Protein Recognition Research Articles

Two-Stage Recognition Mechanism of the SARS-CoV-2 Receptor-Binding Domain to Angiotensin-Converting Enzyme-2 (ACE2).

The SARS-CoV-2 virus, commonly known as COVID-19, occurred in 2019. It is a highly contagious illness with effects ranging from mild symptoms to severe illness. It is also one of the best-known pathogens since more than 200,000 scientific papers occurred in the last few years. With the publication of the SARS-CoV-2 (SARS-CoV-2-CTD) spike (S) protein in a complex with human ACE2 (hACE2) (PDB (6LZG)), the molecular analysis of one of the most crucial steps on the infection pathway was possible. The aim of this manuscript is to simulate the most widely spread mutants of SARS-CoV-2, namely Alpha, Beta, Gamma, Delta, Omicron, and the first recognized variant (natural wild type). With the wide search of the hypersurface of the potential energy performed using the UNRES force field, the intermediate state of the ACE2-RBD complex was found. R403, K/N/T417, L455, F486, Y489, F495, Y501, and Y505 played a crucial role in the protein recognition mechanism. The intermediate state cannot be very stable since it will prevent the infection cascade.

Decoding the enigma of RNA-protein recognition: quantum chemical insights into arginine fork motifs.

Arginine (Arg) forks are noncovalent recognition motifs wherein an Arg interacts with the phosphates and guanine nucleobases of RNA, providing extraordinary specific RNA:protein recognition. In this work, we carried out an in-depth DFT based quantum mechanical investigation on all known classes of Arg forks to estimate their intrinsic structural stabilities and interaction energies. The optimized structures closely mimic the structural characteristics of Arg forks and this close match between experimental and optimized geometries suggests that Arg forks are intrinsically stable and do not require additional support from other RNA or protein components. Both hydrogen-bonding and cation-π interactions are important for the intrinsic stability of Arg forks, providing an average interaction energy of -36.7 kcal mol-1. Furthermore, we found a direct correlation between Arg forks' interaction energies and the number of phosphates involved, which is more delicately modulated by other factors, like the types of hydrogen bonds and cation-π interactions that constitute the Arg fork. Additionally, we observed a positive correlation between the average interaction energies of Arg forks and the frequency of their occurrence in available crystal structures. At the broader level, this work establishes the groundwork for more precise modeling and understanding of RNA-protein interfaces, which could have potential implications in advancing the knowledge of biomolecular recognition patterns.

Proteomic changes in age‐related cataract and post‐vitrectomy cataract

Aims/Purpose: To present distinct signalling pathways involved in the development of age‐related cataract (ARC) and post‐vitrectomy cataract (PVC).Methods: Three sample groups, for example, the aqueous humour, the anterior capsule and the content of the phaco cassette, were collected during cataract surgery. The samples were collected from 12 patients without diabetes mellitus (DM), older than 75 years old, and from 7 patient patients without DM, who had undergone vitrectomy for retinal detachment in the past 12 months. The samples were prepared based on Sp3 protocol (single‐pot, solid‐phase‐enhanced, sample‐preparation). The recognition and quantification of proteins was performed with liquid chromatography online with tandem mass spectrometry. Data analysis was performed using the DIA‐NN software for identification and quantification of peptides and proteins. Perseus software was used for statistical analysis and data visualization.Results: Wnt signalling pathway and oxidation–reduction pathway were significantly upregulated in the content of the phaco cassette samples of ARC, while proteasome complex and complement/coagulation cascades pathways were upregulated in those of PVC. Regulation of complement pathway was significantly upregulated in all three samples of PVC. Lipid/fatty acid oxidation and response to hydrogen peroxide pathways were upregulated in anterior capsule samples of PVC.Conclusions: Comparisons between the three sample types of ARC and PVC, revealed proteomic profiles and deregulated pathways, that clarify the pathophysiology of those types of cataract. These data sets may allow the identification of specific proteins as druggable targets against cataract.

Molecularly imprinted polymer-based SERS sensing of transferrin in human serum.

