Electrochemistry of membrane proteins and protein–lipid assemblies

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Thermal properties and combustibility of elastomer–protein composites

This article presents the test results of thermal properties and flammability of crosslinked nitrile rubber in the presence of zinc oxide or nano-zinc oxide containing waste keratin, using the test results obtained by means of a derivatograph, DSC, and oxygen index. The influence of modified montmorillonite (NanoBent) on selected properties of investigated elastomer–protein composites has also been studied. The composites' thermal stability and flammability depend on the method of composite preparation and the quantity of added keratin. The addition of waste keratin reduces the flammability of NBR–keratin composites.     

Thermal properties and combustibility of elastomer–protein composites

The article describes the measurements results of the influence of waste keratin on the properties of cross-linked styrene-butadiene rubber especially taking its thermal properties and flammability into consideration. The biopolymer used was thoroughly examined by means of derivatography, elementary analysis, FTIR spectroscopy, Zetasizer nano S90, and Zetasizer 2000. It has been found that the presence of protein facilitates the cross-linking of the elastomer investigated and the elastomeric-protein materials are characterized by good thermal and mechanical properties as well as a considerably increased resistance to thermooxidative aging. Under the influence of keratin, the flammability of the composites obtained is decreased.     

Scoring protein–protein docked structures based on the balance and tightness of binding

One main issue in protein-protein docking is to filter or score the putative docked structures. Unlike many popular scoring functions that are based on geometric and energetic complementarity, we present a set of scoring functions that are based on the consideration of local balance and tightness of binding of the docked structures. These scoring functions include the force and moment acting on one component (ligand) imposed by the other (receptor) and the second order spatial derivatives of protein-protein interaction potential. The scoring functions were applied to the docked structures of 19 test targets including enzyme/inhibitor, antibody/antigen and other classes of protein complexes. The results indicate that these scoring functions are also discriminative for the near-native conformation. For some cases, such as antibody/antigen, they show more discriminative efficiency than some other scoring functions, such as desolvation free energy (deltaG(des)) based on pairwise atom-atom contact energy (ACE). The correlation analyses between present scoring functions and the energetic functions also show that there is no clear correlation between them; therefore, the present scoring functions are not essentially the same as energy functions.     

Exploring the effectiveness of the TSR-based protein 3-D structural comparison method for protein clustering,and structural motif identification and discovery of protein kinases,hydrolases, and SARS-CoV-2’s protein via the application of amino acid grouping

Development of protein 3-D structural comparison methods is essential for understanding protein functions. Some amino acids share structural similarities while others vary considerably. These structures determine the chemical and physical properties of amino acids. Grouping amino acids with similar structures potentially improves the ability to identify structurally conserved regions and increases the global structural similarity between proteins. We systematically studied the effects of amino acid grouping on the numbers of Specific/specific, Common/common, and statistically different keys to achieve a better understanding of protein structure relations. Common keys represent substructures found in all types of proteins and Specific keys represent substructures exclusively belonging to a certain type of proteins in a data set. Our results show that applying amino acid grouping to the Triangular Spatial Relationship (TSR)-based method, while computing structural similarity among proteins, improves the accuracy of protein clustering in certain cases. In addition, applying amino acid grouping facilitates the process of identification or discovery of conserved structural motifs. The results from the principal component analysis (PCA) demonstrate that applying amino acid grouping captures slightly more structural variation than when amino acid grouping is not used, indicating that amino acid grouping reduces structure diversity as predicted. The TSR-based method uniquely identifies and discovers binding sites for drugs or interacting proteins. The binding sites of nsp16 of SARS-CoV-2, SARS-CoV and MERS-CoV that we have defined will aid future antiviral drug design for improving therapeutic outcome. This approach for incorporating the amino acid grouping feature into our structural comparison method is promising and provides a deeper insight into understanding of structural relations of proteins.     

Investigation of protein–protein interactions in living cells by chemical crosslinking and mass spectrometry

The identification of protein–protein interactions within their physiological environment is the key to understanding biological processes at the molecular level. However, the artificial nature of in vitro experiments, with their lack of other cellular components, may obstruct observations of specific cellular processes. In vivo analyses can provide information on the processes within a cell that might not be observed in vitro. Chemical crosslinking combined with mass spectrometric analysis of the covalently connected binding partners allows us to identify interacting proteins and to map their interface regions directly in the cell. In this paper, different in vivo crosslinking strategies for deriving information on protein–protein interactions in their physiological environment are described.     

