Structural Characterization Of Proteins Research Articles

Structural Transitions of Papain-like Cysteine Proteases: Implications for Sensor Development.

The significant role of papain-like cysteine proteases, including papain, cathepsin L and SARS-CoV-2 PLpro, in biomedicine and biotechnology makes them interesting model systems for sensor development. These enzymes have a free thiol group that is suitable for many sensor designs including strong binding to gold nanoparticles or low-molecular-weight inhibitors. Focusing on the importance of the preservation of native protein structure for inhibitor-binding and molecular-imprinting, which has been applied in some efficient examples of sensor development, the aim of this work was to examine the effects of the free-thiol-group's reversible blocking on papain denaturation that is the basis of its activity loss and aggregation. To utilize biophysical methods common in protein structural transitions characterization, such as fluorimetry and high-resolution infrared spectroscopy, low-molecular-weight electrophilic thiol blocking reagent S-Methyl methanethiosulfonate (MMTS) was used in solution. MMTS binding led to a two-fold increase in 8-Anilinonaphthalene-1-sulfonic acid fluorescence, indicating increased hydrophobic residue exposure. A more in-depth analysis showed significant transitions on the secondary structure level upon MMTS binding, mostly characterized by the lowered content of α-helices and unordered structures (either for approximately one third), and the increase in aggregation-specific β-sheets (from 25 to 52%) in a dose-dependant manner. The recovery of this inhibited protein showed that reversibility of inhibition is accompanied by reversibility of protein denaturation. Nevertheless, a 100-fold molar excess of the inhibitor led to the incomplete recovery of proteolytic activity, which can be explained by irreversible denaturation. The structural stability of the C-terminal β-sheet rich domain of the papain-like cysteine protease family opens up an interesting possibility to use its foldamers as a strategy for sensor development and other multiple potential applications that rely on the great commercial value of papain-like cysteine proteases.

Structure analysis and molecular docking studies of laccase from “Bacillus licheniformis NS2324”

Laccase in prokaryotes have enormous application as biocatalysts. Nevertheless, very few laccases have been characterized structurally till date. Recently, a prokaryotic laccase from“Bacillus licheniformis NS2324” have been was cloned and expresses in E. coli. The present research was focused on in silicostructure prediction and characterization of cloned laccase gene isolated from “B. licheniformisNS2324”.In this study various homology modeling servers were used to predict the protein structure of the cloned laccase. Total 17 models were predicted with servers like SWISS-MODEL, ModWeb, Geno3D,I-TASSER,HHPRED using different template structures. All of these models were further validated through PROTSAV, PROCHECK and SAVES server.The best scoring model predicted by SWISS MODEL was selected and submitted in PMDB database. Selected and submitted protein structure was used further for in silico protein structure characterization and docking studies on leather dyes. It was found that all the 33 tested acid leather dyes were docked perfectly to laccase structure with good binding affinity. Acid orange 56 was having highest affinity of − 9.6 kcal mol−1for binding site. A binding affinity of − 9.3 kcal mol−1 and − 9.2 kcal mol−1 was achieved by docking acid red 97 and acid yellow 110 with laccase respectively. The docking studies were further validated by wet laboratory dye decolorization studies which showed a maximum of 96.26 ± 2.51% of (acid orange 56) and a minimum of 61.87 ± 1.30% (acid red 18) This is, to the best of our knowledge, the first study that reports model building from extracellular B. licheniformis laccase and docking with acid leather dyes.

Exploiting Interactions between Polyoxometalates and Proteins for Applications in (Bio)chemistry and Medicine

AbstractThe specific interactions of anionic metal‐oxo clusters, known as polyoxometalates (POMs), with proteins can be leveraged for a wide range of analytical and biomedical applications. For example, POMs have been developed as selective catalysts that can induce protein modifications and have also been shown to facilitate protein crystallization, both of which are instrumental in the structural characterization of proteins. POMs can also be used for selective protein separation and enzyme inhibition, which makes them promising therapeutic agents. Hence, understanding POM‐protein interactions is essential for the development of POM‐based materials and their implementation in several fields. In this Review we summarize in detail the key insights that have been gained so far on POM‐protein interactions. Emphasis is also given to hybrid POMs functionalized with organic ligands to prompt further research in this direction owing to the promising recent results on tuning POM‐protein interactions through POM functionalization.

