Structural Features Of Proteins Research Articles

ProBAPred: Inferring protein-protein binding affinity by incorporating protein sequence and structural features.

Protein-protein binding interaction is the most prevalent biological activity that mediates a great variety of biological processes. The increasing availability of experimental data of protein-protein interaction allows a systematic construction of protein-protein interaction networks, significantly contributing to a better understanding of protein functions and their roles in cellular pathways and human diseases. Compared to well-established classification for protein-protein interactions (PPIs), limited work has been conducted for estimating protein-protein binding free energy, which can provide informative real-value regression models for characterizing the protein-protein binding affinity. In this study, we propose a novel ensemble computational framework, termed ProBAPred (Protein-protein Binding Affinity Predictor), for quantitative estimation of protein-protein binding affinity. A large number of sequence and structural features, including physical-chemical properties, binding energy and conformation annotations, were collected and calculated from currently available protein binding complex datasets and the literature. Feature selection based on the WEKA package was performed to identify and characterize the most informative and contributing feature subsets. Experiments on the independent test showed that our ensemble method achieved the lowest Mean Absolute Error (MAE; 1.657 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mspace/></mml:math> kcal/mol) and the second highest correlation coefficient ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>R</mml:mi><mml:mtext>-value</mml:mtext><mml:mo>=</mml:mo><mml:mn>0</mml:mn><mml:mo>.</mml:mo><mml:mn>4</mml:mn><mml:mn>6</mml:mn><mml:mn>7</mml:mn></mml:math> ), compared with the existing methods. The datasets and source codes of ProBAPred, and the supplementary materials in this study can be downloaded at http://lightning.med.monash.edu/probapred/ for academic use. We anticipate that the developed ProBAPred regression models can facilitate computational characterization and experimental studies of protein-protein binding affinity.

Integration of ultrasonic treatment in biorefinery of tea residue: protein structural characteristics and functionality, and the generation of by-products

The effect of integrating ultrasonic pretreatment with ethanol and Viscozyme in the alkaline extraction of protein from tea residue and the generation of possible by-products such as polyphenols and galacturonic acid was assessed. Four extraction pathways: ethanol, Viscozyme, ultrasound (EVU); water, Viscozyme, ultrasound (WVU); ethanol, water, ultrasound (EWU); and ethanol, Viscozyme, heat (EVH) were employed. EVU pretreatment together with alkaline extraction resulted in the highest protein recovery yield of 80.95% with a purification factor of 8.5. EVU enhanced the functionality of extracted proteins in terms of solubility, foam capacity and stability, and emulsion capacity and stability. Surface hydrophobicity of EVU extracted proteins increased compared to the other treatments. There was an increase in free sulfhydryl and a decrease in disulfide bond contents in all the treatments except EVH. Analysis of Fourier transform infrared spectroscopy, ultraviolet–visible spectroscopy, non-protein nitrogen content and amino acid content revealed slight modification in the protein advance structure in terms of pretreatment, however, the main peptide chain and amino acid composition were not altered. Yield of 79.25 ± 0.75, 54.7 ± 0.98, and 116.50 ± 6.36 mg/g of polyphenols, galacturonic acid, and total sugars were respectively extracted along the extraction protocol as by-products.

Structural Characterization and Functional Properties of Proteins from Oat Milling Fractions

AbstractThe aim of this work was to study the structure and functionalities of proteins from commercial oat milling fractions. Protein isolates obtained from fine (FB), medium (MB), and low (LB) oat brans, and whole oat groat flour (WF) contained 75.0–97.1% proteins. However, the protein content of the products of 15% (15% high glucan [15HG]) and 20% (20% high glucan [20HG]) HG flours were four fold less because of their high carbohydrate contents (~75%). There was no apparent difference in molecular weights of the polypeptides (20, 35, 60, and 150 kDa) contained in these protein products. Protein profiling using mass spectrometry showed that avenin was not detected in FB and MB because of their relatively high concentrations of 11–12S globulins. Secondary structural features of the molecules and microstructure details of the gelled proteins were similar for proteins from FB, MB, LB, and WF, but different from those of 15HG and 20HG. Similarly, these differences in the structural features of proteins of the milling fractions were reflected in their water‐holding capacity and the solubility properties of the protein products.

Analysis of protein landscapes around N-glycosylation sites from the PDB repository for understanding the structural basis of N-glycoprotein processing and maturation.