Computer-aided design and discovery of protein–protein interaction inhibitors as agents for anti-HIV therapy

Protein–protein interactions (PPI) are involved in most of the essential processes that occur in organisms. In recent years, PPI have become the object of increasing attention in drug discovery, particularly for anti-HIV drugs. Although the use of combinations of existing drugs, termed highly active antiretroviral therapy (HAART), has revolutionized the treatment of HIV/AIDS, problems with these agents, such as the rapid emergence of drug-resistant HIV-1 mutants and serious adverse effects, have highlighted the need for further discovery of new drugs and new targets. Numerous investigations have shown that PPI play a key role in the virus’s life cycle and that blocking or modulating them has a significant therapeutic potential. Here we summarize the recent progress in computer-aided design of PPI inhibitors, mainly focusing on the selection of the drug targets (HIV enzymes and virus entry machinery) and the utilization of peptides and small molecules to prevent a variety of protein–protein interactions (viral–viral or viral–host) that play a vital role in the progression of HIV infection.     

Nanocoating of CsgA protein for enhanced cell adhesion and proliferation

Immune rejection, poor biocompatibility and cytotoxicity have seriously stalled the widespread application of biometallic materials. To overcome these problems, biometallic materials with fast and sufficient osseointegration, antibacterial properties and long-term stability have attracted the attention of researchers worldwide. Surface modification is currently used as a general strategy to develop material coatings that will overcome these challenging requirements and achieve the successful per...     

Theoretical prediction of the protein–protein interaction between Arabidopsis thaliana COP1 and UVR8

In plants, ultraviolet-B radiation (280–315 nm) regulates gene expression and plant morphology through the UV RESPONSE LOCUS 8 (UVR8) photoreceptor. The first signaling event after quantal absorbance is the interaction of the UVR8 C-terminus with the E3 ubiquitin ligase CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1). The nature of the interaction between these two proteins is hitherto unknown. A protein homology model of the Arabidopsis thaliana COP1 seven-bladed propeller WD40 repeat domain and de novo folds of the C-terminal 27 amino acid (amino acids 397–423) peptide of Arabidopsis UVR8 (UVR8^397?423) is herein reported. Using a theoretical computational docking protocol, the interaction between COP1 and UVR8 was predicted. A core motif was identified in UVR8^397?423 comprising adjacent hydrophobic residues V410 and P411 together with a charged residue D412, homologous to corresponding motifs in other COP1-binding proteins, such as ELONGATED HYPOCOTYL 5 (HY5), cryptochrome 1 (CRY1), and salt tolerance proteins STO/STH. The protein–protein interaction between the COP1 WD40 repeat domain and UVR8^397?423 reveals binding within a region of COP1 overlapping with the binding site for HY5 and the other COP1-interacting proteins. This study provides a framework for understanding docking between UVR8 and COP1, which in turn gives clues for experimental testing of UVR8/COP1 interaction.     

Fluorescence enhancement of the protein–curcumin–sodium dodecyl benzene sulfonate system and protein determination

Protein can greatly enhance the fluorescence of curcumin (CU) in the presence of sodium dodecyl benzene sulfonate (SDBS). Experiments indicate that under the optimum conditions, the enhanced intensity of fluorescence is proportional to the concentration of proteins in the range of 0.0050–20.0 μg mL⁻¹ for bovine serum albumin (BSA), 0.080–20.0 μg mL⁻¹ for human serum albumin (HSA), and 0.040–28.0 μg mL⁻¹ for egg albumin (EA). Their detection limits (S/N=3) are 1.4 ng mL⁻¹, 20 ng mL⁻¹, and 16 ng mL⁻¹, respectively. The method has been satisfactorily used for the determination of proteins in actual samples. In comparison with most of fluorimetric methods, this method is quick and simple, has high sensitivity and good stability. The interaction mechanism is also studied.     