Exploiting Interactions between Polyoxometalates and Proteins for Applications in (Bio)chemistry and Medicine.

The specific interactions of anionic metal-oxo clusters, known as polyoxometalates (POMs), with proteins can be leveraged for a wide range of analytical and biomedical applications. For example, POMs have been developed as selective catalysts that can induce protein modifications and have also been shown to facilitate protein crystallization, both of which are instrumental in the structural characterization of proteins. POMs can also be used for selective protein separation and enzyme inhibition, which makes them promising therapeutic agents. Hence, understanding POM-protein interactions is essential for the development of POM-based materials and their implementation in several fields. In this Review we summarize in detail the key insights that have been gained so far on POM-protein interactions. Emphasis is also given to hybrid POMs functionalized with organic ligands to prompt further research in this direction owing to the promising recent results on tuning POM-protein interactions through POM functionalization.

Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data.

The structural characterization of proteins with a disorder requires a computational approach backed by experiments to model their diverse and dynamic structural ensembles. The selection of conformational ensembles consistent with solution experiments of disordered proteins highly depends on the initial pool of conformers, with currently available tools limited by conformational sampling. We have developed a Generative Recurrent Neural Network (GRNN) that uses supervised learning to bias the probability distributions of torsions to take advantage of experimental data types such as nuclear magnetic resonance J-couplings, nuclear Overhauser effects, and paramagnetic resonance enhancements. We show that updating the generative model parameters according to the reward feedback on the basis of the agreement between experimental data and probabilistic selection of torsions from learned distributions provides an alternative to existing approaches that simply reweight conformers of a static structural pool for disordered proteins. Instead, the biased GRNN, DynamICE, learns to physically change the conformations of the underlying pool of the disordered protein to those that better agree with experiments.

Water filling of rapidly salted separated egg yolks: Characterization of water migration, aggregation behavior and protein structure

Water filling occurs during the rapid salting of separated egg yolks. The purpose of this study was to investigate the changes in water migration, protein aggregation and structures of the separated egg yolks salted with 20% salt solution over 24 hours to understand the principles of this phenomenon. The results showed that water filling occurred within 12 h. The hardness of the salted egg yolk increased significantly within approximately 0−6 h and then decreased significantly. The springiness and cohesiveness of the egg yolk did not change significantly during salting. With the appearance of water filling, the T23, A23, soluble protein content, free sulfhydryl content, β-turns, α-helices and maximum fluorescence intensity (FImax) increased; the T22, A22, disulfide bonds, β-sheets, irregular curls, maximum emission wavelength (λmax) and average particle sizes decreased. This work showed that water filling enhanced the hydrogen bonding between proteins and water and inhibited protein aggregation.

The Conformational Changes of Bovine Serum Albumin at the Air/Water Interface: HDX-MS and Interfacial Rheology Analysis.

The characterization and dynamics of protein structures upon adsorption at the air/water interface are important for understanding the mechanism of the foamability of proteins. Hydrogen-deuterium exchange, coupled with mass spectrometry (HDX-MS), is an advantageous technique for providing conformational information for proteins. In this work, an air/water interface, HDX-MS, for the adsorbed proteins at the interface was developed. The model protein bovine serum albumin (BSA) was deuterium-labeled at the air/water interface in situ for different predetermined times (10 min and 4 h), and then the resulting mass shifts were analyzed by MS. The results indicated that peptides 54-63, 227-236, and 355-366 of BSA might be involved in the adsorption to the air/water interface. Moreover, the residues L55, H63, R232, A233, L234, K235, A236, R359, and V366 of these peptides might interact with the air/water interface through hydrophobic and electrostatic interactions. Meanwhile, the results showed that conformational changes of peptides 54-63, 227-236, and 355-366 could lead to structural changes in their surrounding peptides, 204-208 and 349-354, which could cause the reduction of the content of helical structures in the rearrangement process of interfacial proteins. Therefore, our air/water interface HDX-MS method could provide new and meaningful insights into the spatial conformational changes of proteins at the air/water interface, which could help us to further understand the mechanism of protein foaming properties.

Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning

While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue–residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.

Formation of Nε-Carboxymethyl-Lysine and Nε-Carboxyethyl-Lysine in Heated Fish Myofibrillar Proteins with Glucose: Relationship with Its Protein Structural Characterization.

