Structural Features Of Proteins Research Articles

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.

Tm-Values and Unfolded Fraction Can Predict Aggregation Rates for Granulocyte Colony Stimulating Factor Variant Formulations but Not under Predominantly Native Conditions.

Protein engineering and formulation optimization strategies can be taken to minimize protein aggregation in the biopharmaceutical industry. Short-term stability measures such as the midpoint transition temperature (Tm) for global unfolding provide convenient surrogates for longer-term (e.g., 2-year) degradation kinetics, with which to optimize formulations on practical time-scales. While successful in some cases, their limitations have not been fully evaluated or understood. Tm values are known to correlate with chemical degradation kinetics for wild-type granulocyte colony stimulating factor (GCSF) at pH 4-5.5. However, we found previously that the Tm of an antibody Fab fragment only correlated with its rate of monomer loss at temperatures close to the Tm. Here we evaluated Tm, the fraction of unfolded protein (fT) at temperature T, and two additional short-term stability measures, for their ability to predict the kinetics of monomer and bioactivity loss of wild-type GCSF and four variants, at 37 °C, and in a wide range of formulations. The GCSF variants introduced one to three mutations, giving a range of conformational stabilities spanning 7.8 kcal mol-1. We determined the extent to which the formulation rank order differs across the variants when evaluated by each of the four short-term stability measures. All correlations decreased as the difference in average Tm between each pair of GCSF variants increased. The rank order of formulations determined by Tm was the best preserved, with R2-values >0.7. Tm-values also provided a good predictor (R2 = 0.73) of the aggregation rates, extending previous findings to include GCSF variant-formulation combinations. Further analysis revealed that GCSF aggregation rates at 37 °C were dependent on the fraction unfolded at 37 °C (fT37), but transitioned smoothly to a constant baseline rate of aggregation at fT37 < 10-3. A similar function was observed previously for A33 Fab formulated by pH, ionic strength, and temperature, without excipients. For GCSF, all combinations of variants and formulations fit onto a single curve, suggesting that even single mutations destabilized by up to 4.8 kcal mol-1, are insufficient to change significantly the baseline rate of aggregation under native conditions. The baseline rate of aggregation for GCSF under native conditions was 66-fold higher than that for A33 Fab, highlighting that they are a specific feature of each native protein structure, likely to be dependent on local surface properties and dynamics.

Structure of a Thermostable Group II Intron Reverse Transcriptase with Template-Primer and Its Functional and Evolutionary Implications

Bacterial group II intron reverse transcriptases (RTs) function in both intron mobility and RNA splicing and are evolutionary predecessors of retrotransposon, telomerase, and retroviral RTs as well as the spliceosomal protein Prp8 in eukaryotes. Here we determined a crystal structure of a full-length thermostable group II intron RT in complex with an RNA template-DNA primer duplex and incoming deoxynucleotide triphosphate (dNTP) at 3.0-Å resolution. We find that the binding of template-primer and key aspects of the RT active site are surprisingly different from retroviral RTs but remarkably similar to viral RNA-dependent RNA polymerases. The structure reveals a host of features not seen previously in RTs that may contribute to distinctive biochemical properties of group II intron RTs, and it provides a prototype for many related bacterial and eukaryotic non-LTR retroelement RTs. It also reveals how protein structural features used for reverse transcription evolved to promote the splicing of both group II and spliceosomal introns.

Metallothionein: Protein structure prediction and sequence analyses in pigeon pea(Cajanuscajan)

Metallothioneins are a special group of small proteins capable of detoxifying non-essential metal ions present in excess within a plant cell. Metallothioneins are cysteine-rich diverse classes of heavy metal binding protein molecules which are essential for plant growth.These proteins are present in all taxa, except eubacteria. The similarity in protein sequences provides a basis for the method which predicts structural features of a protein with that of a known protein structure. Structural similarity of entire sequence or large sequence fragment enables prediction and modeling of entire structural domain, while distribution of local features of known protein structure make it possible to predict such features in structure of unknown or uncharacterised proteins.In this study, from available genomic resources metallothionein of pigeonpea was identified, structure of metallothionein was predicted and validated. We have presented a step-wise methodology to model a given protein and to validate the structures.

