Bridging the past and the future of virology: surface plasmon resonance as a powerful tool to investigate virus/host interactions

Never ending story? Evolution of SARS-CoV-2 monitored through Gibbs energies of biosynthesis and antigen-receptor binding of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants

RNA viruses exhibit a great tendency to mutate. Mutations occur in the parts of the genome that encode the spike glycoprotein and less often in the rest of the genome. This is why Gibbs energy of binding changes more than that of biosynthesis. Starting from 2019, the wild type that was labeled Hu-1 has during the last 3 years evolved to produce several dozen new variants, as a consequence of mutations. Mutations cause changes in empirical formulas of new virus strains, which lead to change in thermodynamic properties of biosynthesis and binding. These changes cause changes in the rate of reactions of binding of virus antigen to the host cell receptor and the rate of virus multiplication in the host cell. Changes in thermodynamic and kinetic parameters lead to changes in biological parameters of infectivity and pathogenicity. Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has been evolving towards increase in infectivity and maintaining constant pathogenicity, or for some variants a slight decrease in pathogenicity. In the case of Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants pathogenicity is identical as in the Omicron BA.2.75 variant. On the other hand, infectivity of the Omicron BQ.1, BQ.1.1, XBB and XBB.1 variants is greater than those of previous variants. This will most likely result in the phenomenon of asymmetric coinfection, that is circulation of several variants in the population, some being dominant.

Medicinal Chemistry Strategies for the Development of Inhibitors Disrupting β-Catenin's Interactions with Its Nuclear Partners

Dysregulation of the Wnt/β-catenin signaling pathway is strongly associated with various aspects of cancer, including tumor initiation, proliferation, and metastasis as well as antitumor immunity, and presents a promising opportunity for cancer therapy. Wnt/β-catenin signaling activation increases nuclear dephosphorylated β-catenin levels, resulting in β-catenin binding to TCF and additional cotranscription factors, such as BCL9, CBP, and p300. Therefore, directly disrupting β-catenin's interactions with these nuclear partners holds promise for the effective and selective suppression of the aberrant activation of Wnt/β-catenin signaling. Herein, we summarize recent advances in biochemical techniques and medicinal chemistry strategies used to identify potent peptide-based and small-molecule inhibitors that directly disrupt β-catenin's interactions with its nuclear binding partners. We discuss the challenges involved in developing drug-like inhibitors that target the interactions of β-catenin and its nuclear binding partner into therapeutic agents.

Biothermodynamics of Viruses from Absolute Zero (1950) to Virothermodynamics (2022)

Biothermodynamics of viruses is among the youngest but most rapidly developing scientific disciplines. During the COVID-19 pandemic, it closely followed the results published by molecular biologists. Empirical formulas were published for 50 viruses and thermodynamic properties for multiple viruses and virus variants, including all variants of concern of SARS-CoV-2, SARS-CoV, MERS-CoV, Ebola virus, Vaccinia and Monkeypox virus. A review of the development of biothermodynamics of viruses during the last several decades and intense development during the last 3 years is described in this paper.

Strain wars 3: Differences in infectivity and pathogenicity between Delta and Omicron strains of SARS-CoV-2 can be explained by thermodynamic and kinetic parameters of binding and growth

In this paper, for the first time, empirical formulas have been reported of the Delta and Omicron strains of SARS-CoV-2. The empirical formula of the Delta strain entire virion was found to be CH_1.6383O_0.2844N_0.2294P_0.0064S_0.0042, while its nucleocapsid has the formula CH_1.5692O_0.3431N_0.3106P_0.0060S_0.0043. The empirical formula of the Omicron strain entire virion was found to be CH_1.6404O_0.2842N_0.2299P_0.0064S_0.0038, while its nucleocapsid has the formula CH_1.5734O_0.3442N_0.3122P_0.0060S_0.0033. Based on the empirical formulas, standard thermodynamic properties of formation and growth have been calculated and reported for the Delta and Omicron strains. Moreover, standard thermodynamic properties of binding have been reported for Wild type (Hu-1), Alpha, Beta, Gamma, Delta and Omicron strains. For all the strains, binding phenomenological coefficients and antigen-receptor (SGP-ACE2) binding rates have been determined and compared, which are proportional to infectivity. The results show that the binding rate of the Omicron strain is between 1.5 and 2.5 times greater than that of the Delta strain. The Omicron strain is characterized by a greater infectivity, based on the epidemiological data available in the literature. The increased infectivity was explained in this paper using Gibbs energy of binding. However, no indications exist for decreased pathogenicity of the Omicron strain. Pathogenicity is proportional to the virus multiplication rate, while Gibbs energies of multiplication are very similar for the Delta and Omicron strains. Thus, multiplication rate and pathogenicity are similar for the Delta and Omicron strains. The lower number of severe cases caused by the Omicron strain can be explained by increased number of immunized people. Immunization does not influence the possibility of occurrence of infection, but influences the rate of immune response, which is much more efficient in immunized people. This leads to prevention of more severe Omicron infection cases.