The formation of advanced glycation end products (AGEs), including Nε-carboxymethyl-lysine (CML) and Nε-carboxyethyl-lysine (CEL), in a fish myofibrillar protein and glucose (MPG) model system at 80 °C and 98 °C for up to 45 min of heating were investigated. The characterization of protein structures, including their particle size, ζ-potential, total sulfhydryl (T-SH), surface hydrophobicity (H0), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Fourier transform infrared spectroscopy (FTIR), were also analyzed. It was found that the covalent binding of glucose and myofibrillar protein at 98 °C promoted protein aggregation when compared with the fish myofibrillar protein (MP) heated alone, and this aggregation was associated with the formation of disulfide bonds between myofibrillar proteins. Furthermore, the rapid increase of CEL level with the initial heating at 98 °C was related to the unfolding of fish myofibrillar protein caused by thermal treatment. Finally, correlation analysis indicated that the formation of CEL and CML had a significantly negative correlation with T-SH content (r = -0.68 and r = -0.86, p ≤ 0.011) and particle size (r = -0.87 and r = -0.67, p ≤ 0.012), but was weakly correlated with α-Helix, β-Sheet and H0 (r2 ≤ 0.28, p > 0.05) during thermal treatment. Overall, these findings provide new insights into the formation of AGEs in fish products based on changes of protein structure.

Differentiating R5l and wildtype tau using atomic force microscopy.

Tau is a microtubule associated protein found in neuronal axons which regulates microtubule assembly and organization. Aberrant tau polymerization into neurofibrillary tangles is highly correlated with neurodegenerative diseases such as Alzheimer's disease. As a natively unstructured protein, it has eluded traditional protein structural characterization methods such as crystallography, but analysis with atomic force microscopy (AFM) offers a novel method to interrogate tau structure. When tau is adsorbed on the AFM tip and onto a flat mica surface, the N-terminal projection domains of the protein extend outwards to form polyelectrolyte brushes on both the tip and surface, allowing measurement of forces between the projection domains of the opposing layers of tau as the tip approaches the surface.

Heteroprotein complex between soy protein isolate and lysozyme: Protein conformation, lysozyme activity, and structural characterization

Heteroprotein complexes are formed by electrostatic interactions of oppositely charged proteins in a purely aqueous environment. Understanding the relationship between their structural and functional properties will contribute to their tailor-made applications. Therefore, this study investigated the protein conformation, assembling structure, and enzyme activity of soy protein isolate/lysozyme (SPI/LYS) complexes at mass ratios of 2:1 (soluble complex) and 1:1.3 (stoichiometric ratio). Electrostatic complexation increased the surface hydrophobicity of complexes. Their surface hydrophobicity decreased with increasing NaCl concentrations and reached the theoretical values at the critical salt concentration of 200 mM NaCl. Electrostatic complexation did not decrease the LYS activity (∼43,000 units/mg). SPI/LYS complexes exhibited flocculated structures in which the two proteins were unevenly distributed; these were typical amorphous complexes. High dilution disassembled these complexes over 5 μm into particles of ∼100 nm, and NaCl reduced the size of these particles. Immobilized water was detected in the complexes formed by particle flocculation.

Molecular cloning, expression, mRNA secondary structure and immunological characterization of mussel foot proteins (Mfps) (Mollusca: Bivalvia)

The macroscale production of mussel foot proteins (Mfps) in the expression system has not succeeded to date. The principal reasons for this are low levels of expression and yield of Mfps, lack of post-translational modifications (PTMs), and immunological toxic effects on the host system. Identification of post-translational modification sites, suitable expression hosts, and immunological responses through an experimental approach is very costly and time-consuming. However, in the present study, in silico post-translation modification, antigenicity, allergenicity, and the immunological reaction of all available Mfps were characterized. Furthermore, all Mfps were codon optimized in three different expression systems to determine the best expression host. Finally, we performed the in-silico cloning of all codon-optimized Mfps in a suitable host (E. coli K12, pET28a(+) vector) and analyzed the secondary structure of mRNA and its structural stability. Among the 78 Mfps, six fps are considered potential allergenic proteins, six fps are considered non-allergenic proteins, and all other fps are probably allergenic. High antigenicity was observed in bacterial cells as compared to yeast and tumor cells. Nevertheless, the predicted expression of Mfps in a bacterial host is higher than in other expression hosts. Important to note that all Mfps showed significant immunological activity in the human system, and we concluded that these antigenic, allergenic, and immunological properties are directly correlated with their amino acid composition. The study’s major goal is to provide a comprehensive understanding of Mfps and aid in the future genetic engineering and expression of Mfps and its diverse applications in different fields. Communicated by Ramaswamy H. Sarma

Rapid Assessment of Membrane Protein Quality by Fluorescent Size Exclusion Chromatography.

