written by eminent scientists in the field were consulted as well.

RESULTS

The review is mainly focused on NMR tools to gain the 3D structure of small unlabeled peptides. It is more application-oriented as it is beyond its goal to deliver a profound theoretical background. However, the basic principles of 2D homonuclear and heteronuclear experiments are briefly described. Protocols to obtain isotopically labeled peptides and principal triple resonance experiments needed to study them, are discussed as well.

CONCLUSION

NMR is a leading technique in the study of conformational preferences of small flexible peptides whose structure can be often only described by an ensemble of conformations. Although NMR studies of peptides can be easily and fast performed by canonical protocols established a few decades ago, more recently we have assisted to tremendous improvements of NMR spectroscopy to investigate instead large systems and overcome its molecular weight limit.

Analysis and prediction of human acetylation using a cascade classifier based on support vector machine

Background

Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify acetylation sites in proteins accurately. Computational methods are popular because they are more convenient and faster than experimental methods. In this study, we proposed a new computational method to predict acetylation sites in human by combining sequence features and structural features including physicochemical property (PCP), position specific score matrix (PSSM), auto covariation (AC), residue composition (RC), secondary structure (SS) and accessible surface area (ASA), which can well characterize the information of acetylated lysine sites. Besides, a two-step feature selection was applied, which combined mRMR and IFS. It finally trained a cascade classifier based on SVM, which successfully solved the imbalance between positive samples and negative samples and covered all negative sample information.

Results

The performance of this method is measured with a specificity of 72.19% and a sensibility of 76.71% on independent dataset which shows that a cascade SVM classifier outperforms single SVM classifier.

Conclusions

In addition to the analysis of experimental results, we also made a systematic and comprehensive analysis of the acetylation data.

Evaluation of capillary electrophoresis-mass spectrometry for the analysis of the conformational heterogeneity of intact proteins using beta2-microglobulin as model compound

In this work we explored the feasibility of different CE-ESI-MS set-ups for the analysis of conformational states of an intact protein. By using the same background electrolyte at quasi physiological conditions (50 mM ammonium bicarbonate, pH 7.4) a sequential optimization was carried out, initially by evaluating a sheath-liquid interface with both a single quadrupole (SQ) and a time-of-flight (TOF) mass spectrometer; then a sheathless interface coupled with high-resolution QTOF MS was considered. Beta₂-microglobulin has been taken as a model, as it is an amyloidogenic protein and its conformational changes are strictly connected to the onset of a disease. The separation of two conformers at dynamic equilibrium is achieved all the way down to the MS detection. Notably, the equilibrium ratio of the protein conformers is maintained in the electrospray source after CE separation. Strengths and weaknesses of each optimized set-up are emphasized and their feasibility in unfolding studies is evaluated. In particular, ESI-TOF MS can assign protein forms that differ by 1 Da only and sheathless interfacing is best suited to preserve protein structure integrity. This demonstrates the CE-ESI-MS performance in terms of separation, detection and characterization of conformational species that co-populate a protein solution.

Sequence Based Prediction of Antioxidant Proteins Using a Classifier Selection Strategy

Antioxidant proteins perform significant functions in maintaining oxidation/antioxidation balance and have potential therapies for some diseases. Accurate identification of antioxidant proteins could contribute to revealing physiological processes of oxidation/antioxidation balance and developing novel antioxidation-based drugs. In this study, an ensemble method is presented to predict antioxidant proteins with hybrid features, incorporating SSI (Secondary Structure Information), PSSM (Position Specific Scoring Matrix), RSA (Relative Solvent Accessibility), and CTD (Composition, Transition, Distribution). The prediction results of the ensemble predictor are determined by an average of prediction results of multiple base classifiers. Based on a classifier selection strategy, we obtain an optimal ensemble classifier composed of RF (Random Forest), SMO (Sequential Minimal Optimization), NNA (Nearest Neighbor Algorithm), and J48 with an accuracy of 0.925. A Relief combined with IFS (Incremental Feature Selection) method is adopted to obtain optimal features from hybrid features. With the optimal features, the ensemble method achieves improved performance with a sensitivity of 0.95, a specificity of 0.93, an accuracy of 0.94, and an MCC (Matthew’s Correlation Coefficient) of 0.880, far better than the existing method. To evaluate the prediction performance objectively, the proposed method is compared with existing methods on the same independent testing dataset. Encouragingly, our method performs better than previous studies. In addition, our method achieves more balanced performance with a sensitivity of 0.878 and a specificity of 0.860. These results suggest that the proposed ensemble method can be a potential candidate for antioxidant protein prediction. For public access, we develop a user-friendly web server for antioxidant protein identification that is freely accessible at http://antioxidant.weka.cc.