Asparagine-linked glycans (N-glycans) are attached onto nascent glycoproteins in the endoplasmic reticulum (ER) and subsequently processed by a set of processing enzymes in the ER and Golgi apparatus. Accumulating evidence has shown that not all N-glycans on glycoproteins are uniformly processed into mature forms (hybrid and complex types in mammals) through the ER and Golgi apparatus, and a certain set of glycans remains unprocessed as an "immature" form (high-mannose type in mammals). Much attention has been paid to environmental factors regulating N-glycoprotein maturation, such as the expression levels of glycosyltransferases/glycosidases. On the other hand, the influence of the 3D structure of the carrier glycoprotein on N-glycan maturation has been investigated mostly using individual model glycoproteins. To obtain more insights into N-glycoprotein maturation, we herein analyze glycoprotein structures extracted from the Protein Data Bank. We confirm that site-specific N-glycan processing is largely explained by the solvent accessibility of the glycosylated Asn residue and of the conjugated N-glycan. Potential bias of protein structural features toward immature or mature forms was explored within a range of concentric circles of fully folded glycoproteins. There does appear to be bias in amino acid composition and secondary structure. Most notably, γ-branched amino acid residues (Asn+Asp+Leu) occur more frequently on unstructured loop regions of immature glycoproteins. Structural features of the protein surface around the N-glycosylated site do seem to affect N-glycan processing and maturation.

Endogenous amdoparvovirus-related elements reveal insights into the biology and evolution of vertebrate parvoviruses

Amdoparvoviruses (family Parvoviridae: genus Amdoparvovirus) infect carnivores, and are a major cause of morbidity and mortality in farmed animals. In this study, we systematically screened animal genomes to identify endogenous parvoviral elements (EPVs) disclosing a high degree of similarity to amdoparvoviruses, and investigated their genomic, phylogenetic and protein structural features. We report the first examples of full-length, amdoparvovirus-derived EPVs in the genome of the Transcaucasian mole vole (Ellobius lutescens). We also identify four EPVs in mammal and reptile genomes that are intermediate between amdoparvoviruses and their sister genus (Protoparvovirus) in terms of their phylogenetic placement and genomic features. In particular, we identify a genome-length EPV in the genome of a pit viper (Protobothrops mucrosquamatus) that is more similar to a protoparvovirus than an amdoparvovirus in terms of its phylogenetic placement and the structural features of its capsid protein (as revealed by homology modeling), yet exhibits characteristically amdoparvovirus-like genome features including: (1) a putative middle ORF gene; (2) a capsid gene that lacks a phospholipase A2 domain; (3) a genome structure consistent with an amdoparvovirus-like mechanism of capsid gene expression. Our findings indicate that amdoparvovirus host range extends to rodents, and that parvovirus lineages possessing a mixture of proto- and amdoparvovirus-like characteristics have circulated in the past. In addition, we show that EPV sequences in the mole vole and pit viper encode intact, expressible replicase genes that have potentially been co-opted or exapted in these host species.

Structure-based stabilization of insulin as a therapeutic protein assembly via enhanced aromatic–aromatic interactions

Key contributions to protein structure and stability are provided by weakly polar interactions, which arise from asymmetric electronic distributions within amino acids and peptide bonds. Of particular interest are aromatic side chains whose directional π-systems commonly stabilize protein interiors and interfaces. Here, we consider aromatic-aromatic interactions within a model protein assembly: the dimer interface of insulin. Semi-classical simulations of aromatic-aromatic interactions at this interface suggested that substitution of residue TyrB26 by Trp would preserve native structure while enhancing dimerization (and hence hexamer stability). The crystal structure of a [TrpB26]insulin analog (determined as a T3Rf3 zinc hexamer at a resolution of 2.25 Å) was observed to be essentially identical to that of WT insulin. Remarkably and yet in general accordance with theoretical expectations, spectroscopic studies demonstrated a 150-fold increase in the in vitro lifetime of the variant hexamer, a critical pharmacokinetic parameter influencing design of long-acting formulations. Functional studies in diabetic rats indeed revealed prolonged action following subcutaneous injection. The potency of the TrpB26-modified analog was equal to or greater than an unmodified control. Thus, exploiting a general quantum-chemical feature of protein structure and stability, our results exemplify a mechanism-based approach to the optimization of a therapeutic protein assembly.

