Protein Quaternary Structure Research Articles

Mercury in dental amalgam: a risk analysis

Mercury is a highly potent cell toxin with effects on human and animal nervous systems. Mercury vapour released from dental amalgam is the predominant source of mercury in the human adult and foetal central nervous system in populations of developed countries. Only in small populations with high consumption of methyl mercury containing fish can the contribution from fish consumption reach or surpass that of amalgam fillings. The most severe health risk is that of interference with foetal and child brain development. This effect of mercury vapour exposure has been demonstrated in animal experiments on monkeys and rats and in nerve cell cultures at nanomolar concentrations. The effect is also supported by epidemiological studies on women occupationally exposed to mercury vapour during pregnancy. However, there is no data permitting an assessment of dose-response relations for this effect in humans. In epidemiological studies on populations with occupational exposure to mercury vapour, subclinical effects on kidneys, the immune system, thyroid function, and CNS function have been observed at an exposure level equal to the upper range of the exposure range seen in amalgam bearers and measured as urine excretion rate of inorganic mercury. The cell toxic effect of mercury is likely to be based on the ability of mercury to modify protein tertiary and quaternary structure. As protein structure is genetically determined, there is ample scope for genetic polymorphism to manifest itself in varying sensitivity and reaction to mercury exposure. It is also likely that mercury exposure from dental amalgam exerts side effects like most potent pharmaceuticals. The clinical support for this assumption is reviewed. An incidence of side effects exceeding 10% is unlikely considering available epidemiological evidence. However, an incidence of 1% or below is highly probable. It is recommended that use of amalgam for dental restorations is abandoned and substituted with available less toxic material and that amalgam restorations in children and women of childbearing age should be avoided due to the potential risk of interference by mercury with brain development.

Metal-Templated Design of Chemically Switchable Protein Assemblies with High-Affinity Coordination Sites.

To mimic a hypothetical pathway for protein evolution, we previously tailored a monomeric protein (cyt cb562 ) for metal-mediated self-assembly, followed by re-design of the resulting oligomers for enhanced stability and metal-based functions. We show that a single hydrophobic mutation on the cyt cb562 surface drastically alters the outcome of metal-directed oligomerization to yield a new trimeric architecture, (TriCyt1)3. This nascent trimer was redesigned into second and third-generation variants (TriCyt2)3 and (TriCyt3)3 with increased structural stability and preorganization for metal coordination. The three TriCyt variants combined furnish a unique platform to 1) provide tunable coupling between protein quaternary structure and metal coordination, 2) enable the construction of metal/pH-switchable protein oligomerization motifs, and 3) generate a robust metal coordination site that can coordinate all mid-to-late first-row transition-metal ions with high affinity.

Metal‐Templated Design of Chemically Switchable Protein Assemblies with High‐Affinity Coordination Sites

AbstractTo mimic a hypothetical pathway for protein evolution, we previously tailored a monomeric protein (cyt cb562) for metal‐mediated self‐assembly, followed by re‐design of the resulting oligomers for enhanced stability and metal‐based functions. We show that a single hydrophobic mutation on the cyt cb562 surface drastically alters the outcome of metal‐directed oligomerization to yield a new trimeric architecture, (TriCyt1)3. This nascent trimer was redesigned into second and third‐generation variants (TriCyt2)3 and (TriCyt3)3 with increased structural stability and preorganization for metal coordination. The three TriCyt variants combined furnish a unique platform to 1) provide tunable coupling between protein quaternary structure and metal coordination, 2) enable the construction of metal/pH‐switchable protein oligomerization motifs, and 3) generate a robust metal coordination site that can coordinate all mid‐to‐late first‐row transition‐metal ions with high affinity.

Preservation of Quaternary Structure in Thermostable, Lyophilized Filovirus Glycoprotein Vaccines: A Search for Stability-Indicating Assays

