Structural Properties Of Proteins Research Articles

Thrombosis in patients with hereditary fibrinogen deficiency

Introduction. In most cases, in patients with hereditary fibrinogen deficiency, clinical manifestations are represented by bleeding of varying intensity and localization. However, the clinical picture of hereditary fibrinogen deficiency can also be represented by thrombosis.Aim — to characterize the detected mutations in fibrinogen genes and to analyze prothrombotic factors in patients with hereditary hypofibrinogenemia and thrombosis.Materials and methods. Forty-nine patients with hereditary hypofibrinogenemia were observed, of which 46 patients had no history of thrombosis and 3 patients had a confirmed history of thrombosis. These 3 patients made up the study group.Results. Heterozygous mutations were found in all 3 patients in the fibrinogen gamma chain gene (FGG), one of them had a previously undescribed deletion g.2653_2684+211del, p.(Asp167Glufs*2), which removes 32 terminal nucleotides of the fifth exon of the FGG gene and leads to the formation of a stop codon in place of amino acid 168. In two other patients, there were missense mutations c.1140T>A, p.(Cys365Ser) and c.1114A>T, p.(Asp356Val), which can determine the thrombogenic properties of the altered protein structure of fibrinogen. Other prothrombotic factors were also identified: genetic polymorphisms of low thrombotic risk, surgery, taking combined oral contraceptives.Conclusion. Hereditary fibrinogen deficiency does not play a protective role in relation to the development of thrombosis and may cause the development of thrombosis, which is associated with its multifunctional role in the hemostasis system. The pathogenesis of thrombosis in patients with hereditary hypofibrinogenemia is multifactorial and may be associated with the characteristics of the main protein defect and the coexistence of hereditary and acquired thrombotic risk factors (surgical interventions, taking combined oral contraceptives, etc.).

Processing Effects on Protein Structure and Physicochemical Properties

Raw materials, whether it is from the animal or plant kingdom, undergo some kind of (domestic or industrial) processing prior to consumption [...]

Selenium Biofortification of Soybean Sprouts: Effects of Selenium Enrichment on Proteins, Protein Structure, and Functional Properties.

Selenium (Se) biofortification during germination is an efficient method for producing Se-enriched soybean sprouts; however, few studies have investigated Se distribution in different germinated soybean proteins and its effects on protein fractions. Herein, we examined Se distribution and speciation in the dominant proteins 7S and 11S of raw soybean (RS), germinated soybean (GS), and germinated soybean with Se biofortification (GS-Se). The effects of germination and Se treatment on protein structure, functional properties, and antioxidant capacity were also determined. The Se concentration in GS-Se was 79.8-fold higher than that in GS. Selenomethionine and methylselenocysteine were the dominant Se species in GS-Se, accounting for 41.5–80.5 and 19.5–21.2% of the total Se with different concentrations of Se treatment, respectively. Se treatment had no significant effects on amino acids but decreased methionine in 11S. In addition, the α-helix contents decreased as the Se concentration increased; the other structures showed no significant changes. The Se treatment also had no significant effects on the water and oil-holding capacities in protein but increased the foaming capacity and emulsion activity index (EAI) of 7S, but only the EAI of 11S. The Se treatment also significantly increased the antioxidant capacity in 7S but not in 11S. This study indicates that the dominant proteins 7S and 11S have different Se enrichment abilities, and the protein structures, functional properties, and antioxidant capacity of GS can be altered by Se biofortification.

Structural Studies of Copper‐Binding Proteins Encoded by the ycnOperon from Bacillus subtilis

Most living organisms encode an ensemble of protein transporters and chaperones to regulate copper levels. The ycn operon of the bacterium Bacillus subtilisis regulated in response to copper, suggesting that the three proteins it encodes may engage in direct interactions with copper ions to facilitate transport and homeostasis of this transition metal. Here, we use a combination of structural, biochemical, biophysical, and bioinorganic approaches to determine the structures of individual proteins and their interactions with copper and other binding partners. The YcnI protein encoded by the operon contains a domain of unknown function (DUF1775) at its N‐terminus. We determined the structure of this domain and characterized its interactions with copper ions, finding that it coordinates the metal using a unique “mono‐histidine brace” site that is highly conserved across other members of the DUF1775 family. Our data also suggest a potential role for this domain to serve as a chaperone to facilitate transfer of metal ions. Furthermore, we also identify potential copper binding sites within the transcriptional regulator encoded within the same operon. Together, these studies reveal new insights into the structure and copper‐binding properties of proteins encoded by the ycnoperon, providing additional perspectives on how they may work together to regulate copper homeostasis. As homologs of these proteins are shared by many other bacterial species, it is likely that analogous mechanisms exist for copper uptake and homeostasis beyond B. subtilis.