Specific detection of glycoproteins such as transferrin (TRF) related to neurological diseases, hepatoma and other diseases always plays an important role in the field of disease diagnosis. We designed an antibody-free immunoassay sensing method based on molecularly imprinted polymers (MIPs) formed by the polymerization of multiple functional monomers for the sensitive and selective detection of TRF in human serum. In the sandwich surface-enhanced Raman spectroscopy (SERS) sensor, the TRF-oriented magnetic MIP nanoparticles (Fe3O4@SiO2-MIPs) served as capture units to specifically recognize TRF and 4-mercaptophenylboronic acid-functionalized gold nanorods (MPBA-Au NRs) served as SERS probes to label the targets. In order to achieve stronger interaction between the recognition cavities of the prepared MIPs and the different amino acid fragments that make up TRF, Fe3O4@SiO2-MIPs were obtained through polycondensation reactions between more silylating reagents, enhancing the specific recognition of the entire TRF protein and achieving high IF. This sensing method exhibited a good linear response to TRF within the TRF concentration range of 0.01 ng mL-1 to 1 mg mL-1 (R2 = 0.9974), and the LOD was 0.00407 ng mL-1 (S/N = 3). The good stability, reproducibility and specificity of the resulting MIP based SERS sensor were demonstrated. The determination of TRF in human serum confirmed the feasibility of the method in practical applications.

Solution NMR Analysis of O-Glycopeptide-Antibody Interaction.

O-Linked glycans potentially play a functional role in cellular recognition events. Recent structural analyses suggest that O-glycosylation can be a specific signal for a lectin receptor which recognizes both the O-glycan and the adjacent polypeptide region. Further, certain antibodies specifically bind to the O-glycosylated peptide. There is growing interest in the mechanism by which O-glycans on proteins are specifically recognized by lectins and antibodies. The recognition system may be common to many O-glycosylated proteins; however, there is limited 3D structural information on the dual recognition of glycan and protein. This chapter describes a solution NMR analysis of the interaction between MUC1 O-glycopeptide and anti-MUC1 antibody MY.1E12.

Sequence determinants of protein phase separation and recognition by protein phase-separated condensates through molecular dynamics and active learning.

Elucidating how protein sequence determines the properties of disordered proteins and their phase-separated condensates is a great challenge in computational chemistry, biology, and biophysics. Quantitative molecular dynamics simulations and derived free energy values can in principle capture how a sequence encodes the chemical and biological properties of a protein. These calculations are, however, computationally demanding, even after reducing the representation by coarse-graining; exploring the large spaces of potentially relevant sequences remains a formidable task. We employ an "active learning" scheme introduced by Yang et al. (bioRxiv, 2022, https://doi.org/10.1101/2022.08.05.502972) to reduce the number of labelled examples needed from simulations, where a neural network-based model suggests the most useful examples for the next training cycle. Applying this Bayesian optimisation framework, we determine properties of protein sequences with coarse-grained molecular dynamics, which enables the network to establish sequence-property relationships for disordered proteins and their self-interactions and their interactions in phase-separated condensates. We show how iterative training with second virial coefficients derived from the simulations of disordered protein sequences leads to a rapid improvement in predicting peptide self-interactions. We employ this Bayesian approach to efficiently search for new sequences that bind to condensates of the disordered C-terminal domain (CTD) of RNA Polymerase II, by simulating molecular recognition of peptides to phase-separated condensates in coarse-grained molecular dynamics. By searching for protein sequences which prefer to self-interact rather than interact with another protein sequence we are able to shape the morphology of protein condensates and design multiphasic protein condensates.

Using AlphaFold2 and Molecular Dynamics Simulation to Model Protein Recognition.

In this chapter, we predict the structure of the Arabidopsis receptor-homology-transmembrane-RING-H2 isoform 1 (RMR1) in complex with the C-terminal sorting determinant of cruciferin (CRU1) by AlphaFold2 using the ColabFold web interface and to perform molecular dynamics simulation to probe the dynamics of the predicted structures. Our results predict that the C-terminal carboxylate group of ctVSD of CRU1 is recognized by the conserved Arg89 of the cargo-binding loop of RMR1 and Arg468 of CRU1 by negative charge residues in the cargo-binding pocket of RMR1. The procedures described here are useful for modeling of other protein complexes.

A generic approach based on long-lifetime fluorophores for the assessment of protein binding to polymer nanoparticles by fluorescence anisotropy.

Quantitation of protein-nanoparticle interactions is essential for the investigation of the protein corona around NPs in vivo and when using synthetic polymer nanoparticles as affinity reagents for selective protein recognition in vitro. Here, a method based on steady-state fluorescence anisotropy measurement is presented as a novel, separation-free tool for the assessment of protein-nanoparticle interactions. For this purpose, a long-lifetime luminescent Ru-complex is used for protein labelling, which exhibits low anisotropy when conjugated to the protein but displays high anisotropy when the proteins are bound to the much larger polymer nanoparticles. As a proof of concept, the interaction of lysozyme with poly(N-isopropylacrylamide-co-N-tert-butylacrylamide-co-acrylic acid) nanoparticles is studied, and fluorescence anisotropy measurements are used to establish the binding kinetics, binding isotherm and a competitive binding assay.