The filoviruses Zaire ebolavirus (EBOV), Marburg marburgvirus (MARV), and Sudan ebolavirus (SUDV) are some of the most lethal infectious agents known. To date, the Zaire ebolavirus vaccine (ERVEBO®) is the only United States Food and Drug Administration (FDA) approved vaccine available for any species of filovirus. However, the ERVEBO® vaccine requires cold-chain storage not to exceed −60 °C. Such cold-chain requirements are difficult to maintain in low- and middle-income countries where filovirus outbreaks originate. To improve the thermostability of filovirus vaccines in order to potentially relax or eliminate these cold-chain requirements, monovalent subunit vaccines consisting of glycoproteins from EBOV, MARV, and SUDV were stabilized within amorphous disaccharide glasses through lyophilization. Lyophilized formulations and liquid controls were incubated for up to 12 weeks at 50 °C to accelerate degradation. To identify a stability-indicating assay appropriate for monitoring protein degradation and immunogenicity loss during these accelerated stability studies, filovirus glycoprotein secondary, tertiary, and quaternary structures and vaccine immunogenicity were measured. Size-exclusion chromatography was the most sensitive indicator of glycoprotein stability in the various formulations for all three filovirus immunogens. Degradation of the test vaccines during accelerated stability studies was reflected in changes in quaternary structure, which were discernible with size-exclusion chromatography. Filovirus glycoproteins in glassy lyophilized formulations retained secondary, tertiary, and quaternary protein structure over the incubation period, whereas the proteins within liquid controls both aggregated to form higher molecular weight species and dissociated from their native quaternary structure to form a variety of structurally-perturbed lower molecular weight species.

Therapeutically Targeted Destabilization of the Quaternary Structure of the Spike Protein in the Dominant G614 Strain of SARS-CoV-2.

The evolutionary change of SARS-CoV-2 is of the outmost concern. With a more stable phenotype, mutation D614G has become dominant. Its structural impact prompts the development of an antibody that destabilizes the virus quaternary structure where it is most vulnerable. Vaccine-related antigenic regions are different from the proposed epitope, hence avoiding therapeutic redundancy.

A Plant-Derived Antigen-Antibody Complex Induces Anti-Cancer Immune Responses by Forming a Large Quaternary Structure.

The antigen–antibody complex (AAC) has novel functions for immunomodulation, encouraging the application of diverse quaternary protein structures for vaccination. In this study, GA733 antigen and anti-GA733 antibody proteins were both co-expressed to obtain the AAC protein structures in a F1 plant obtained by crossing the plants expressing each protein. In F1 plant, the antigen and antibody assembled to form a large quaternary circular ACC structure (~30 nm). The large quaternary protein structures induced immune response to produce anticancer immunoglobulins G (IgGs) that are specific to the corresponding antigens in mouse. The serum containing the anticancer IgGs inhibited the human colorectal cancer cell growth in the xenograft nude mouse. Taken together, antigens and antibodies can be assembled to form AAC protein structures in plants. Plant crossing represents an alternative strategy for the formation of AAC vaccines that efficiently increases anticancer antibody production.

Atomic Details of Carbon-Based Nanomolecules Interacting with Proteins.

Since the discovery of fullerene, carbon-based nanomolecules sparked a wealth of research across biological, medical and material sciences. Understanding the interactions of these materials with biological samples at the atomic level is crucial for improving the applications of nanomolecules and address safety aspects concerning their use in medicine. Protein crystallography provides the interface view between proteins and carbon-based nanomolecules. We review forefront structural studies of nanomolecules interacting with proteins and the mechanism underlying these interactions. We provide a systematic analysis of approaches used to select proteins interacting with carbon-based nanomolecules explored from the worldwide Protein Data Bank (wwPDB) and scientific literature. The analysis of van der Waals interactions from available data provides important aspects of interactions between proteins and nanomolecules with implications on functional consequences. Carbon-based nanomolecules modulate protein surface electrostatic and, by forming ordered clusters, could modify protein quaternary structures. Lessons learned from structural studies are exemplary and will guide new projects for bioimaging tools, tuning of intrinsically disordered proteins, and design assembly of precise hybrid materials.

Refinement of pairwise potentials via logistic regression to score protein-protein interactions.

Protein-protein interactions (PPIs) are ubiquitous and functionally of great importance in biological systems. Hence, the accurate prediction of PPIs by protein-protein docking and scoring tools is highly desirable in order to characterize their structure and biological function. Ab initio docking protocols are divided into the sampling of docking poses to produce at least one near-native structure, and then to evaluate the vast candidate structures by scoring. Concurrent development in both sampling and scoring is crucial for the deployment of protein-protein docking software. In the present work, we apply a machine learning model on pairwise potentials to refine the task of protein quaternary structure native structure detection among decoys. A decoy set was featurized using the Knowledge and Empirical Combined Scoring Algorithm 2 (KECSA2) pairwise potential. The highly unbalanced decoy set was then balanced using a comparison concept between native and decoy structures. The resultant comparison descriptors were used to train a logistic regression (LR) classifier. The LR model yielded the optimal performance for native detection among decoys compared with conventional scoring functions, while exhibiting lesser performance for the detection of low root mean square deviation decoy structures. Its deployment on an independent benchmark set confirms that the scoring function performs competitively relative to other scoring functions. The scripts used are available at https://github.com/TanemuraKiyoto/PPI-native-detection-via-LR.