MP-VHPPI: Meta predictor for viral host protein-protein interaction prediction in multiple hosts and viruses

Viral-host protein-protein interaction (VHPPI) prediction is essential to decoding molecular mechanisms of viral pathogens and host immunity processes that eventually help to control the propagation of viral diseases and to design optimized therapeutics. Multiple AI-based predictors have been developed to predict diverse VHPPIs across a wide range of viruses and hosts, however, these predictors produce better performance only for specific types of hosts and viruses. The prime objective of this research is to develop a robust meta predictor (MP-VHPPI) capable of more accurately predicting VHPPI across multiple hosts and viruses. The proposed meta predictor makes use of two well-known encoding methods Amphiphilic Pseudo-Amino Acid Composition (APAAC) and Quasi-sequence (QS) Order that capture amino acids sequence order and distributional information to most effectively generate the numerical representation of complete viral-host raw protein sequences. Feature agglomeration method is utilized to transform the original feature space into a more informative feature space. Random forest (RF) and Extra tree (ET) classifiers are trained on optimized feature space of both APAAC and QS order separate encoders and by combining both encodings. Further predictions of both classifiers are utilized to feed the Support Vector Machine (SVM) classifier that makes final predictions. The proposed meta predictor is evaluated over 7 different benchmark datasets, where it outperforms existing VHPPI predictors with an average performance of 3.07, 6.07, 2.95, and 2.85% in terms of accuracy, Mathews correlation coefficient, precision, and sensitivity, respectively. To facilitate the scientific community, the MP-VHPPI web server is available at https://sds_genetic_analysis.opendfki.de/MP-VHPPI/.

Omicron BA.2.75 Sublineage (Centaurus) Follows the Expectations of the Evolution Theory: Less Negative Gibbs Energy of Biosynthesis Indicates Decreased Pathogenicity

SARS-CoV-2 belongs to the group of RNA viruses with a pronounced tendency to mutate. Omicron BA.2.75 is a subvariant believed to be able to suppress the currently dominant BA.5 and cause a new winter wave of the COVID-19 pandemic. Omicron BA.2.75 is characterized by a greater infectivity compared to earlier Omicron variants. However, the Gibbs energy of the biosynthesis of virus particles is slightly less negative compared to those of other variants. Thus, the multiplication rate of Omicron BA.2.75 is lower than that of other SARS-CoV-2 variants. This leads to slower accumulation of newly formed virions and less damage to host cells, indicating evolution of SARS-CoV-2 toward decreasing pathogenicity.

Role of plasmonics in detection of deadliest viruses: a review

Viruses have threatened animal and human lives since a long time ago all over the world. Some of these tiny particles have caused disastrous pandemics that killed a large number of people with subsequent economic downturns. In addition, the quarantine situation itself encounters the challenges like the deficiency in the online educational system, psychiatric problems and poor international relations. Although viruses have a rather simple protein structure, they have structural heterogeneity with a high tendency to mutation that impedes their study. On top of the breadth of such worldwide worrying issues, there are profound scientific gaps, and several unanswered questions, like lack of vaccines or antivirals to combat these pathogens. Various detection techniques like the nucleic acid test, immunoassay, and microscopy have been developed; however, there is a tradeoff between their advantages and disadvantages like safety in sample collecting, invasiveness, sensitivity, response time, etc. One of the highly resolved techniques that can provide early-stage detection with fast experiment duration is plasmonics. This optical technique has the capability to detect viral proteins and genomes at the early stage via highly sensitive interaction between the biological target and the plasmonic chip. The efficiency of this technique could be proved using commercialized techniques like reverse transcription polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA) techniques. In this study, we aim to review the role of plasmonic technique in the detection of 11 deadliest viruses besides 2 common genital viruses for the human being. This is a rapidly moving topic of research, and a review article that encompasses the current findings may be useful for guiding strategies to deal with the pandemics. By investigating the potential aspects of this technique, we hope that this study could open new avenues toward the application of point-of-care techniques for virus detection at early stage that may inhibit the progressively hygienic threats.