Predicting the functional impact of KCNQ1 variants with artificial neural networks.

Recent advances in experimental and computational protein structure determination have provided access to high-quality structures for most human proteins and mutants thereof. However, linking changes in structure in protein mutants to functional impact remains an active area of method development. If successful, such methods can ultimately assist physicians in taking appropriate treatment decisions. This work presents three artificial neural network (ANN)-based predictive models that classify four key functional parameters of KCNQ1 variants as normal or dysfunctional using PSSM-based evolutionary and/or biophysical descriptors. Recent advances in predicting protein structure and variant properties with artificial intelligence (AI) rely heavily on the availability of evolutionary features and thus fail to directly assess the biophysical underpinnings of a change in structure and/or function. The central goal of this work was to develop an ANN model based on structure and physiochemical properties of KCNQ1 potassium channels that performs comparably or better than algorithms using only on PSSM-based evolutionary features. These biophysical features highlight the structure-function relationships that govern protein stability, function, and regulation. The input sensitivity algorithm incorporates the roles of hydrophobicity, polarizability, and functional densities on key functional parameters of the KCNQ1 channel. Inclusion of the biophysical features outperforms exclusive use of PSSM-based evolutionary features in predicting activation voltage dependence and deactivation time. As AI is increasingly applied to problems in biology, biophysical understanding will be critical with respect to 'explainable AI', i.e., understanding the relation of sequence, structure, and function of proteins. Our model is available at www.kcnq1predict.org.

Ultrasonication as an innovative approach to tailor the apple seed proteins into nanosize: Effect on protein structural and functional properties

In this study, protein was extracted from the apple seed flour using alkali-acid precipitation method. The main objective of this study was to evaluate the impact of ultrasonication on structural and techno-functional properties of apple seed protein. Both native (N-protein) and ultra-sonicated protein (US-protein) were characterized for size, zeta potential, structure, protein pattern, crystallinity, thermal stability and functional properties. The results revealed that the hydrodynamic diameter of N-protein and US-protein was 1.2 µm and 484 nm while zeta potential was −11 and −19 mV, respectively. Fourier transform infrared-spectroscopy and X-ray diffraction analysis showed change in the conformational characteristics and functional groups of proteins after nano-reduction. SEM revealed change in the surface morphology of protein molecule upon ultrasonication. Differential scanning calorimetry showed decreased denaturation temperature for US-protein compared to N-protein . SDS-PAGE depicted no change in protein pattern upon ultrasonication. Ultrasonicated protein exhibited increased functional properties like emulsification, foaming, hydrophobicity and oil absorbing properties and hence can be efficiently used as functional ingredient in food and nutraceutical industry.

Relationship between Molecular Structure and Heat-Induced Gel Properties of Duck Myofibrillar Proteins Affected by the Addition of Pea Protein Isolate.

This paper investigates the relationship between the molecular structure and thermally induced gel properties of duck myofibrillar protein isolate (DMPI) as influenced by the addition of pea protein isolate (PPI). The results showed that b* value of the gels increased; however, a* value decreased with the increase of PPI content (p < 0.05). The whiteness of the gels decreased significantly with the addition of pea protein compared with 0% vs. 0.5% addition. Nuclear magnetic resonance tests showed the area of immobilized water also increased with increasing PPI addition (0–2%), thus consistent with the increased water-holding capacity (p < 0.05). The penetration force of the gels increased with increasing PPI addition (p < 0.05), while the storage modulus and loss modulus of the gels were also found to increase, accompanied by the transformation of the α-helix structure into β-sheet, resulting in better dynamics of gel formation. These results indicated the gel-forming ability of DMPI, including water retention and textural properties, improves with increasing PPI addition. Principal component analysis verified these interrelationships. Thus, pea protein could improve the properties of duck myofibrillar protein gels to some extent and improve their microstructure, potentially facilitating the transition from a weak to a non-aggregated, rigid structure.

Effect of wheat gluten addition on the texture, surface tackiness, protein structure, and sensory properties of frozen cooked noodles

Frozen cooked noodles (FCNs) were prepared with different levels (0, 1%, 3% and 5%) of gluten addition, and the effect of gluten on quality of FCNs was investigated. Cooking properties analysis showed that water absorption ratio and cooking loss of FCNs decreased at first and then increased with the increase of gluten addition. Compared to FCNs with 1% and 5% gluten additions, recooked FCNs with 3% gluten addition had a similar texture property to control sample, and they had the highest tensile force and distance, and the lowest surface tackiness. Meanwhile, the recooked FCNs (3% gluten addition) had smaller pores, denser and more complex gluten network, and their force and elasticity during chewing were the best in sensory evaluation. Low-field 1H nuclear magnetic resonance showed that the lowest T21 (0.11 ms) and T23 (51.11 ms) were found in the recooked FCNs (3% gluten addition). Furthermore, the α-helix of samples increased while the β-sheet and random coil decreased, the glutenin macropolymer content of recooked FCNs increased at first and then decreased with adding gluten. These results indicated that the recooked FCNs (3% gluten addition) had a lower surface tackiness, higher sensory scores, and better quality.