Abstract 3285: COSMIC-3D: Impacts of cancer mutations on protein structure, function, and druggability

Abstract In recent years there has been an explosion in cancer genomic data that has enabled understanding of the incidence and patterns of mutations in cancer patients. The challenge is to translate this vast resource of genomic research and data into precision medicines that target specific mutations in patient populations and improve clinical outcomes. Delivering personalised cancer medicines requires greater understanding of how cancer mutations impact the structure, function, and druggability of known and potential protein drug targets. In this study we annotate each missense mutation in COSMIC, via COSMIC-3D (http://cancer.sanger.ac.uk/cosmic3d), with protein structural features derived from the wwPDB, and rich functional features derived from the UniProt protein database. The structural features include small molecule binding sites (including drug binding sites), protein-protein interaction interfaces, protein-nucleic acid interactions, solvent inaccessible protein “core” versus solvent exposed areas, and predicted small-molecule druggability. The UniProt-derived functional features represent high quality functional site annotations, including post-translational modification sites, functional domains and motifs, and regions of biological interest. In addition, we explore the relationship between mutation occurrence in protein structural and functional sites, and recurrence in cancer. We found that recurrent missense mutations are significantly enriched in specific structural and functional environments, including small-molecule binding sites and predicted druggable pockets. These results provide promising hypotheses that recurrent, cancer driving mutations may be targeted by small-molecule drugs. We posit that further characterisation of the structure-function implications of each mutation in COSMIC-3D will increasingly aid mutation-guided target discovery and drug design. Citation Format: Harry C. Jubb, Harpreet K. Saini, Marcel L. Verdonk, Simon A. Forbes. COSMIC-3D: Impacts of cancer mutations on protein structure, function, and druggability [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3285.

BioStructMap: a Python tool for integration of protein structure and sequence-based features.

SummaryA sliding window analysis over a protein or genomic sequence is commonly performed, and we present a Python tool, BioStructMap, that extends this concept to three-dimensional (3D) space, allowing the application of a 3D sliding window analysis over a protein structure. BioStructMap is easily extensible, allowing the user to apply custom functions to spatially aggregated data. BioStructMap also allows mapping of underlying genomic sequences to protein structures, allowing the user to perform genetic-based analysis over spatially linked codons—this has applications when selection pressures arise at the level of protein structure.Availability and implementationThe Python BioStructMap package is available at https://github.com/andrewguy/biostructmap and released under the MIT License. An online server implementing standard functionality is available at https://biostructmap.burnet.edu.au.Supplementary information Supplementary data are available at Bioinformatics online.

Structural Influence on the Dominance of Virus-Specific CD4 T Cell Epitopes in Zika Virus Infection.

Zika virus (ZIKV) has recently caused explosive outbreaks in Pacific islands, South- and Central America. Like with other flaviviruses, protective immunity is strongly dependent on potently neutralizing antibodies (Abs) directed against the viral envelope protein E. Such Ab formation is promoted by CD4 T cells through direct interaction with B cells that present epitopes derived from E or other structural proteins of the virus. Here, we examined the extent and epitope dominance of CD4 T cell responses to capsid (C) and envelope proteins in Zika patients. All patients developed ZIKV-specific CD4 T cell responses, with substantial contributions of C and E. In both proteins, immunodominant epitopes clustered at sites that are structurally conserved among flaviviruses but have highly variable sequences, suggesting a strong impact of protein structural features on immunodominant CD4 T cell responses. Our data are particularly relevant for designing flavivirus vaccines and their evaluation in T cell assays and provide insights into the importance of viral protein structure for epitope selection and antigenicity.

Conformation and dynamics of soluble repetitive domain elucidates the initial \u03b2-sheet formation of spider silk

The β-sheet is the key structure underlying the excellent mechanical properties of spider silk. However, the comprehensive mechanism underlying β-sheet formation from soluble silk proteins during the transition into insoluble stable fibers has not been elucidated. Notably, the assembly of repetitive domains that dominate the length of the protein chains and structural features within the spun fibers has not been clarified. Here we determine the conformation and dynamics of the soluble precursor of the repetitive domain of spider silk using solution-state NMR, far-UV circular dichroism and vibrational circular dichroism. The soluble repetitive domain contains two major populations: ~65% random coil and ~24% polyproline type II helix (PPII helix). The PPII helix conformation in the glycine-rich region is proposed as a soluble prefibrillar region that subsequently undergoes intramolecular interactions. These findings unravel the mechanism underlying the initial step of β-sheet formation, which is an extremely rapid process during spider silk assembly.

Engineering altered protein-DNA recognition specificity.