Viruses Like Sugars: How to Assess Glycan Involvement in Viral Attachment

The first step of viral infection requires interaction with the host cell. Before finding the specific receptor that triggers entry, the majority of viruses interact with the glycocalyx. Identifying the carbohydrates that are specifically recognized by different viruses is important both for assessing the cellular tropism and for identifying new antiviral targets. Advances in the tools available for studying glycan-protein interactions have made it possible to identify them more rapidly; however, it is important to recognize the limitations of these methods in order to draw relevant conclusions. Here, we review different techniques: genetic screening, glycan arrays, enzymatic and pharmacological approaches, and surface plasmon resonance. We then detail the glycan interactions of enterovirus D68 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), highlighting the aspects that need further clarification.

A Bittersweet Computational Journey among Glycosaminoglycans

Glycosaminoglycans (GAGs) are linear polysaccharides. In proteoglycans (PGs), they are attached to a core protein. GAGs and PGs can be found as free molecules, associated with the extracellular matrix or expressed on the cell membrane. They play a role in the regulation of a wide array of physiological and pathological processes by binding to different proteins, thus modulating their structure and function, and their concentration and availability in the microenvironment. Unfortunately, the enormous structural diversity of GAGs/PGs has hampered the development of dedicated analytical technologies and experimental models. Similarly, computational approaches (in particular, molecular modeling, docking and dynamics simulations) have not been fully exploited in glycobiology, despite their potential to demystify the complexity of GAGs/PGs at a structural and functional level. Here, we review the state-of-the art of computational approaches to studying GAGs/PGs with the aim of pointing out the “bitter” and “sweet” aspects of this field of research. Furthermore, we attempt to bridge the gap between bioinformatics and glycobiology, which have so far been kept apart by conceptual and technical differences. For this purpose, we provide computational scientists and glycobiologists with the fundamentals of these two fields of research, with the aim of creating opportunities for their combined exploitation, and thereby contributing to a substantial improvement in scientific knowledge.

Recent progress on developing of plasmon biosensing of tumor biomarkers: Efficient method towards early stage recognition of cancer

Cancer is the second most extended disease with an improved death rate over the past several time. Due to the restrictions of cancer analysis methods, the patient's real survival rate is unknown. Therefore, early stage diagnosis of cancer is crucial for its strong detection. Bio-analysis based on biomarkers may help to overcome the problem Biosensors with high sensitivity and specificity, low-cost, high analysis speed and minimum limit of detection are practical alternatives for laboratory tests. Surface plasmon resonance (SPR) is reaching a maturity level sufficient for their application in detection and determination cancer biomarkers in clinical samples. This review discusses main concepts and performance characteristics of SPR biosensor. Mainly, it focuses on newly emerged enhanced SPR biosensors towards high-throughput and ultrasensitive screening of cancer biomarkers such as PSA, α-fetoprotein, CEA, CA125, CA 15-3, HER2, ctDNA, ALCAM, hCG, VEGF, TNF, Interleukin, IFN-γ, CD24, CD44, Ferritin, COLIV using labeling processes with focusing on the future application in biomedical research and clinical diagnosis. This article reviews current status of the field, showcasing a series of early successes in the application of SPR for clinical bioanalysis of cancer related biomolecules and detailing a series of considerations regarding sensing schemes, exposing issues with analysis in biofluids, while providing an outlook of the challenges currently associated with plasmonic materials, bioreceptor selection, microfluidics, and validation of a clinical bioassay for applying SPR biosensors to clinical samples. Research opportunities are proposed to further advance the field and transition SPR biosensors from research proof-of-concept stage to actual clinical usage.

Recent Strategic Advances in CFTR Drug Discovery: An Overview

Cystic fibrosis transmembrane conductance regulator (CFTR)-rescuing drugs have already transformed cystic fibrosis (CF) from a fatal disease to a treatable chronic condition. However, new-generation drugs able to bind CFTR with higher specificity/affinity and to exert stronger therapeutic benefits and fewer side effects are still awaited. Computational methods and biosensors have become indispensable tools in the process of drug discovery for many important human pathologies. Instead, they have been used only piecemeal in CF so far, calling for their appropriate integration with well-tried CF biochemical and cell-based models to speed up the discovery of new CFTR-rescuing drugs. This review will give an overview of the available structures and computational models of CFTR and of the biosensors, biochemical and cell-based assays already used in CF-oriented studies. It will also give the reader some insights about how to integrate these tools as to improve the efficiency of the drug discovery process targeted to CFTR.