Magnetic nanoparticle-facilitated rapid mass production of high affinity polymeric materials (nanoMIPs) for protein recognition and biosensing.

Molecularly imprinted polymers (MIPs) have been investigated extensively for broad applications in diagnostics, imaging and therapeutics due to their antibody-like specificity, high stability, and low-cost and rapid production when compared with biological antibodies. Yet, their wide-scale adoption and commercial viability are limited due to low yields and relatively lengthy preparations of current methods. We report the novel application of protein-functionalised magnetic nanoparticles (MNPs) to enable the rapid mass production of nanoMIPs for protein recognition. An aldehyde-functionalised MNP (MNP@CHO) precursor was synthesised using a one-pot microwave method in less than 20 minutes, resulting in 330 mg yield for a 30 mL reaction volume. The MNP@CHO precursor (10 mg) was subsequently functionalised with 600 μg of a target template protein, giving MNP@protein. In the presence of an N-hydroxymethylacrylamide (NHMA) functional monomer and N,N'-methylene bisacrylamide as a crosslinker, the MNP@protein particles served as nucleants for the mass production of nanoMIPs in a 20-30 minute synthesis process. Subsequently, the nanoMIPs could be harvested with sonication and then retrieved using a magnet, leaving the MNP@protein particles to be recycled and re-used at least 5 times for further nanoMIP production cycles. In general, 10 mg of MNP@protein produced 10 mg of nanoMIP with a 20% decrease in the yield over the 5 synthesis cycles. For the bovine haemoglobin nanoMIP, the KD was determined to be 3.47 × 10-11 M, a binding affinity rivalling values found for monoclonal antibodies. We also demonstrate that the methodology is generic by producing high-affinity nanoMIPs for other proteins including albumin, lysozyme and SARS-CoV-2 recombinant protein. We therefore present a facile route to produce nanoMIPs in large industrially relevant quantities (hundreds of mg) and at short timescales (within a day). Our method offers realistic opportunities for the industry to adopt such materials as an antibody replacement technology in diagnostics, biological extraction and therapeutics.

Understanding β-strand mediated protein-protein interactions: tuning binding behaviour of intrinsically disordered sequences by backbone modification.

A significant challenge in chemical biology is to understand and modulate protein-protein interactions (PPIs). Given that many PPIs involve a folded protein domain and a peptide sequence that is intrinsically disordered in isolation, peptides represent powerful tools to understand PPIs. Using the interaction between small ubiquitin-like modifier (SUMO) and SUMO-interacting motifs (SIMs), here we show that N-methylation of the peptide backbone can effectively restrict accessible peptide conformations, predisposing them for protein recognition. Backbone N-methylation in appropriate locations results in faster target binding, and thus higher affinity, as shown by relaxation-based NMR experiments and computational analysis. We show that such higher affinities occur as a consequence of an increase in the energy of the unbound state, and a reduction in the entropic contribution to the binding and activation energies. Thus, backbone N-methylation may represent a useful modification within the peptidomimetic toolbox to probe β-strand mediated interactions.

HDAC Inhibitors against SARS-CoV-2

Abstract: Following the coronavirus outbreak, global efforts to find a vaccine and drug affecting Covid- 19 have been widespread. Reusing some of the available drugs has had relatively satisfactory results. One of the classes of drugs studied against SARS-CoV-2 is the HDAC inhibitors collected in this review. Among the most important points of this study can be mentioned: (a) SARS-COV-2 infection can influence the ACE/ACE2-ATR1-Cholesterol-HDAC axis signaling, (b) By limiting endocytosis and decreasing ACE2-spike protein recognition at the same time, Romidepsin may hinder SARS-2-S-driven host cell entry. (c) HDAC inhibitors affect the expression of ABO, ACE2 and TMPRSS2 in epithelial cell lines. (d) Valproic acid may help to reduce ARDS as well as hospitalizations and death. (e) Trichostatin A inhibits antigen expression, viral RNA load and infectious particle production in SARS-CoV-2.

Occurrences of allergenicity to banana pathogenesis-related-10 (PR10) protein variants.