Empirical formulation and parameterization of cation-π interactions for protein modeling

Cation-π interaction is comparable and as important as other main molecular interaction types, such as hydrogen bond, electrostatic interaction, van der Waals interaction, and hydrophobic interaction. Cation-π interactions frequently occur in protein structures, because six (Phe, Tyr, Trp, Arg, Lys, and His) of 20 natural amino acids and all metallic cations could be involved in cation-π interaction. Cation-π interactions arise from complex physicochemical nature and possess unique interaction behaviors, which cannot be modeled and evaluated by existing empirical equations and force field parameters that are widely used in the molecular dynamics. In this study, the authors present an empirical approach for cation-π interaction energy calculations in protein interactions. The accurate cation-π interaction energies of aromatic amino acids (Phe, Tyr, and Try) with protonated amino acids (Arg and Lys) and metallic cations (Li(+), Na(+), K(+), and Ca(2+)) are calculated using B3LYP/6-311+G(d,p) method as the benchmark for the empirical formulization and parameterization. Then, the empirical equations are built and the parameters are optimized based on the benchmark calculations. The cation-π interactions are distance and orientation dependent. Correspondingly, the empirical equations of cation-π interactions are functions of two variables, the distance r and the orientation angle θ. Two types of empirical equations of cation-π interactions are proposed. One is a modified distance and orientation dependent Lennard-Jones equation. The second is a polynomial function of two variables r and θ. The amino acid-based empirical equations and parameters provide simple and useful tools for evaluations of cation-π interaction energies in protein interactions.     

Why not consider a spherical protein? Implications of backbone hydrogen bonding for protein structure and function

The intrinsic ability of protein structures to exhibit the geometric features required for molecular function in the absence of evolution is examined in the context of three systems: the reference set of real, single domain protein structures, a library of computationally generated, compact homopolypeptides, artificial structures with protein-like secondary structural elements, and quasi-spherical random proteins packed at the same density as proteins but lacking backbone secondary structure and hydrogen bonding. Without any evolutionary selection, the library of artificial structures has similar backbone hydrogen bonding, global shape, surface to volume ratio and statistically significant structural matches to real protein global structures. Moreover, these artificial structures have native like ligand binding cavities, and a tiny subset has interfacial geometries consistent with native-like protein-protein interactions and DNA binding. In contrast, the quasi-spherical random proteins, being devoid of secondary structure, have a lower surface to volume ratio and lack ligand binding pockets and intermolecular interaction interfaces. Surprisingly, these quasi-spherical random proteins exhibit protein like distributions of virtual bond angles and almost all have a statistically significant structural match to real protein structures. This implies that it is local chain stiffness, even without backbone hydrogen bonding, and compactness that give rise to the likely completeness of the library solved single domain protein structures. These studies also suggest that the packing of secondary structural elements generates the requisite geometry for intermolecular binding. Thus, backbone hydrogen bonding plays an important role not only in protein structure but also in protein function. Such ability to bind biological molecules is an inherent feature of protein structure; if combined with appropriate protein sequences, it could provide the non-zero background probability for low-level function that evolution requires for selection to occur.     

Assessment of high-confidence protein–protein interactome in yeast

The identification of protein–protein interactions (PPIs) and their networks is vitally important to systemically define and understand the roles of proteins in biological systems. In spite of development of numerous experimental systems to detect PPIs and diverse research on assessment of the quality of the obtained data, a consensus – highly reliable, almost complete – interactome of Saccharomyces cerevisiae is not presented yet. In this work, we proposed an unsupervised statistical approach to create a high-confidence yeast PPI network. For this, we assembled databases of interacting protein pairs for yeast and obtained an extremely large PPI dataset which comprises of 135 154 non-redundant interactions between 6191 yeast proteins. A scoring scheme considering eight heterogeneous biological features resulted with a broad score distribution and a highly reliable network consisting of 29 046 physical interactions with scores higher than the threshold value of 0.85, for which sensitivity, specificity and coverage were 86%, 68%, and 72%, respectively. We evaluated our method by comparing it with other scoring schemes and showed that reducing the noise inherent in experimental PPIs via our scoring scheme further increased the accuracy. Current study is expected to increase the efficiency of the methodologies in biological research which make use of protein interaction networks.     