A high-performance soybean meal-based plywood adhesive prepared via an ultrasonic process and using significantly lower amounts of chemical additives

The development of a formaldehyde-free, high-performance soybean meal (SM)-based adhesive for manufacturing cleaner wood-based panels is important for minimizing environmental pollution and promoting sustainability. However, the addition of chemical agents for this purpose negatively impacts the environment. Drawing from molecular recombination enhancement theory, a simple physical ultrasonic treatment was used to pretreat the SM to break its particles down and reduce the protein molecular weight. A bio-derived crosslinker was mixed into the SM to recombine the soy protein and prepare a clean, high-performance, bio-based adhesive requiring significantly lower amounts of chemical agents. After 20 min of ultrasonic treatment, the SM particle size was reduced by up to 48.8%, the quaternary structure of the soybean protein was destroyed, and the protein molecular weight decreased, exposing more active groups on the protein surface and resulting in an adhesive system that was both more stable and had a higher reactivity. Moreover, when adding only 4% crosslinker and zero denaturing agent, the ultrasonic treatment process increased the adhesive residual rate by 15.78%, decreased the moisture absorption rate by 25.26%, and improved the wet shear strength of the resultant plywood by 368.2% (to 1.03 MPa), meeting the requirements of the GB/T 9846.3–2004 standard for interior-use plywood. The loading of chemical agents was reduced by up to 650% in comparison to that used in other SM-based adhesive formulations reported in the literature. Thus, using a clean ultrasonic pretreatment process on the SM enabled the preparation of a high-performance, stable, and clean SM-based adhesive, thereby providing a promising option for the implementation of a bio-based product in industrial applications.

QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding.

Many proteins exist in natures as oligomers with various quaternary structural attributes rather than as single chains. Predicting these attributes is an essential task in computational biology for the advancement of proteomics. However, the existing methods do not consider the integration of heterogeneous coding and the accuracy of subunit categories with limited data. To this end, we proposed a tool that can predict more than 12 subunit protein oligomers, QUATgo. Meanwhile, three kinds of sequence coding were used, including dipeptide composition, which was used for the first time to predict protein quaternary structural attributes, and protein half-life characteristics, and we modified the coding method of the functional domain composition proposed by predecessors to solve the problem of large feature vectors. QUATgo solves the problem of insufficient data for a single subunit using a two-stage architecture and uses 10-fold cross-validation to test the predictive accuracy of the classifier. QUATgo has 49.0% cross-validation accuracy and 31.1% independent test accuracy. In the case study, the accuracy of QUATgo can reach 61.5% for predicting the quaternary structure of influenza virus hemagglutinin proteins. Finally, QUATgo is freely accessible to the public as a web server via the site http://predictor.nchu.edu.tw/QUATgo.

Platelet Factor 4 Interactions with Short Heparin Oligomers: Implications for Folding and Assembly

Association of platelet factor 4 (PF4) with heparin is a first step in formation of aggregates implicated in the development of heparin-induced thrombocytopenia (HIT), a potentially fatal immune disorder affecting 1–5% of patients receiving heparin. Despite being a critically important element in HIT etiology, relatively little is known about the specific molecular mechanism of PF4-heparin interactions. This work uses native mass spectrometry to investigate PF4 interactions with relatively short heparin chains (up to decasaccharides). The protein is shown to be remarkably unstable at physiological ionic strength in the absence of polyanions; only monomeric species are observed, and the extent of multiple charging of corresponding ions indicates a partial loss of conformational integrity. The tetramer signal remains at or below the detection threshold in the mass spectra until the solution’s ionic strength is elevated well above the physiological level, highlighting the destabilizing role played by electrostatic interactions vis-à-vis quaternary structure of this high-pI protein. The tetramer assembly is dramatically facilitated by relatively short polyanions (synthetic heparin-mimetic pentasaccharide), with the majority of the protein molecules existing in the tetrameric state even at physiological ionic strength. Each tetramer accommodates up to six pentasaccharides, with at least three such ligands required to guarantee the higher-order structure integrity. Similar results are obtained for PF4 association with longer and structurally heterogeneous heparin oligomers (decamers). These longer polyanions can also induce PF4 dimer assembly when bound to the protein in relatively low numbers, lending support to a model of PF4/heparin interaction in which the latter wraps around the protein, making contacts with multiple subunits. Taken together, these results provide a more nuanced picture of PF4-glycosaminoglycan interactions leading to complex formation. This work also advocates for a greater utilization of native mass spectrometry in elucidating molecular mechanisms underlying HIT, as well as other physiological processes driven by electrostatic interactions.