During membrane protein structural elucidation and biophysical characterization, it is common to trial numerous protein constructs containing different tags, truncations, deletions, fusion partner insertions, and stabilizing mutations to find one that is not aggregated after extraction from the membrane. Furthermore, buffer screening to determine the detergent, additive, ligand, or polymer that provides the most stabilizing condition for the membrane protein is an important practice. The early characterization of membrane protein quality by fluorescent size exclusion chromatography provides a powerful tool to assess and rank different constructs or conditions without the requirement for protein purification, and this tool also minimizes the sample requirement. The membrane proteins must be fluorescently tagged, commonly by expressing them with a GFP tag or similar. The protein can be solubilized directly from whole cells and then crudely clarified by centrifugation; subsequently, the protein is passed down a size exclusion column, and a fluorescent trace is collected. Here, a method for running FSEC and representative FSEC data on the GPCR targets sphingosine-1-phosphate receptor (S1PR1) and serotonin receptor (5HT2AR) are presented.

REVIEW ON PROTEIN FOOTPRINTING AS A TOOL IN STRUCTURAL BIOLOGY

Structural characterization of proteins is fundamental for understanding their functions and interactions within cellular environments. Protein footprinting has emerged as a powerful and versatile technique in structural biology, providing valuable insights into protein structure, dynamics, and conformational changes. This study comprehensively explores the principles, methodologies, and applications of protein footprinting as an indispensable tool in structural biology. Protein footprinting encompasses a range of innovative techniques, including hydroxyl radical footprinting, mass spectrometry-based footprinting, and chemical footprinting, each offering unique advantages for probing different aspects of protein structure. The study elucidates the underlying principles of these methods, discussing the mechanisms by which protein-footprinting agents interact with amino acid residues and elucidate structural details. The application of protein footprinting in studying protein-protein interactions, ligand binding, and conformational changes is highlighted through a detailed examination of key studies and experimental approaches. The review emphasizes the versatility of protein footprinting in investigating diverse protein systems, from small globular proteins to large multi-subunit complexes. Furthermore, the integration of protein footprinting with other structural biology techniques, such as X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy, is explored to showcase the complementary nature of these approaches in achieving a comprehensive understanding of protein structure and function. The study addresses recent advancements and technological innovations in protein footprinting methodologies, including advancements in mass spectrometry instrumentation and data analysis strategies. Additionally, it discusses challenges associated with the technique, such as data interpretation and accessibility, and proposes future directions for overcoming these hurdles. Protein footprinting stands as a valuable tool in the structural biologist’s arsenal, providing unique perspectives on protein structure and dynamics. As the field continues to evolve, with ongoing refinements in methodologies and expanded applications, protein footprinting is poised to play a pivotal role in unraveling the complexities of biological macromolecules. This study serves as a comprehensive resource for researchers and practitioners seeking an in-depth understanding of protein footprinting and its contributions to advancing structural biology.

Abstract P003: Computational identification of ovarian cancer candidate genes with mutated protein structures caused by missense variants