HDX-MS in den Lebenswissenschaften

In-depth structural and mechanistic analysis of biomolecular complexes is crucial for modern life sciences. Here we give an overview on hydrogendeuterium exchange mass spectrometry (HDX-MS) as an attractive tool to study the dynamic and structural features of proteins and their complexes.

APPRIS 2017: principal isoforms for multiple gene sets.

The APPRIS database (http://appris-tools.org) uses protein structural and functional features and information from cross-species conservation to annotate splice isoforms in protein-coding genes. APPRIS selects a single protein isoform, the ‘principal’ isoform, as the reference for each gene based on these annotations. A single main splice isoform reflects the biological reality for most protein coding genes and APPRIS principal isoforms are the best predictors of these main proteins isoforms. Here, we present the updates to the database, new developments that include the addition of three new species (chimpanzee, Drosophila melangaster and Caenorhabditis elegans), the expansion of APPRIS to cover the RefSeq gene set and the UniProtKB proteome for six species and refinements in the core methods that make up the annotation pipeline. In addition APPRIS now provides a measure of reliability for individual principal isoforms and updates with each release of the GENCODE/Ensembl and RefSeq reference sets. The individual GENCODE/Ensembl, RefSeq and UniProtKB reference gene sets for six organisms have been merged to produce common sets of splice variants.

Systematic Identification of Machine-Learning Models Aimed to Classify Critical Residues for Protein Function from Protein Structure.

Protein structure and protein function should be related, yet the nature of this relationship remains unsolved. Mapping the critical residues for protein function with protein structure features represents an opportunity to explore this relationship, yet two important limitations have precluded a proper analysis of the structure-function relationship of proteins: (i) the lack of a formal definition of what critical residues are and (ii) the lack of a systematic evaluation of methods and protein structure features. To address this problem, here we introduce an index to quantify the protein-function criticality of a residue based on experimental data and a strategy aimed to optimize both, descriptors of protein structure (physicochemical and centrality descriptors) and machine learning algorithms, to minimize the error in the classification of critical residues. We observed that both physicochemical and centrality descriptors of residues effectively relate protein structure and protein function, and that physicochemical descriptors better describe critical residues. We also show that critical residues are better classified when residue criticality is considered as a binary attribute (i.e., residues are considered critical or not critical). Using this binary annotation for critical residues 8 models rendered accurate and non-overlapping classification of critical residues, confirming the multi-factorial character of the structure-function relationship of proteins.

Whey protein film properties as affected by ultraviolet treatment under alkaline conditions

The effects of UV radiation treatment on film-forming solutions adjusted to two alkaline pH values (9 or 11) on the properties (water vapour permeability, solubility, mechanical properties, colour and microstructure) of whey protein concentrate films, and on some structural characteristics of proteins (free sulphydryl groups, degree of aggregation, denaturation and secondary structure) were evaluated. UV radiation increased protein aggregation at both pH values. Ultraviolet treatment of pH 9 solutions increased free sulphydryl groups and produced films with higher solubility, tensile strength, elastic modulus, and puncture properties and lower elongation at break; UV radiation at pH 11 decreased free sulphydryl groups and films showed higher solubility and elastic modulus and lower puncture deformation and elongation at break than untreated films. The treatment also affected film colour differently depending on the pH. In conclusion, ultraviolet treatment modifies the properties of the films in different ways depending on the pH of the solutions.

NewProt - a protein engineering portal.

The NewProt protein engineering portal is a one-stop-shop for in silico protein engineering. It gives access to a large number of servers that compute a wide variety of protein structure characteristics supporting work on the modification of proteins through the introduction of (multiple) point mutations. The results can be inspected through multiple visualizers. The HOPE software is included to indicate mutations with possible undesired side effects. The Hotspot Wizard software is embedded for the design of mutations that modify a proteins' activity, specificity, or stability. The NewProt portal is freely accessible at http://newprot.cmbi.umcn.nl/ and http://newprot.fluidops.net/.