An ensemble method with hybrid features to identify extracellular matrix proteins

The extracellular matrix (ECM) is a dynamic composite of secreted proteins that play important roles in numerous biological processes such as tissue morphogenesis, differentiation and homeostasis. Furthermore, various diseases are caused by the dysfunction of ECM proteins. Therefore, identifying these important ECM proteins may assist in understanding related biological processes and drug development. In view of the serious imbalance in the training dataset, a Random Forest-based ensemble method with hybrid features is developed in this paper to identify ECM proteins. Hybrid features are employed by incorporating sequence composition, physicochemical properties, evolutionary and structural information. The Information Gain Ratio and Incremental Feature Selection (IGR-IFS) methods are adopted to select the optimal features. Finally, the resulting predictor termed IECMP (Identify ECM Proteins) achieves an balanced accuracy of 86.4% using the 10-fold cross-validation on the training dataset, which is much higher than results obtained by other methods (ECMPRED: 71.0%, ECMPP: 77.8%). Moreover, when tested on a common independent dataset, our method also achieves significantly improved performance over ECMPP and ECMPRED. These results indicate that IECMP is an effective method for ECM protein prediction, which has a more balanced prediction capability for positive and negative samples. It is anticipated that the proposed method will provide significant information to fully decipher the molecular mechanisms of ECM-related biological processes and discover candidate drug targets. For public access, we develop a user-friendly web server for ECM protein identification that is freely accessible at http://iecmp.weka.cc.

Spectroscopic studies of kinetically trapped conformations in the gas phase: the case of triply protonated bradykinin

We explore conformational space of triply protonated bradykinin. Three conformational families are mobility-separated and spectroscopically characterized. Kinetically trapped structures are identified via annealing.

A new window into the molecular physiology of membrane proteins

Integral membrane proteins comprise ∼25% of the human proteome. Yet, our understanding of their molecular physiology is still in its infancy. This can be attributed to two factors: the experimental challenges that arise from the difficult chemical nature of membrane proteins, and the unclear relationship between their activity and their native environment. New approaches are therefore required to address these challenges. Recent developments in mass spectrometry have shown that it is possible to study membrane proteins in a solvent-free environment and provide detailed insights into complex interactions, ligand binding and folding processes. Interestingly, not only detergent micelles but also lipid bilayer nanodiscs or bicelles can serve as a means for the gentle desolvation of membrane proteins in the gas phase. In this manner, as well as by direct addition of lipids, it is possible to study the effects of different membrane components on the structure and function of the protein components allowing us to add functional data to the least accessible part of the proteome.

Twenty years of gas phase structural biology

Over the past two decades, mass spectrometry (MS) of protein complexes from their native state has made inroads into structural biology. To coincide with the 20(th) anniversary of Structure, and given that it is now approximately 20 years since the first mass spectra of noncovalent protein complexes were reported, it is timely to consider progress of MS as a structural biology tool. Early reports focused on soluble complexes, contributing to ligand binding studies, subunit interaction maps, and topological models. Recent discoveries have enabled delivery of membrane complexes, encapsulated in detergent micelles, prompting new opportunities. By maintaining interactions between membrane and cytoplasmic subunits in the gas phase, it is now possible to investigate the effects of lipids, nucleotides, and drugs on intact membrane assemblies. These investigations reveal allosteric and synergistic effects of small molecule binding and expose the consequences of posttranslational modifications. In this review, we consider recent progress in the study of protein complexes, focusing particularly on complexes extracted from membranes, and outline future prospects for gas phase structural biology.

Insulin, islet amyloid polypeptide and C-peptide interactions evaluated by mass spectrometric analysis

RATIONALE

Insulin, islet amyloid polypeptide (IAPP), and the C-peptide part of proinsulin are co-secreted from the pancreatic beta cell granules. IAPP aggregation can be inhibited by insulin and insulin aggregation by C-peptide, but different binding and disaggregating interactions may apply for the peptide complexes. A more detailed knowledge of these interactions is necessary for the development strategies against diabetic complications that stem from peptide aggregations.

METHODS

Mass spectrometry (MS) is utilized to investigate pH-dependencies, sequence determinants and association strengths of interactions between pairs of all three peptides. Electrospray ionization (ESI)-MS was used to monitor complex formation and interaction stoichiometries at different pH values. Collision-induced dissociation (CID) was employed to probe relative association strengths and complex dissociation pathways.