Abstract Ovarian cancer is one of the leading killers in the US for women. The American Cancer Society (ACR) ranks ovarian cancer as the fifth leading cause of cancer deaths among women. This cancer is hereditary, with higher risks if the patient has more relatives who have had ovarian cancer before. The Cancer Genome Atlas (TCGA) is a joint-effort project by NCI and NHGRI that generates genomic data for the cancer patients and matches normal data samples with these patients. Missense mutations are single nucleotide polymorphisms (SNPs) in which the amino acids are changed. A missense variant could disrupt protein structures; thus the function of the disrupted protein is altered. In this study, we investigated genes with high expression levels in the TCGA RNA-seq dataset by characterizing protein structure change patterns of candidate genes due to missense mutations in association with ovarian cancer. We also analyzed the association of these genes with ovarian cancer prognosis. We aim to select genes that have pathogenic consequences. We selected 44 genes with the highest expression values based on TCGA ovarian cancer RNA-seq data. We then retrieved protein sequences from the Ensembl BioMart database and missense mutation annotation information from cBioPortal for 44 input genes. Specifically, the missense mutation dataset, which is projected by the Pan-Cancer Analysis of Whole Genomes, was retrieved from cBioPortal. We then used the Phyre2 database to predict the 3-D structures of the wild and mutated type genes to identify structural changes. However, some genes were not suitable for Phyre2 analysis. For example, RPL41 was not long enough for analysis with Phyre2 as it only had 25 amino acids whereas Phyre2 required 30. TMSL3 (TMSB4XP8) is a pseudogene not found in both NCBI and AlphaFold. We then searched DrugBank for 42 genes with the predicted protein structure changes by Phyre2 to identify drug targets. We also performed Kaplan-Meier survival analysis to further evaluate the clinical consequences of the candidate genes. Our preliminary results show 26 genes that have drug targets and several of them have been identified to either decrease or increase the survival rate when the expression is high in ovarian cancer patients. This indicates that the highly expressed genes with protein structure changes due to missense mutations could be potential biomarkers for treating ovarian cancer. The functional annotation study could further validate ovarian cancer association for our prioritized gene list. In the future, we also plan to compare prediction results between genders and race groups. Our results could guide medical researchers in prioritizing drug targets and developing better treatment strategies for ovarian cancer. Our approach in prioritizing candidate genes is applicable to other cancers as well, and we plan to develop bioinformatic pipelines for automatically predicting candidate genes with significant effect on patient survival for any cancer type. Citation Format: Ian W. Hou, Yongsheng Bai. Computational identification of ovarian cancer candidate genes with mutated protein structures caused by missense variants. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P003.

Convolutional ProteinUnetLM competitive with long short-term memory-based protein secondary structure predictors.

The protein secondary structure (SS) prediction plays an important role in the characterization of general protein structure and function. In recent years, a new generation of algorithms for SS prediction based on embeddings from protein language models (pLMs) is emerging. These algorithms reach state-of-the-art accuracy without the need for time-consuming multiple sequence alignment (MSA) calculations. Long short-term memory (LSTM)-based SPOT-1D-LM and NetSurfP-3.0 are the latest examples of such predictors. We present the ProteinUnetLM model using a convolutional Attention U-Net architecture that provides prediction quality and inference times at least as good as the best LSTM-based models for 8-class SS prediction (SS8). Additionally, we address the issue of the heavily imbalanced nature of the SS8 problem by extending the loss function with the Matthews correlation coefficient, and by proper assessment using previously introduced adjusted geometric mean (AGM) metric. ProteinUnetLM achieved better AGM and sequence overlap score than LSTM-based predictors, especially for the rare structures 310-helix (G), beta-bridge (B), and high curvature loop (S). It is also competitive on challenging datasets without homologs, free-modeling targets, and chameleon sequences. Moreover, ProteinUnetLM outperformed its previous MSA-based version ProteinUnet2, and provided better AGM than AlphaFold2 for 1/3 of proteins from the CASP14 dataset, proving its potential for making a significant step forward in the domain. To facilitate the usage of our solution by protein scientists, we provide an easy-to-use web interface under https://biolib.com/SUT/ProteinUnetLM/.

Modification mechanism of protein in rice adjuncts upon extrusion and its effects on nitrogen conversion during mashing

The traditional production of wort with adjunct-introduced was achieved by double mashing procedure, which hindered the utilization of proteins in adjunct and led to a deficiency of nitrogen in wort. In this study, the modification mechanism of the extrusion pretreatment on the structure characterization of rice flour protein was investigated. The decoction mashing procedure was performed to enhance the nitrogen conversion of the extruded rice adjunct. Decreased solubility along with disrupted secondary and tertiary structures of rice protein were observed after extrusion. As a result, the total nitrogen, free amino nitrogen, and free amino acids content of wort with extruded rice adjunct-introduced were improved by 23.28 %, 34.67 %, and 7.33 %, respectively, which could be verified by the electrophoretic patterns of the wort protein. The application of extrusion as a pretreatment of adjuncts can promote the protein availability of adjuncts in the decoction mashing stage.