RegSNPs-splicing: a tool for prioritizing synonymous single-nucleotide substitution

While synonymous single-nucleotide variants (sSNVs) have largely been unstudied, since they do not alter protein sequence, mounting evidence suggests that they may affect RNA conformation, splicing, and the stability of nascent-mRNAs to promote various diseases. Accurately prioritizing deleterious sSNVs from a pool of neutral ones can significantly improve our ability of selecting functional genetic variants identified from various genome-sequencing projects, and, therefore, advance our understanding of disease etiology. In this study, we develop a computational algorithm to prioritize sSNVs based on their impact on mRNA splicing and protein function. In addition to genomic features that potentially affect splicing regulation, our proposed algorithm also includes dozens structural features that characterize the functions of alternatively spliced exons on protein function. Our systematical evaluation on thousands of sSNVs suggests that several structural features, including intrinsic disorder protein scores, solvent accessible surface areas, protein secondary structures, and known and predicted protein family domains, show significant differences between disease-causing and neutral sSNVs. Our result suggests that the protein structure features offer an added dimension of information while distinguishing disease-causing and neutral synonymous variants. The inclusion of structural features increases the predictive accuracy for functional sSNV prioritization.

Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks.

Post-translational modifications (PTMs) provide an extensible framework for regulation of protein behavior beyond the diversity represented within the genome alone. While the rate of identification of PTMs has rapidly increased in recent years, our knowledge of PTM functionality encompasses less than 5% of this data. We previously developed SAPH-ire (Structural Analysis of PTM Hotspots) for the prioritization of eukaryotic PTMs based on function potential of discrete modified alignment positions (MAPs) in a set of 8 protein families. A proteome-wide expansion of the dataset to all families of PTM-bearing, eukaryotic proteins with a representational crystal structure and the application of artificial neural network (ANN) models demonstrated the broader applicability of this approach. Although structural features of proteins have been repeatedly demonstrated to be predictive of PTM functionality, the availability of adequately resolved 3D structures in the Protein Data Bank (PDB) limits the scope of these methods. In order to bridge this gap and capture the larger set of PTM-bearing proteins without an available, homologous structure, we explored all available MAP features as ANN inputs to identify predictive models that do not rely on 3D protein structural data. This systematic, algorithmic approach explores 8 available input features in exhaustive combinations (247 models; size 2–8). To control for potential bias in random sampling for holdback in training sets, we iterated each model across 100 randomized, sample training and testing sets—yielding 24,700 individual ANNs. The size of the analyzed dataset and iterative generation of ANNs represents the largest and most thorough investigation of predictive models for PTM functionality to date. Comparison of input layer combinations allows us to quantify ANN performance with a high degree of confidence and subsequently select a top-ranked, robust fit model which highlights 3,687 MAPs, including 10,933 PTMs with a high probability of biological impact but without a currently known functional role.

Proton Dynamics in Protein Mass Spectrometry.

Native electrospray ionization/ion mobility-mass spectrometry (ESI/IM-MS) allows an accurate determination of low-resolution structural features of proteins. Yet, the presence of proton dynamics, observed already by us for DNA in the gas phase, and its impact on protein structural determinants, have not been investigated so far. Here, we address this issue by a multistep simulation strategy on a pharmacologically relevant peptide, the N-terminal residues of amyloid-β peptide (Aβ(1-16)). Our calculations reproduce the experimental maximum charge state from ESI-MS and are also in fair agreement with collision cross section (CCS) data measured here by ESI/IM-MS. Although the main structural features are preserved, subtle conformational changes do take place in the first ∼0.1 ms of dynamics. In addition, intramolecular proton dynamics processes occur on the picosecond-time scale in the gas phase as emerging from quantum mechanics/molecular mechanics (QM/MM) simulations at the B3LYP level of theory. We conclude that proton transfer phenomena do occur frequently during fly time in ESI-MS experiments (typically on the millisecond time scale). However, the structural changes associated with the process do not significantly affect the structural determinants.