Quantification of β-trace protein and detection of transferrin isoforms in mixtures of cerebrospinal fluid and blood serum as models of rhinorrhea and otorrhea diagnosis

Different mixtures from a serum pool and a cerebrospinal fluid (CSF) pool were used as models to study CSF contamination in secretions by determining two CSF specific proteins: β-trace protein (β-TP) and the asialo-transferrin (a-Tf) band which was detected by isoelectric focusing (IEF) with Tf specific immunofixation. β-TP and total Tf were measured immunonephelometrically. Secretion/serum ratios of β-TP content > 2.0 indicated CSF contaminations with ≥ 5% (v/v) CSF; this was confirmed by detecting the a-Tf band by IEF. Reliable ¶a-Tf bands were only revealed with secretion/serum rations of Tf contents < 0.1, indicating an interference of major sialo-Tf fractions with the a-TF band detection in the sample. For CSF detection in rhinorrhea and otorrhea, complementary use of β-TP assay and a-Tf assay is recommended. Preanalytically, dilution or concentration of the sample as well as denaturation of Tf and β-TP should be prevented by optimizing sample collection.     

Stochastic kinetic study of protein aggregation and molecular crowding effects of Aβ40 and Aβ42

Two isoforms of β-amyloid peptides, Aβ40 and Aβ42, differ from each other only in the last two amino acids, IA, at the end of Aβ42. They, however, differ significantly in their ability in inducing Alzheimer's disease (AD). The rate curves of fibril growth of Aβ40 and Aβ42 and the effects of molecular crowding have been measured in in vitro experiments. These experimental curves, on the other hand, have been fitted in terms of rate constants for elementary reaction steps using rate equation approaches. Several sets of such rate parameters have been reported in the literature. Employing a recently developed stochastic kinetic method, implemented in a browser-based simulator, popsim, we study to reveal the differences in the kinetic behaviors implied by these sets of rate parameters. In particular, the stochastic method is used to distinguish the kinetic behaviors between Aβ40 and Aβ42 isoforms. As a result, we make general comments on the usefulness of these sets of rate parameters.     

Studying protein–protein affinity and immobilized ligand–protein affinity interactions using MS-based methods

This review discusses the most important current methods employing mass spectrometry (MS) analysis for the study of protein affinity interactions. The methods are discussed in depth with particular reference to MS-based approaches for analyzing protein–protein and protein–immobilized ligand interactions, analyzed either directly or indirectly. First, we introduce MS methods for the study of intact protein complexes in the gas phase. Next, pull-down methods for affinity-based analysis of protein–protein and protein–immobilized ligand interactions are discussed. Presently, this field of research is often called interactomics or interaction proteomics. A slightly different approach that will be discussed, chemical proteomics, allows one to analyze selectivity profiles of ligands for multiple drug targets and off-targets. Additionally, of particular interest is the use of surface plasmon resonance technologies coupled with MS for the study of protein interactions. The review addresses the principle of each of the methods with a focus on recent developments and the applicability to lead compound generation in drug discovery as well as the elucidation of protein interactions involved in cellular processes. The review focuses on the analysis of bioaffinity interactions of proteins with other proteins and with ligands, where the proteins are considered as the bioactives analyzed by MS.     

Streaming potential and protein transmission ultrafiltration of single proteins and proteins in mixture: β-lactoglobulin and lysozyme

A study of single proteins, β-lactoglobulin and lysozyme of different sizes and electrical characteristic as a function of pH, ionic strength and nature of salt (NaCl or CaCl₂) allows to evaluate the filtration performances. Streaming potential measurements confirm that proteins contribute to the net charge of the system and that the protein tranfer through mineral membranes is governed by ionic and steric exclusion phenomena.This work shows the correlation between protein transmission and streaming potential values which takes into account steric and ionic exclusion. The ionic repulsion decreases the transmission. This one depends on membrane net charge characterised by streaming potential, which depends on the solution composition. This model, which does not take into account interactions between protein and membrane fouling leads to an overestimation of calculated transmission values when proteins are in a mixture. However, it allows a correct estimation of transmission variations versus the studied variables: pH and ionic strength.     

Synthesis and protein binding studies of a peptide fragment of clathrin assembly protein AP180 bearing an O-linked β-N-acetylglucosaminyl-6-phosphate modification

A novel post-translational modification of threonine, β-N-acetylglucosaminyl-phosphate, was recently discovered on assembly protein AP180, a protein which plays a crucial role in clathrin coated vesicle formation in synaptic vesicle endocytosis (SVE). Herein, we report studies aimed at probing the effect of this modification on binding to proteins in rat brain lysate using pull down experiments with peptide fragments of AP180.