Combining Molecular Dynamics and Docking Simulations to Develop Targeted Protocols for Performing Optimized Virtual Screening Campaigns on The hTRPM8 Channel.

Background: There is an increasing interest in TRPM8 ligands of medicinal interest, the rational design of which can be nowadays supported by structure-based in silico studies based on the recently resolved TRPM8 structures. Methods: The study involves the generation of a reliable hTRPM8 homology model, the reliability of which was assessed by a 1.0 μs MD simulation which was also used to generate multiple receptor conformations for the following structure-based virtual screening (VS) campaigns; docking simulations utilized different programs and involved all monomers of the selected frames; the so computed docking scores were combined by consensus approaches based on the EFO algorithm. Results: The obtained models revealed very satisfactory performances; LiGen™ provided the best results among the tested docking programs; the combination of docking results from the four monomers elicited a markedly beneficial effect on the computed consensus models. Conclusions: The generated hTRPM8 model appears to be amenable for successful structure-based VS studies; cross-talk modulating effects between interacting monomers on the binding sites can be accounted for by combining docking simulations as performed on all the monomers; this strategy can have general applicability for docking simulations involving quaternary protein structures with multiple identical binding pockets.

A Novel Prediction of Quaternary Structural Type of Proteins with Gene Ontology.

The information of quaternary structure attributes of proteins is very important because it is closely related to the biological functions of proteins. With the rapid development of new generation sequencing technology, we are facing a challenge: how to automatically identify the four-level attributes of new polypeptide chains according to their sequence information (i.e., whether they are formed as just as a monomer, or as a hetero-oligomer, or a homo-oligomer). In this article, our goal is to find a new way to represent protein sequences, thereby improving the prediction rate of protein quaternary structure. In this article, we developed a prediction system for protein quaternary structural type in which a protein sequence was expressed by combining the Pfam functional-domain and gene ontology. turn protein features into digital sequences, and complete the prediction of quaternary structure through specific machine learning algorithms and verification algorithm. Our data set contains 5495 protein samples. Through the method provided in this paper, we classify proteins into monomer, or as a hetero-oligomer, or a homo-oligomer, and the prediction rate is 74.38%, which is 3.24% higher than that of previous studies. Through this new feature extraction method, we can further classify the four-level structure of proteins, and the results are also correspondingly improved. After the applying the new prediction system, compared with the previous results, we have successfully improved the prediction rate. We have reason to believe that the feature extraction method in this paper has better practicability and can be used as a reference for other protein classification problems.

Will Cryo-Electron Microscopy Shift the Current Paradigm in Protein Structure Prediction?

Protein dynamics is undoubtedly a pervasive ingredient in all biological functions. However, structural biology has been strongly driven by a static-centered view of protein architecture. We argue that the recent advances of cryo-electron microscopy (EM) have the potential to more broadly explore the conformational landscapes of protein complexes and therefore will enhance our ability to predict the diverse conformations of tertiary and quaternary protein structures that are functionally relevant in physiological conditions.

Denaturing Lysis of Cells for Immunoprecipitation.

The only way to solubilize many antigens for immunoprecipitation is by denaturation. This cell lysis protocol is ideally suited for this purpose to release proteins from complex structures or reveal antibody epitopes hidden within native proteins. Short linear epitopes may not be accessible to antibodies within the native tertiary and quaternary protein structures, but they become exposed upon the unraveling of proteins, exposing their secondary structure. Antibodies otherwise not suitable for the immunoprecipitation of proteins prepared under nondenaturing conditions are now able to bind these antigens of interest in cell lysates prepared under denaturing conditions. These antibodies may also work well for immunoblotting purposes when the protein target is completely denatured. Harvested cells in this protocol are washed in tris-buffered saline (TBS) before lysis in 2% sodium dodecyl sulfate (SDS)-containing Lysis buffer for 10 min at 100°C. The resulting sample is diluted 20-fold in TBS to reduce the SDS concentration to ≤0.1% before the addition of an antibody for immunoprecipitation. Addition of 2% bovine serum albumin (BSA) or 0.1% Nonidet P-40 to the TBS before an immunoprecipitation, respectively, ensures either removal of SDS from the target protein or retaining denatured proteins in solution.