Protein engineering is used to generate novel protein folds and assemblages, to impart new properties and functions onto existing proteins, and to enhance our understanding of principles that govern protein structure. While such approaches can be employed to reprogram protein–protein interactions, modifying protein–DNA interactions is more difficult. This may be related to the structural features of protein–DNA interfaces, which display more charged groups, directional hydrogen bonds, ordered solvent molecules and counterions than comparable protein interfaces. Nevertheless, progress has been made in the redesign of protein–DNA specificity, much of it driven by the development of engineered enzymes for genome modification. Here, we summarize the creation of novel DNA specificities for zinc finger proteins, meganucleases, TAL effectors, recombinases and restriction endonucleases. The ease of re-engineering each system is related both to the modularity of the protein and the extent to which the proteins have evolved to be capable of readily modifying their recognition specificities in response to natural selection. The development of engineered DNA binding proteins that display an ideal combination of activity, specificity, deliverability, and outcomes is not a fully solved problem, however each of the current platforms offers unique advantages, offset by behaviors and properties requiring further study and development.

Emerging Camelina Protein: Extraction, Modification, and Structural/Functional Characterization

AbstractCamelina sativa, a sustainable oilseed crop, is a novel source of plant protein. The aim of this work was to evaluate two protein extraction approaches, alkaline and salt extraction, and determine their impact on the structural and functional properties of camelina protein. Protein yield, content, structural characteristics, and functional properties of the produced camelina protein concentrates (CPC, 70–80% protein) and camelina protein hydrolysates were assessed and compared to reference proteins, whey protein isolate and soy protein isolate (SPI). Compared to alkaline pH extraction, data showed that salt extraction produces less denatured and more functional CPC, composed mainly of cruciferin and napin proteins. The functionality of the salt‐extracted CPC was comparable and sometimes better than that of SPI. Specifically, the solubility (~70%) of the salt‐extracted CPC at pH 3.4 was significantly (P &lt; 0.05) higher than that (~50%) of SPI. Additionally, salt‐extracted CPC had significantly higher emulsification capacity and foaming capacity than SPI. On the other hand, the gelation property of CPC was inferior to that of SPI, an observation attributed to the molecular size of camelina protein compared to soy protein. Upon hydrolysis of CPC with Aspergillus oryzae protease, a limited benefit to solubility was noted at pH 7 postthermal treatment. Overall, results revealed the potential of camelina as a novel source of functional plant protein that might gain a position in the protein market place, and possibly compete with soy protein for several applications targeting the use of plant proteins.

Hydrogen Bonds: Simple after All?

Hydrogen bonds play integral roles in biological structure, function, and conformational dynamics and are fundamental to life as it has evolved on Earth. However, our understanding of these fundamental and ubiquitous interactions has seemed fractured and incomplete, and it has been difficult to extract generalities and principles about hydrogen bonds despite thousands of papers published on this topic, perhaps in part because of the expanse of this subject and the density of studies. Fortunately, recent hydrogen bond proposals, discussions, and debates have stimulated new tests and models and have led to a remarkably simple picture of the structure of hydrogen bonds. This knowledge also provides clarity concerning hydrogen bond energetics, limiting and simplifying the factors that need be considered. Herein we recount the advances that have led to this simpler view of hydrogen bond structure, dynamics, and energetics. A quantitative predictive model for hydrogen bond length can now be broadly and deeply applied to evaluate current proposals and to uncover structural features of proteins, their conformational restraints, and their correlated motions. In contrast, a quantitative energetic description of molecular recognition and catalysis by proteins remains an important ongoing challenge, although our improved understanding of hydrogen bonds may aid in testing predictions from current and future models. We close by codifying our current state of understanding into five "Rules for Hydrogen Bonding" that may provide a foundation for understanding and teaching about these vital interactions and for building toward a deeper understanding of hydrogen bond energetics.

Improving the theranostics of Mendelian diseases: from ad hoc to evidence‐based tailored thresholds