Effect of partial substitution of NaCl by KCl , CaCl 2 , and MgCl 2 on properties of mixed gelation from myofibrillar protein and Flammulina velutipes protein

The effects of substitution of sodium chloride (NaCl) by chloride salt mixtures (KCl, CaCl2, and MgCl2) with different formulas on quality characteristics of mixed protein system containing 80% myofibrillar protein (MP) and 20% Flammulina velutipes protein (FVP) were investigated in this study. The addition of chloride salts (KCl, CaCl2, and MgCl2) into a reduced-sodium (0.3 M NaCl) mixed gel system, increased the gel properties, and network structure of the MP-FVP gel, which might be attributed to the increase in protein solubility and rheological properties. The examination of the turbidity, particle size, zeta potential, UV spectroscopy, and Fourier transform infrared spectroscopy indicated that the protein molecules were obviously aggregated, that the electrostatic interaction was weakened, that the hydrophobic interaction and β-sheet content was increased. The results showed that when KCl, CaCl2, and MgCl2 were used to replace NaCl at 35, 10, and 5%, respectively, the gel properties reached the maximum. Practical applications This study evaluated the effects of different types of sodium salt substitution on the structural properties of proteins and the structural properties of mixed myofibrillar protein and Flammulina velutipes protein gels. The results revealed that the mixed protein molecules apparently aggregated under different replacement of KCl, CaCl2, and MgCl2 (i.e., 35, 10, and 5%). The hydrophobicity and β-sheet content significantly increased, while the electrostatic interaction decreased, leading to enhanced mixed gel properties. The results indicated the different replacements of sodium salts could improve the gels characteristics, which may be a guide for the future production of low-salt meat products.

Evolution of the SARS-CoV-2 spike protein in the human host

Recently emerged variants of SARS-CoV-2 contain in their surface spike glycoproteins multiple substitutions associated with increased transmission and resistance to neutralising antibodies. We have examined the structure and receptor binding properties of spike proteins from the B.1.1.7 (Alpha) and B.1.351 (Beta) variants to better understand the evolution of the virus in humans. Spikes of both variants have the same mutation, N501Y, in the receptor-binding domains. This substitution confers tighter ACE2 binding, dependent on the common earlier substitution, D614G. Each variant spike has acquired other key changes in structure that likely impact virus pathogenesis. The spike from the Alpha variant is more stable against disruption upon binding ACE2 receptor than all other spikes studied. This feature is linked to the acquisition of a more basic substitution at the S1-S2 furin site (also observed for the variants of concern Delta, Kappa, and Omicron) which allows for near-complete cleavage. In the Beta variant spike, the presence of a new substitution, K417N (also observed in the Omicron variant), in combination with the D614G, stabilises a more open spike trimer, a conformation required for receptor binding. Our observations suggest ways these viruses have evolved to achieve greater transmissibility in humans.

Protein c-phycocyanin, structure, physicochemical and biological properties, methods of extraction

Protein c-phycocyanin, structure, physicochemical and biological properties, methods of extraction

CRESSP: a comprehensive pipeline for prediction of immunopathogenic SARS-CoV-2 epitopes using structural properties of proteins.

The development of autoimmune diseases following SARS-CoV-2 infection, including multisystem inflammatory syndrome, has been reported, and several mechanisms have been suggested, including molecular mimicry. We developed a scalable, comparative immunoinformatics pipeline called cross-reactive-epitope-search-using-structural-properties-of-proteins (CRESSP) to identify cross-reactive epitopes between a collection of SARS-CoV-2 proteomes and the human proteome using the structural properties of the proteins. Overall, by searching 4911245 proteins from 196352 SARS-CoV-2 genomes, we identified 133 and 648 human proteins harboring potential cross-reactive B-cell and CD8+ T-cell epitopes, respectively. To demonstrate the robustness of our pipeline, we predicted the cross-reactive epitopes of coronavirus spike proteins, which were recognized by known cross-neutralizing antibodies. Using single-cell expression data, we identified PARP14 as a potential target of intermolecular epitope spreading between the virus and human proteins. Finally, we developed a web application (https://ahs2202.github.io/3M/) to interactively visualize our results. We also made our pipeline available as an open-source CRESSP package (https://pypi.org/project/cressp/), which can analyze any two proteomes of interest to identify potentially cross-reactive epitopes between the proteomes. Overall, our immunoinformatic resources provide a foundation for the investigation of molecular mimicry in the pathogenesis of autoimmune and chronic inflammatory diseases following COVID-19.