RESULTS

IAPP, like C-peptide, removes insulin oligomers observable by ESI-MS. Both C-peptide and IAPP form stable 1:1 heterodimers with insulin. Complexes of the negatively charged C-peptide with the positively charged IAPP, on the other hand, are easily dissociated. Replacement of the conserved glutamic acid residues in C-peptide with alanine residues increases the stability, indicating that net charge alone does not predict association strength. Binding to insulin has been suggested to stabilize a helical fold in IAPP via charge and hydrophobic interactions, which is in agreement with the now observed high gas-phase stability and sensitivity to low pH.

CONCLUSIONS

Combined, these results suggest that the C-peptide-insulin and IAPP-insulin interactions are mediated by a defined binding site, while such a feature is not apparent in the IAPP-C-peptide association. Hence, IAPP and C-peptide are interacting in similar manners and with similar monomerizing effects on insulin, suggesting that both peptides can prevent insulin aggregation. Simultaneous interactions of all three peptides cannot be excluded but appear unlikely from the uneven pairwise binding strengths.

A mesofluidic platform integrating on-chip probe ultrasonication for multiple sample pretreatment involving denaturation, reduction, and digestion in protein identification assays by mass spectrometry

A novel mesofluidic platform integrating on-chip probe ultrasonication for automated high-throughput shotgun proteomic assays.

Protein hydrogen exchange at residue resolution by proteolytic fragmentation mass spectrometry analysis

Hydrogen exchange technology provides a uniquely powerful instrument for measuring protein structural and biophysical properties, quantitatively and in a nonperturbing way, and determining how these properties are implemented to produce protein function. A developing hydrogen exchange-mass spectrometry method (HX MS) is able to analyze large biologically important protein systems while requiring only minuscule amounts of experimental material. The major remaining deficiency of the HX MS method is the inability to deconvolve HX results to individual amino acid residue resolution. To pursue this goal we used an iterative optimization program (HDsite) that integrates recent progress in multiple peptide acquisition together with previously unexamined isotopic envelope-shape information and a site-resolved back-exchange correction. To test this approach, residue-resolved HX rates computed from HX MS data were compared with extensive HX NMR measurements, and analogous comparisons were made in simulation trials. These tests found excellent agreement and revealed the important computational determinants.

An electrospray ms-coupled microfluidic device for sub-second hydrogen/deuterium exchange pulse-labelling reveals allosteric effects in enzyme inhibition

In this work, we introduce an integrated, electrospray mass spectrometry-coupled microfluidic chip that supports the complete workflow for 'bottom up' hydrogen/deuterium exchange (HDX) pulse labelling experiments. HDX pulse labelling is used to measure structural changes in proteins that occur after the initiation of a reaction, most commonly folding. In the present case, we demonstrate the device on the β-lactamase enzyme TEM-1, identifying active site changes that occur upon acylation by a covalent inhibitor and subtle changes in conformational dynamics that occur away from the active site over a period of several second after the inhibitor is bound. Our results demonstrate the power of microfluidics-enabled sub-second HDX pulse labelling as a tool for studying allostery and show some intriguing correlations with mutagenesis studies.

Measuring dynamics in weakly structured regions of proteins using microfluidics-enabled subsecond H/D exchange mass spectrometry

This work introduces an integrated microfluidic device for measuring rapid H/D exchange (HDX) in proteins. By monitoring backbone amide HDX on the millisecond to low second time scale, we are able to characterize conformational dynamics in weakly structured regions, such as loops and molten globule-like domains that are inaccessible in conventional HDX experiments. The device accommodates the entire MS-based HDX workflow on a single chip with residence times sufficiently small (ca. 8 s) that back-exchange is negligible (≤5%), even without cooling. Components include an adjustable position capillary mixer providing a variable-time labeling pulse, a static mixer for HDX quenching, a proteolytic microreactor for rapid protein digestion, and on-chip electrospray ionization (ESI). In the present work, we characterize device performance using three model systems, each illustrating a different application of 'time-resolved' HDX. Ubiquitin is used to illustrate a crude, high throughput structural analysis based on a single subsecond HDX time-point. In experiments using cytochrome c, we distinguish dynamic behavior in loops, establishing a link between flexibility and interactions with the heme prosthetic group. Finally, we localize an unusually high 'burst-phase' of HDX in the large tetrameric enzyme DAHP synthase to a 'molten globule-like' region surrounding the active site.