Prediction methods are an integral part of biomedical and biotechnological research, particularly with the recent applications of next‐generation sequencing and ever‐growing databases. Most of the prediction methods are based on evolutionary sequence information combined with structural features of proteins. We focused on how applicable the state‐of‐the‐art prediction methods are. We tested the functionality of the recently developed method, EVmutation, which reflects epistasis, on a large set of clinically observed variations in genes associated with Mendelian diseases. Our study has included 44 genes, 7,178 missense variations with known clinical phenotype of their carriers, and 221,337 theoretical missense variations. We compared the outputs from EVmutation with those from SNAP2 and PoPMuSiC 2.1. Despite its novelty, EVmutation was associated with a lack of specificity that was similar to the other methods. The lack of specificity seems to be the common constraint of all recently used prediction methods despite their predictions are associated with high sensitivity, which is often close to 100%. Hence, we tailored the default settings of prediction methods, which appeared burdened by a kind of systemic error, in a general and gene‐specific manner. We found the threshold settings that allowed high specificity and high sensitivity of EVmutation and/or SNAP2 for a precise prediction of up to 41% variations. Besides that, we focused on unsettled criteria for VUS (variant of unknown significance) and inference of variation conservation from multiple sequence alignments (MSAs). Particularly, the effectiveness of prediction methods that are based on use of MSAs can be crippled by low variability among analyzed protein sequences. As a proof of concept, we demonstrated the the improvement in prediction of the effect of clinically observed variations in highly conserved genes AR and PTEN by using a modified MSA building approach. The study confirmed that the predictions of variations in enzymatically active proteins and/or in highly conserved domain structures are more precise than predictions of proteins within flexible parts of protein chains or in domains without catalytic function, which maintain their function, irrespectively of their low sequence identity. When we analyzed a distribution of EVmutation and SNAP2 scores among clinically observed and theoretical variations, we identified several large previously unreported pools of variations that are under negative selection during molecular evolution and are absent in patients; these variations were particularly prominent in G6PD, PTPN11, HNF4A and HBB. The study showed that the prediction of clinical effects differs from simply predicting the effects at the biochemical or molecular level. We thus argue for the re‐evaluation of currently used approaches before getting confused with a vast number of newly developed prediction approaches, which all fail to cope with the specificity issue unless appropriately modified.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Functional characterization of glutamate carboxypeptidase II: a multifunctional Zn‐metalloprotease

Glutamate Carboxypeptidase II (GCPII) is a dimeric, transmembrane, zinc metallopeptidase produced in many organisms including humans. Human GCPII (hGCPII) is expressed in the brain, prostate, intestine, and kidney, and is therefor predicted to exhibit varying tissue‐specific hydrolase activities. The only documented GCPII hydrolase activities are the breakdown of N‐acetyl‐aspartyl‐glutamate (NAAG) – GCPII is involved in the development of neurotoxicity due to excess glutamate – and folyl‐poly‐γ‐glutamate – GCPII is involved in folate uptake across intestinal mucosal membrane. However, functions in other tissues have not been reported. A comprehensive understanding of potentially diverse tissue‐specific proteolytic and other biochemical functions of GCPII requires detailed molecular level in vivo and in vitro studies using the full‐length GCPII and suitable model organism respectively.Homology modeling and protein structure analyses identified a hGCPII ortholog in the roundworm Caenorhabditis elegans, (hereafter referred as cGCPII), thus C. elegans has been chosen for the in vivo studies. The hGCPII and the cGCPII share all essential protein structural features. The cGCPII is encoded as three paralogs (gcp‐2.1, gcp‐2.2, gcp‐2.3) compared to five paralogs in humans. Whole animal phenotypic studies carried out using the wild‐type (N2) and the mutant RB1055, which lacks the gcp‐2.1, showed a larger brood size for RB1005 than N2 and longevity assays showed similar lifespans for both strains. The N2 and RB1055 strains raised in the presence of the folate hydrolase inhibitor sulfasalazine (SSZ) and GCPII specific inhibitors 2‐(Phosphonomethyl)pentane‐1,5‐dioicacid (PMPA) or 2‐(3‐Mercaptopropyl)pentanedioic acid (2‐MPPA) and the showed significantly reduced brood size for RB1055 compared to N2. The functional roles of individual cGCPII paralogs were investigated by RNAi mediated knockout experiments. Collective results indicate that the all three cGCPII paralogs may be involved in functional complementation in C. elegans. For the in vitro studies, the full‐length hGCPII was cloned and overexpression was carried out in Pichia pastoris. Several hGCPII expressing transformants have been identified and expression optimization is underway. Parallel cloning in insect cells in process to compare the functionally important glycosylation levels in Pichia versus the insect cells in order to choose an optimal expression system. Together, the in vivo and in vitro findings will aid in further understanding of the physiological functions of GCPII.Support or Funding InformationEastern Illinois UniversityThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Effect of the sequence data deluge on the performance of methods for detecting protein functional residues