Pathogenesis-related-10 (PR10) proteins play significant roles in plant defence against biotic and abiotic stresses. Recently, two banana PR10 proteins (MaPR10-BeB5 and MaPR10-GNA5) were characterised and shown to exhibit antifungal properties against Aspergillus fumigatus in vitro. In rice, transgenic overexpression of PR10 proteins conferred resistance to pathogen infection and drought tolerance without affecting productivity, highlighting their potential for agricultural applications. However, PR10 proteins also include the Bet v 1-like family of allergens implicated in pollen food allergy syndromes, raising concerns about potential adverse effects on human health. In this study, we evaluated the allergenic potential of the recently isolated banana PR10 proteins. We first predicted the presence of IgE epitopes of the Bet v 1 allergen family in the deduced PR10 peptide sequences in silico. We then predicted the structures of four human IgE scFv protein sequences and three plant PR10 protein sequences. Based on the quality of the predicted structures, one IgE scFv protein structure was selected for docking with the three plant PR10 proteins. We confirmed the docking results with immunoblot analysis performed using recombinant MaPR10-BeB5 and MaPR10-GNA5 proteins against the sera of banana-allergic patients. Our experimental results substantiated the notion that both protein variants are potentially allergenic since these proteins were recognised by 26.6% of banana-allergic patients with broad PR10 protein recognition. We caution that the allergenic potential of MaPR10 proteins should be carefully considered before implementing transgenic overexpression strategies to improve crops, with a suggestion to limit their expression to non-edible plant tissues.

Interrogating the potential of helical aromatic foldamers for protein recognition.

A biotinylated helical aromatic oligoamide foldamer equivalent in size to a 24mer peptide was designed without any prejudice other than to display various polar and hydrophobic side chains at its surface. It was synthesized on solid phase, its P- and M-helical conformers were separated by HPLC on a chiral stationary phase, and the solid state structure of a non-biotinylated analogue was elucidated by X-ray crystallography. Pull-down experiments from a yeast cell lysate using the foldamer as a bait followed by proteomic analysis revealed potential protein binding partners. Three of these proteins were recombinantly expressed. Biolayer interferometry showed submicromolar binding demonstrating the potential of a given foldamer to have affinity for certain proteins in the absence of design considerations. Yet, binding selectivity was low in all three cases since both P- and M-conformers bound to the proteins with similar affinities.

Studying specificity in protein-glycosaminoglycan recognition with umbrella sampling.

In the past few decades, glycosaminoglycan (GAG) research has been crucial for gaining insights into various physiological, pathological, and therapeutic aspects mediated by the direct interactions between the GAG molecules and diverse proteins. The structural and functional heterogeneities of GAGs as well as their ability to bind specific proteins are determined by the sugar composition of the GAG, the size of the GAG chains, and the degree and pattern of sulfation. A deep understanding of the interactions in protein-GAG complexes is essential to explain their biological functions. In this study, the umbrella sampling (US) approach is used to pull away a GAG ligand from the binding site and then pull it back in. We analyze the binding interactions between GAGs of three types (heparin, desulfated heparan sulfate, and chondroitin sulfate) with three different proteins (basic fibroblast growth factor, acidic fibroblast growth factor, and cathepsin K). The main focus of our study was to evaluate whether the US approach is able to reproduce experimentally obtained structures, and how useful it can be for getting a deeper understanding of GAG properties, especially protein recognition specificity and multipose binding. We found that the binding free energy landscape in the proximity of the GAG native binding pose is complex and implies the co-existence of several binding poses. The sliding of a GAG chain along a protein surface could be a potential mechanism of GAG particular sequence recognition by proteins.

Susceptibility of Toxoplasma gondii to autophagy in human cells relies on multiple interacting parasite loci.

Autophagy is a process used by cells to recycle organelles and macromolecules and to eliminate intracellular pathogens. Previous studies have shown that some stains of Toxoplasma gondii are resistant to autophagy-dependent growth restriction, while others are highly susceptible. Although it is known that autophagy-mediated control requires activation by interferon gamma, the basis for why parasite strains differ in their susceptibility is unknown. Our findings indicate that susceptibility involves at least five unlinked parasite genes on different chromosomes, including several secretory proteins targeted to the parasite-containing vacuole and exposed to the host cell cytosol. Our findings reveal that susceptibility to autophagy-mediated growth restriction relies on differential recognition of parasite proteins exposed at the host-pathogen interface, thus identifying a new mechanism for cell-autonomous control of intracellular pathogens.