Investigation of Roles of TaTALE Genes during Development and Stress Response in Bread Wheat.

The three amino acid loop extension (TALE) genes of the homeobox superfamily are responsible for numerous biological functions in plants. Herein, we identified a total of 72 TaTALE genes in the allohexaploid genome of bread wheat (Triticum aestivum L.) and performed a comprehensive investigation for gene and protein structural properties, phylogeny, expression patterns, and multilevel gene regulations. The identified TaTALE proteins were further classified into two groups, TaBLHs and TaKNOXs, which were tightly clustered into the phylogeny. The negative Ka/Ks ratio of duplicated genes suggested purifying selection pressure with confined functional divergence. Various signature domains and motifs were found conserved in both groups of proteins. The occurrence of diverse cis-regulatory elements and modulated expression during various developmental stages and in the presence of abiotic (heat, drought, salt) and two different fungal stresses suggested their roles in development and stress response, as well. The interaction of TaTALEs with the miRNAs and other development-related homeobox proteins also suggested their roles in growth and development and stress response. The present study revealed several important aspects of TaTALEs that will be useful in further functional validation of these genes in future studies.

Prediction of structural alphabet protein blocks using data mining

3D protein structures determine proteins' biological functions. The 3D structure of the protein backbone can be approximated using the prototypes of local protein conformations. Sets of these prototypes are called structural alphabets (SAs). Amongst several approaches to the prediction of 3D structures from amino acid sequences, one approach is based on the prediction of SA prototypes for a given amino acid sequence. Protein Blocks (PBs) is the most known SA, and it is composed of 16 prototypes of five consecutive amino acids which were identified as optimal prototypes considering the ability to correctly approximate the local structure and the prediction accuracy of prototypes from an amino acid sequence. We developed models for PBs prediction from sequence information using different data mining approaches and machine learning algorithms. Besides the amino acid sequences, the results of the following tools were used to train the models: the Spider3 predictor of protein structure properties, several predictors of the protein's intrinsically disordered regions, and a tool for finding repeats in amino acid sequences. The highest accuracy of the constructed models is 80%, which is a significant improvement compared to the previous best available prediction, whose accuracy was 61%. Analyzing the models constructed by applying different algorithms, it was noticed that the significance of input attributes differs among the models constructed by algorithms. Using the information about amino acids belonging to intrinsically disordered regions and repeats improves the precision of prediction for some PBs using the CART classification algorithm, while this is not the case with the C5.0 classification algorithm. Improved prediction approaches can have interesting applications in protein structural model approaches or computational protein design.

Molecular modeling of the interface of an egg yolk protein-based emulsion

Many food emulsions are stabilized by functional egg yolk biomolecules, which act as surfactants at the oil/water interface. Detailed experimental studies on egg yolk emulsifying properties have been largely hindered due to the difficulty in isolating individual chemical species. Therefore, this work presents a molecular model of an oil/water interfacial system where the emulsifier is one of the most surface-active proteins from the egg yolk low-density lipoproteins (LDL), the so-called Apovitellenin I. Dissipative particle dynamics (DPD) was here adopted in order to simulate large systems over long time scales, when compared with full-atom molecular dynamics (MD). Instead of a manual assignment of the DPD simulation parameters, a fully automated coarse-graining procedure was employed. The molecular interactions used in the DPD system were determined by means of a parameter calibration based on matching structural data from atomistic MD simulations. Despite the little availability of experimental data, the model was designed to test the most relevant physical properties of the protein investigated. Protein structural and dynamics properties obtained via MD and DPD were compared highlighting advantages and limits of each molecular technique. Promising results were achieved from DPD simulations of the oil/water interface. The proposed model was able to properly describe the protein surfactant behavior in terms of interfacial tension decrease at increasing protein surface concentration. Moreover, the adsorption time of a free protein molecule was estimated and, finally, an LDL-like particle adsorption mechanism was qualitatively reproduced.