Comparative structure-function characterization of the saposin-like domains from potato, barley, cardoon and Arabidopsis aspartic proteases

The present study characterized the aspartic protease saposin-like domains of four plant species, Solanum tuberosum (potato), Hordeum vulgare L. (barley), Cynara cardunculus L. (cardoon; artichoke thistle) and Arabidopsis thaliana, in terms of bilayer disruption and fusion, and structure pH-dependence. Comparison of the recombinant saposin-like domains revealed that each induced leakage of bilayer vesicles composed of a simple phospholipid mixture with relative rates Arabidopsis>barley>cardoon>potato. When compared for leakage of bilayer composed of a vacuole-like phospholipid mixture, leakage was approximately five times higher for potato saposin-like domain compared to the others. In terms of fusogenic activity, distinctions between particle size profiles were noted among the four proteins, particularly for potato saposin-like domain. Bilayer fusion assays in reducing conditions resulted in altered fusion profiles except in the case of cardoon saposin-like domain which was virtually unchanged. Secondary structure profiles were similar across all four proteins under different pH conditions, although cardoon saposin-like domain appeared to have higher overall helix structure. Furthermore, increases in Trp emission upon protein-bilayer interactions suggested that protein structure rearrangements equilibrated with half-times ranging from 52 to 120s, with cardoon saposin-like domain significantly slower than the other three species. Overall, the present findings serve as a foundation for future studies seeking to delineate protein structural features and motifs in protein-bilayer interactions based upon variability in plant aspartic protease saposin-like domain structures.

A New Method to Predict the Electronic Circular Dichroism Spectra of Proteins

Electronic circular dichroism (ECD) is a widely applied tool providing information on the average structure of biomolecules, particularly of proteins. The connection between the ECD spectrum in the far ultraviolet range (175-260 nm) and the secondary structure characteristics of proteins has long been established, and is used to monitor structural re-arrangements during biochemical processes such as (un)folding or binding events. The two main methods to interpret ECD spectra are estimation of the average secondary structure ratios by spectrum deconvolution, or the prediction of the spectrum from a proposed structural model and comparison to the experimental spectrum. However, the ambiguity of spectrum deconvolution, and the computational power required for an accurate spectrum prediction with quantum mechanics limited the quantitative interpretation of protein ECD spectra so far.Here we present a computational method that allows the rapid and accurate prediction of the ECD spectra of proteins using their three-dimensional structure and a set of pre-calculated spectrum components (basis set). We derived several basis sets using the crystal structure and CD spectra of 64 ordered proteins. The basis sets are compatible with established secondary structure classification programs such as DSSP and DISICL. We evaluated the accuracy of the derived basis sets and some of the previously available deconvolution and prediction methods. The results indicate that our method has a comparable accuracy to spectrum deconvolution techniques, while eliminating the ambiguity, and provides a significant (+50%) improvement in accuracy over the available CD spectrum prediction software DichroCalc.

Detect unique molecular structure associated with physiochemical properties in CDC varieties of oat grain with unique nutrient traits [Feed Type vs. Milling Type] in comparison with barley grain using advanced molecular spectroscopy as a non-destructive biological tool

The objective of this study was to determinate grain unique protein inherent molecular structure that are related physiochemical and nutrient profiles in CDC developed oat varieties [CDC Nasser (Feed Type) and CDC Seabiscuit (Milling Type)] grown in cool climate condition in western Canada in comparison with conventional barley variety of CDC Meredith as a control using advanced molecular spectroscopy. Multivariate analyses, including an agglomerative hierarchical cluster analysis (CLA) and principal component analysis (PCA), were performed to identify protein molecular structural differences among the grains. The results revealed that CDC Seabiscuit contained greater (P < 0.05) protein structural Amide I and II than CDC Nasser and CDC Meredith, while the greater (P < 0.005) structural Amide I to II area and height ratios was detected in CDC Meredith. New oat grains had greater (P < 0.05) β-sheet height than barley grains, however, there was no difference in α-helix to β-sheet ratio values among the varieties. In conclusion, CDC Nasser and CDC Meredith had no difference in protein molecular structural features, while CDC Seabiscuit contains different protein structural characteristics as compared to CDC Meredith grain. The molecular structure features are highly associated with physiochemical and nutrient profiles in grains, which indicate that it also affect nutrient utilization and availability.