Analysis of RNA Recognition and Binding Characteristics of OsCPPR1 Protein in Rice

Pentatricopeptide repeat (PPR) proteins represent one of the largest protein families in plants and typically localize to organelles like mitochondria and chloroplasts. By contrast, CYTOPLASM- LOCALIZED PPR1 (OsCPPR1) is a cytoplasm-localized PPR protein that can degrade OsGOLDEN- LIKE1 (OsGLK1) mRNA in the tapetum of rice anther. However, the mechanism, by which OsCPPR1 recognizes and binds to OsGLK1 transcripts, remains unknown. Through protein structure prediction and macromolecular docking experiments, we observed that distinct PPR motif structures of OsCPPR1 exhibited varying binding efficiencies to OsGLK1 RNA. Moreover, RNA-electrophoretic mobility shift assay experiment demonstrated that the recombinant OsCPPR1 can directly recognize and bind to OsGLK1 mRNA in vitro. This further confirmed that the mutations in the conserved amino acids in each PPR motif resulted in loss of activity, while truncation of OsCPPR1 decreased its binding efficiency. These findings collectively suggest that it may require some co-factors to assist in cleavage, a facet that warrants further exploration in subsequent studies.

Rapid increase in salivary IgA and broad recognition of spike protein following SARS-CoV-2 vaccination

Saliva is a key component of mucosal immunity, which protects the oral cavity from viral infections. However, salivary immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in terms of immunoglobulin dynamics and recognition, have not been investigated sufficiently. In this study, saliva samples were collected from individuals that received SARS-CoV-2 vaccine, and immunoglobulin G (IgG), IgM, and IgA against whole spike protein and S1 protein were measured. IgA against whole spike protein increased significantly following vaccination, while IgA against S1 protein did not. Of note, the IgA response was evident two weeks after the first vaccine dose and continued to rise thereafter. On the contrary, IgG antibodies against S1 increased significantly at four weeks after vaccination. These results reveal the dynamics and recognition antigens of immunoglobulins in saliva, indicating the function of IgA in the mucosal immune system. These findings may pave the way for further studies on mucosal immune response induced by vaccination.

Predictive Recognition of DNA-binding Proteins Based on Pre-trained Language Model BERT.

Identifying proteins is crucial for disease diagnosis and treatment. With the increase of known proteins, large-scale batch predictions are essential. However, traditional biological experiments being time-consuming and expensive are difficult to accomplish this task efficiently. Nevertheless, deep learning algorithms based on big data analysis have manifested potential in this aspect. In recent years, language representation models, especially BERT, have made significant advancements in natural language processing. In this paper, using three protein segmentation methods and three encoder numbers, nine BERT models with different sizes are constructed to predict whether known proteins are DNA-binding proteins or not. Furthermore, based on the concept of protein motifs, multi-scale convolutional networks are fused into the models to extract the local features of DNA-binding proteins. Finally, we find that the larger the number of encoders, the better the model predictions under the condition of considering each amino acid in the protein as a word. Our proposed algorithm achieves 81.88% sensitivity and 0.39 MCC value on the test set. Furthermore, it achieves 62.41% accuracy on the independent test set PDB2272. It is evident that our proposed method can be a tool to assist in the identification of DNA-binding proteins.

A Computational Approach to Predict the Possible Binding Site of HCV NS5A and the Host Cell Chaperone, GRP78

Aim: Glucose-regulated protein 78 (GRP78) is an endoplasmic reticulum located chaperone that plays a vital role during cellular stress. NS5A is one of the hepatitis C virus (HCV) non-structural proteins essential for replication. Materials & methods: Protein–protein docking was used to test the binding mode between GRP78 and HCV NS5A. Molecular dynamics simulations (MDSs) are performed on HCV NS5A, GRP78 and the HCV NS5A–GRP78 complex. Results: Docking and MDS reveal the ability of the GRP78 substrate-binding domain β to associate tightly with the HCV NS5A C142-C165 region. Conclusion: MDS reveals the potential of the C142-C165 region of the HCV NS5A to be used as a seed to develop a recognition inhibitor that counterparts the viral protein recognition by GRP78.

Unraveling the Cave: A Seventy-Year Journey into the Caveolar Network, Cellular Signaling, and Human Disease.

In the mid-1950s, a groundbreaking discovery revealed the fascinating presence of caveolae, referred to as flask-shaped invaginations of the plasma membrane, sparking renewed excitement in the field of cell biology. Caveolae are small, flask-shaped invaginations in the cell membrane that play crucial roles in diverse cellular processes, including endocytosis, lipid homeostasis, and signal transduction. The structural stability and functionality of these specialized membrane microdomains are attributed to the coordinated activity of scaffolding proteins, including caveolins and cavins. While caveolae and caveolins have been long appreciated for their integral roles in cellular physiology, the accumulating scientific evidence throughout the years reaffirms their association with a broad spectrum of human disorders. This review article aims to offer a thorough account of the historical advancements in caveolae research, spanning from their initial discovery to the recognition of caveolin family proteins and their intricate contributions to cellular functions. Furthermore, it will examine the consequences of a dysfunctional caveolar network in the development of human diseases.