BackgroundThe exponential accumulation of new sequences in public databases is expected to improve the performance of all the approaches for predicting protein structural and functional features. Nevertheless, this was never assessed or quantified for some widely used methodologies, such as those aimed at detecting functional sites and functional subfamilies in protein multiple sequence alignments. Using raw protein sequences as only input, these approaches can detect fully conserved positions, as well as those with a family-dependent conservation pattern. Both types of residues are routinely used as predictors of functional sites and, consequently, understanding how the sequence content of the databases affects them is relevant and timely.ResultsIn this work we evaluate how the growth and change with time in the content of sequence databases affect five sequence-based approaches for detecting functional sites and subfamilies. We do that by recreating historical versions of the multiple sequence alignments that would have been obtained in the past based on the database contents at different time points, covering a period of 20 years. Applying the methods to these historical alignments allows quantifying the temporal variation in their performance. Our results show that the number of families to which these methods can be applied sharply increases with time, while their ability to detect potentially functional residues remains almost constant.ConclusionsThese results are informative for the methods’ developers and final users, and may have implications in the design of new sequencing initiatives.

Power law tails in phylogenetic systems

Covariance analysis of protein sequence alignments uses coevolving pairs of sequence positions to predict features of protein structure and function. However, current methods ignore the phylogenetic relationships between sequences, potentially corrupting the identification of covarying positions. Here, we use random matrix theory to demonstrate the existence of a power law tail that distinguishes the spectrum of covariance caused by phylogeny from that caused by structural interactions. The power law is essentially independent of the phylogenetic tree topology, depending on just two parameters-the sequence length and the average branch length. We demonstrate that these power law tails are ubiquitous in the large protein sequence alignments used to predict contacts in 3D structure, as predicted by our theory. This suggests that to decouple phylogenetic effects from the interactions between sequence distal sites that control biological function, it is necessary to remove or down-weight the eigenvectors of the covariance matrix with largest eigenvalues. We confirm that truncating these eigenvectors improves contact prediction.

Identification and characterization of proteolytically resistant gluten-derived peptides.

The lack of digestibility of certain gluten proteins is essential in the development of celiac disease (CD). Gluten proteins are remarkably resistant to luminal and brush-border proteolysis owing to their high proline and glutamine content. Consequently, large fragments remain intact after digestion exerting toxic effects. Intestinal brush-border membrane vesicles (BBMV) have been described as having strong proteolytic activity mainly through prolyl endopeptidase enzymes. The purpose of this work was to monitor the gastrointestinal digestion of specific CD epitopes by means of an in vitro gastrointestinal digestion model that included incubation with brush-border membrane enzymes. Gluten hydrolysates were characterized by mass spectrometry and the immunologic peptides were tracked by searching the main T-cell stimulating epitopes which have been widely described. The immunologic potential of gluten hydrolysates was further analysed by enzyme-linked immunosorbent assay (ELISA). The results showed that the composition of gluten hydrolysates depended on the digestion time and protein structural characteristics. On the other hand, the main T-cell stimulating epitopes formed during hydrolysis depend on the precursor protein. Glutenin oligopeptides were degraded faster whereas gliadin, mainly α-gliadin oligopeptides, remained intact for a long time. MS-based analysis showed that the formation of the epitopes from γ-gliadin and ω-gliadin or glutenin was favoured but they were generally degraded during the gastrointestinal treatment. However, the peptides containing the epitope PFPQPQLPY (α-gliadin) remained intact even after 180 min of digestion time. Overall, from all the epitopes tracked, PFPQPQLPY was the most resistant to in vitro BBMV digestion.

Homology‐based hydrogen bond information improves crystallographic structures in the PDB

The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H‐bond) distances as a source of information. However, H‐bond restraints can improve structures at low resolution where diffraction data are limited. To improve low‐resolution structure refinement, we present methods for deriving H‐bond information either globally from well‐refined high‐resolution structures from the PDB‐REDO databank, or specifically from on‐the‐fly constructed sets of homologous high‐resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low‐resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB‐REDO databank (https://pdb-redo.eu). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.

Chemical Crosslinking Mass Spectrometry Analysis of Protein Conformations and Supercomplexes in Heart Tissue.

While modern structural biology technologies have greatly expanded the size and type of protein complexes that can now be studied, the ability to derive large-scale structural information on proteins and complexes as they exist within tissues is practically nonexistent. Here, we demonstrate the application of crosslinking mass spectrometry to identify protein structural features and interactions in tissue samples, providing systems structural biology insight into protein complexes as they exist in the mouse heart. This includes insights into multiple conformational states of sarcomere proteins, as well as interactions among OXPHOS complexes indicative of supercomplex assembly. The extension of crosslinking mass spectrometry analysis into the realm of tissues opens the door to increasing our understanding of protein structures and interactions within the context of the greater biological system.