Structures and properties of chicken myofibrillar protein gel induced by microwave heating

SummaryStructures and properties of myofibrillar protein gel prepared at different power (300–800 W) were evaluated. Amino acid analysis demonstrated that changes in microwave power did not alter primary structure of gel. However, an increase in microwave power could change higher structures of gel. As microwave power increased, α‐helix content decreased and β‐sheet content increased. Increased microwave power probably facilitated protein to unfold and expose the internal groups, causing surface hydrophobicity and the formation of disulphide bonds were enhanced, which indicated changes in tertiary and quaternary structures of protein. At 500 W, gel had the best ultrastructure where surface morphology, springiness and water holding capacity reached the optimum. Our findings suggested that microwave at an appropriate power (500 W) could change higher structures of myofibrillar protein gel to achieve desired processing and quality protein gel characteristics.

100 Years of Macromolecular Science

100 Years of Macromolecular Science

The cryo-EM Structure of Thermotoga maritima β-Galactosidase: Quaternary Structure Guides Protein Engineering.

Lactose intolerance is a common digestive disorder that affects a large proportion of the adult human population. The severity of the symptoms is highly variable, depending on the susceptibility to the sugar and the amount digested. For that reason, enzymes that can be used for the production of lactose-free milk and milk derivatives have acquired singular biotechnological importance. One such case is Thermotoga maritima β-galactosidase (TmLac). Here, we report the cryo-EM structure of TmLac at 2.0 Å resolution. The protein features a newly solved domain at its C-terminus, characteristic of the genus Thermotoga, which promotes a peculiar octameric arrangement. We have assessed the constraints imposed by the quaternary protein structure on the construction of hybrid versions of this GH2 enzyme. Carbohydrate binding modules (CBM) from the CBM2 and CBM9 families have been added at either the amino or carboxy terminus, and the structural and functional effects of such modifications have been analyzed. The results provide a basis for the rational design of hybrid enzymes that can be efficiently attached to different solid supports.

Structural transitions of sword bean canavalin in response to different salt concentrations

Canavalin is the major storage protein in sword beans (Canavalia gladiata) and belongs to the 7S seed globulin class. Canavalin solubility can be reversibly altered via the addition of MgCl2 and CaCl2 at different concentrations; specifically, it is insoluble at lower concentrations and soluble at higher concentrations. However, the addition of NaCl does not induce the insolubilization of canavalin. In this study, it was determined that the addition of NaCl causes the nearly complete solubilization of MgCl2-precipitated canavalin in the presence of high concentrations. Moreover, using gel filtration we examined the quaternary structures of soluble canavalin in the bean extract and in the presence of high-concentration salts. Results indicated that canavalin was present in the monomer form within crude extracts with distilled water. Alternatively, we identified trimeric soluble canavalin in the presence of high concentrations of NaCl or MgCl2. Our study revealed that the quaternary structures of sword bean soluble proteins differ in crude extract compared to those in high-concentration salt solutions. The three-dimensional structure of β-conglycinin, which is a typical 7S-seed globulin in soybean, has a trimer form in the presence of high concentrations of NaCl. However, it remains unclear whether β-conglycinin is present as trimers in soybean seed. Our findings serve as an important reference to analyze 7S globulin characteristics.

Protein docking model evaluation by 3D deep convolutional neural networks.

Many important cellular processes involve physical interactions of proteins. Therefore, determining protein quaternary structures provide critical insights for understanding molecular mechanisms of functions of the complexes. To complement experimental methods, many computational methods have been developed to predict structures of protein complexes. One of the challenges in computational protein complex structure prediction is to identify near-native models from a large pool of generated models. We developed a convolutional deep neural network-based approach named DOcking decoy selection with Voxel-based deep neural nEtwork (DOVE) for evaluating protein docking models. To evaluate a protein docking model, DOVE scans the protein-protein interface of the model with a 3D voxel and considers atomic interaction types and their energetic contributions as input features applied to the neural network. The deep learning models were trained and validated on docking models available in the ZDock and DockGround databases. Among the different combinations of features tested, almost all outperformed existing scoring functions. Codes available at http://github.com/kiharalab/DOVE, http://kiharalab.org/dove/. Supplementary data are available at Bioinformatics online.