Improvement of techno-functional properties of acidic subunit from amaranth 11S globulin modified by bioactive peptide insertions

BackgroundProteins are often used in foods as ingredients to provide desirable appearance, texture, or stability. It is commonly used as gelling, emulsifiers, foaming, and thickeners. An awareness of its properties can be achieved by exploring the relationship between structural conformation adopted by a protein and its techno-functional properties. Here, we analyzed the techno-functional properties of the acidic subunit from amarantin AAC and modified variants AACM.1 and AACM.3 with bioactive peptides (VY 4x) insertion. The proteins were expressed at the fermenter level using Escherichia coli. The techno-functional properties were analyzed at different pH and compared with fresh white egg and sodium caseinate. Moreover, the structural characterization of proteins was done through infrared and Raman spectroscopies. ResultsThe techno-functional properties of all proteins studied were better at pH 7.5. Solubility and emulsifying activity of AAC and AACM.3 were similar to sodium caseinate, at pH 5. AACM.3 showed similar foaming stability to the white egg, while at pH 7.5, both modified proteins showed higher foaming stability and were equivalent to the white egg. Spectroscopic techniques showed conformational differences between AAC and modified variants. AACM.3 showed higher unordered secondary content (59.6%) followed by AACM.1 (39.6%), suggesting AACM.3 adopted a structure as a molten globule by modifications done, which enhance its techno-functional properties. ConclusionsThe biopeptide insertions promote conformational changes, such as structure molten globule (AACM.3) and compact structure (AACM.1). In both cases, the techno-functional properties were improved, it could be an advantage focusing on plant protein ingredient development to novel food product creation.How to cite: Cruz-Morán Y, Morales-Camacho JI, Delgado-Macuil R, et al. Improvement of techno-functional properties of acidic subunit from amaranth 11S globulin modified by bioactive peptide insertions. Electron J Biotechnol 2023;61. https://doi.org/10.1016/j.ejbt.2022.11.003.

Label-Free Surface-Enhanced Raman Spectroscopic Analysis of Proteins: Advances and Applications.

Surface-enhanced Raman spectroscopy (SERS) is powerful for structural characterization of biomolecules under physiological condition. Owing to its high sensitivity and selectivity, SERS is useful for probing intrinsic structural information of proteins and is attracting increasing attention in biophysics, bioanalytical chemistry, and biomedicine. This review starts with a brief introduction of SERS theories and SERS methodology of protein structural characterization. SERS-active materials, related synthetic approaches, and strategies for protein-material assemblies are outlined and discussed, followed by detailed discussion of SERS spectroscopy of proteins with and without cofactors. Recent applications and advances of protein SERS in biomarker detection, cell analysis, and pathogen discrimination are then highlighted, and the spectral reproducibility and limitations are critically discussed. The review ends with a conclusion and a discussion of current challenges and perspectives of promising directions.

The Spatial Distribution Patterns, Physicochemical Properties, and Structural Characterization of Proteins in Oysters (Crassostrea hongkongensis).

Protein content, a vital component determining the nutritional quality of oysters, is unevenly distributed in different parts of oyster. In this study, the spatial distribution (visceral mass, mantle, gill, and adductor) patterns and structural characteristics of proteins, including water–soluble proteins (WSP), salt–soluble proteins (SSP), acid–soluble proteins (ASP) and alkali–soluble proteins (ALSP) of oysters (Crassostrea hongkongensis) were investigated with the amino acid analyzer, circular dichroism spectroscopy (CD), fourier transform infrared spectroscopy (FTIR), and fluorescence spectroscopy. The results showed that oyster proteins were mainly distributed in the visceral mass and mantle. The protein composition was WSP, SSP, ALSP, and ASP in descending order, which conformed to the ideal amino acid pattern. Variations in secondary structure, molecular weight distribution, and thermal denaturation temperatures of the oyster proteins were observed. SSP had wider bands (16–270 kDa) than those of ASP (30–37 kDa) and ALSP (66–270 kDa). Among the four proteins, the SSP of the mantle showed the highest thermal stability (87.4 °C), while ALSP of the adductor muscle had the lowest the lowest the peak denaturation temperature (Tm) (53.8 °C). The proportions of secondary structures in oyster proteins were different, with a higher proportion of solid protein β–folds, and the exposure of aromatic amino acid residues and disulfide bonds and the microenvironment in which they were located were also different.