Optimization Using Response Surface Methodology of Amylolytic Capacity of Maize Atp-Y and Coca-Sr Varieties: In Vitro Digestibility Capacity, Protein Structure, Nutritional, Antinutritional, Physical, Antioxdant and Functionnal Properties of Optimal Sample

Optimization Using Response Surface Methodology of Amylolytic Capacity of Maize Atp-Y and Coca-Sr Varieties: In Vitro Digestibility Capacity, Protein Structure, Nutritional, Antinutritional, Physical, Antioxdant and Functionnal Properties of Optimal Sample

Non-covalent interaction between pea protein isolate and catechin: effects on protein structure and functional properties.

The aim of this study was to investigate the effects of non-covalent interaction between pea protein isolate (PPI) and different concentrations (0.05-0.25%, w/v) of catechin (CT) on the structural and functional characteristics of protein. CT introduction changed the PPI secondary and tertiary structures. Hydrophobic actions were the major interaction forces of PPI-CT complexes. Surface hydrophobicity of PPI decreased as many hydrophobic groups were exposed to a more hydrophilic environment. The polyphenol bound equivalents, emulsifying properties, foaming stability, and antioxidant activities of PPI were improved after non-covalently interacting with CT. Therefore, the addition of CT to PPI is an effective approach to improve its structural and functional properties. These results provide a reference for using PPI-polyphenol complexes to develop functional food ingredients.

An integrated protein structure fitness scoring approach for identifying native-like model structures

The structural information of a protein is pivotal to comprehend its functions, protein–protein and protein–ligand interactions. There is a widening gap between the number of known protein sequences and that of experimentally determined structures. The protein structure prediction has emerged as an efficient alternative to deliver the reliable structural information of proteins. However, it remains a challenge to identify the best model among the many predicted by one or a few structure prediction methods. Here we report ProFitFun-Meta, a neural network based pure single model scoring method for assessing the quality of predicted model structures by an effective combination structural information of various backbone dihedral angle and residue surface accessibility preferences of amino acid residues with other spatial properties of protein structures. The performance of ProFitFun-Meta was validated and benchmarked against current state-of-the-art methods on the extensive datasets, comprising a Test Dataset (n = 26,604), an External Dataset (n = 40,000), and CASP14 Dataset (n = 1200). The comprehensive performance evaluation of ProFitFun-Meta demonstrated its reliability and efficiency in terms of Spearman’s (ρ) and Pearson’s (r) correlation coefficients, GDT-TS loss (g), and absolute loss (d). An improved performance over the current state-of-the-art methods and leading performers of CASP14 experiment in quality assessment category demonstrated its potential to become an integral component of computational pipelines for protein modeling and design. The minimal dependencies, high computational efficiency, and portability to various Linux and Windows OS provide an additional edge to ProFitFun-Meta for its easy implementation and applications in various regimes of computational protein folding.

Compound distribution, structural analysis and nanomechanical properties of nanofibers loaded with high-oleic palm oil nanoemulsions for packaging application

The effect of the HOPO concentration on the morphology, fiber diameter, oil load and distribution, protein structure, protein-oil colocalization, and nanomechanical properties of the NFs were evaluated. We obtained smooth and defect-free NFs with diameters in range of 77–94 nm. Fourier-transform infrared spectroscopy was used as a reliable method to confirm oil load and protein structure after electrospinning. β-turn, β-sheet, α-helix, and triple helical structures were quantified. Confocal laser scanning microscopy was used to analyze colocalization, and results revealed a high distribution of NE droplets along the NFs and high oil-protein colocalization (overlap coefficient of ~ 0.63). The nanomechanical properties of the NE-loaded NFs demonstrated that at higher HOPO concentrations, the elastic modulus decreased. Likewise, homogeneity and synergy between compounds were observed. The adhesion properties of NE-loaded NFs were associated with their sticky surface, which was attributed to presence of HOPO. The NE-loaded NFs presented suitable physical properties for edible packaging.

Effects of three treatments on protein structure and gel properties of Perccottus glenii myofibrillar protein

Abstract In order to improve Perccottus glenii myofibrillar protein (MP) gel properties, three treatments were evaluated: ultrasonic, transglutaminase (TGase) and combined ultrasonic-transglutaminase treatments. Combined ultrasonic-transglutaminase treatment altered protein structure and gel properties most dramatically. As compared with untreated control group protein, treated protein gels possessed decreased sulfhydryl group content and increases in water holding capacity, whiteness value and hydrophobic interactions that increased gel strength value by up to 3.79 times that of untreated protein gel. Protein structural and Differential scanning calorimetry (DSC) analyses revealed that combined ultrasonic-TGase treatment increased both protein thermal denaturation temperature and UV absorbance (as compared to control and other treatment groups) that supported formation of MP gels with desirable characteristics. These results provide a theoretical basis for development of superior MP gels to promote greater utilization of this fish protein resource by the food industry.