Protein Structural Features in Winter Wheat: Benchmarking Diversity in Ontario Hard and Soft Winter Wheat

A set of 32 winter wheat lines and varieties was selected to benchmark Ontario winter wheat as a first step toward improving quality. Protein secondary structure, total and accessible thiols, rheological properties, gluten aggregation kinetics, and network forming capabilities of different polymers were determined for each wheat line. Results revealed that there were statistically significant differences among the lines selected (P &lt; 0.05). The differences between hard and soft wheat classes were not as large as would be expected, however, despite the range of quality parameters measured. Benchmarks revealed that several soft wheat lines outperformed hard wheat lines in standard breadmaking quality measures. Protein conformation changed significantly as the moisture content of the samples increased to mimic different model product systems: flour, dough, and batter. The conformation of the flour samples exhibited different patterns between hard and soft wheat classes, although these differences became narrower in the dough and batter states. Principal component analysis (PCA) factors included most quality parameters measured, with the notable exceptions of solvent retention capacity tests and total thiols. Protein conformation and accessible thiols were significant PCA factors that tended to override the rheological measures of quality they represented, suggesting that protein secondary structure and disulfide bonding patterns are fundamental aspects of rheological quality measures.

Excavating the surface-associated and secretory proteome ofMycobacterium lepraefor identifying vaccines and diagnostic markers relevant immunodominant epitopes

For centuries, Mycobacterium leprae, etiological agent of leprosy, has been afflicting mankind regardless of extensive use of live-attenuated vaccines and antibiotics. Surface-associated and secretory proteins (SASPs) are attractive targets against bacteria. We have integrated biological knowledge with computational approaches and present a proteome-wide identification of SASPs. We also performed computational assignment of immunodominant epitopes as coordinates of prospective antigenic candidates in most important class of SASPs, the outer membrane proteins (OMPs). Exploiting the known protein sequence and structural characteristics shared by the SASPs from bacteria, 17 lipoproteins, 11 secretory and 19 novel OMPs (including 4 essential proteins) were identified in M. leprae As OMPs represent the most exposed antigens on the cell surface, their immunoinformatics analysis showed that the identified 19 OMPs harbor T-cell MHC class I epitopes and class II epitopes against HLA-DR alleles (54), while 15 OMPs present potential T-cell class II epitopes against HLA-DQ alleles (6) and 7 OMPs possess T-cell class II epitopes against HLA-DP alleles (5) of humans. Additionally, 11 M. leprae OMPs were found to have B-cell epitopes and these may be considered as prime candidates for the development of new immunotherapeutics against M. leprae.

Are Charge-State Distributions a Reliable Tool Describing Molecular Ensembles of Intrinsically Disordered Proteins by Native MS?

Native mass spectrometry (MS) has become a central tool of structural proteomics, but its applicability to the peculiar class of intrinsically disordered proteins (IDPs) is still object of debate. IDPs lack an ordered tridimensional structure and are characterized by high conformational plasticity. Since they represent valuable targets for cancer and neurodegeneration research, there is an urgent need of methodological advances for description of the conformational ensembles populated by these proteins in solution. However, structural rearrangements during electrospray-ionization (ESI) or after the transfer to the gas phase could affect data obtained by native ESI-MS. In particular, charge-state distributions (CSDs) are affected by protein conformation inside ESI droplets, while ion mobility (IM) reflects protein conformation in the gas phase. This review focuses on the available evidence relating IDP solution ensembles with CSDs, trying to summarize cases of apparent consistency or discrepancy. The protein-specificity of ionization patterns and their responses to ligands and buffer conditions suggests that CSDs are imprinted to protein structural features also in the case of IDPs. Nevertheless, it seems that these proteins are more easily affected by electrospray conditions, leading in some cases to rearrangements of the conformational ensembles. Graphical Abstract ᅟ.

ExonImpact: Prioritizing Pathogenic Alternative Splicing Events.

Alternative splicing (AS) is a closely regulated process that allows a single gene to encode multiple protein isoforms, thereby contributing to the diversity of the proteome. Dysregulation of the splicing process has been found to be associated with many inherited diseases. However, among the pathogenic AS events, there are numerous "passenger" events whose inclusion or exclusion does not lead to significant changes with respect to protein function. In this study, we evaluate the secondary and tertiary structural features of proteins associated with disease-causing and neutral AS events, and show that several structural features are strongly associated with the pathological impact of exon inclusion. We further develop a machine-learning-based computational model, ExonImpact, for prioritizing and evaluating the functional consequences of hitherto uncharacterized AS events. We evaluated our model using several strategies including cross-validation, and data from the Gene-Tissue Expression (GTEx) and ClinVar databases. ExonImpact is freely available at http://watson.compbio.iupui.edu/ExonImpact.