Heparin and heparan sulfate proteoglycans promote HIV-1 p17 matrix protein oligomerization: computational, biochemical and biological implications

p17 matrix protein released by HIV+ cells interacts with leukocytes heparan sulfate proteoglycans (HSPGs), CXCR1 and CXCR2 exerting different cytokine-like activities that contribute to AIDS pathogenesis. Since the bioactive form of several cytokines is represented by dimers/oligomers and oligomerization is promoted by binding to heparin or HSPGs, here we evaluated if heparin/HSPGs also promote p17 oligomerization. Heparin favours p17 dimer, trimer and tetramer assembly, in a time- and biphasic dose-dependent way. Heparin-induced p17 oligomerization is of electrostatic nature, being it prevented by NaCl, by removing negative sulfated groups of heparin and by neutralizing positive lysine residues in the p17 N-terminus. A new computational protocol has been implemented to study heparin chains up to 24-mer accommodating a p17 dimer. Molecular dynamics show that, in the presence of heparin, two p17 molecules undergo conformational modifications creating a continuous “electropositive channel” in which heparin sulfated groups interact with p17 basic amino acids, promoting its dimerization. At the cell surface, HSPGs induce p17 oligomerization, as demonstrated by using B-lymphoblastoid Namalwa cells overexpressing the HSPG Syndecan-1. Also, HSPGs on the surface of BJAB and Raji human B-lymphoblastoid cells are required to p17 to induce ERK_1/2 activation, suggesting that HS-induced oligomerization plays a role in p17-induced lymphoid dysregulation during AIDS.

Heparin Binding Proteins as Therapeutic Target: An Historical Account and Current Trends

The polyanionic nature and the ability to interact with proteins with different affinities are properties of sulfated glycosaminoglycans (GAGs) that determine their biological function. In designing drugs affecting the interaction of proteins with GAGs the challenge has been to generate agents with high binding specificity. The example to emulated has been a heparin-derived pentasaccharide that binds to antithrombin-III with high affinity. However, the portability of this model to other biological situations is questioned on several accounts. Because of their structural flexibility, oligosaccharides with different sulfation and uronic acid conformation can display the same binding proficiency to different proteins and produce comparable biological effects. This circumstance represents a formidable obstacle to the design of drugs based on the heparin scaffold. The conceptual framework discussed in this article is that through a direct intervention on the heparin-binding functionality of proteins is possible to achieve a high degree of action specificity. This objective is currently pursued through two strategies. The first makes use of small molecules for which in the text we provide examples from past and present literature concerning angiogenic factors and enzymes. The second approach entails the mutagenesis of the GAG-binding site of proteins as a means to generate a new class of biologics of therapeutic interest.

Simple Strategy for Rapid and Sensitive Detection of Avian Influenza A H7N9 Virus Based on Intensity-Modulated SPR Biosensor and New Generated Antibody

In 2013 a new reassortant avian influenza A H7N9 virus emerged in China, causing human infection with high mortality. An accurate and timely diagnosis is crucial for controlling the outbreaks of the disease. We therefore propose a simple strategy for rapidly and sensitively detecting the H7N9 virus using an intensity-modulated surface plasmon resonance (IM-SPR) biosensor integrated with a new generated monoclonal antibody. The novel antibody exhibits significant specificity to recognize H7N9 virus compared with other clinical human influenza isolates (p < 0.01). Experimentally, the detection limit of the proposed approach for H7N9 virus detection is estimated to be 144 copies/mL, which is a 20-fold increase in sensitivity compared with homemade target-captured ELISA using the identical antibody. For the measurement of mimic clinical specimens containing the H7N9 virus mixed with nasal mucosa from flu-like syndrome patients, the detection limit is calculated to be 402 copies/mL, which is better than conventional influenza detection assays; quantitative reverse transcription polymerase chain reaction (qRT-PCR) and rapid influenza diagnostic test (RIDT). Most importantly, the assay time took less than 10 min. Combined, the results of this study indicate that the proposed simple strategy demonstrates high sensitivity and time-saving in H7N9 virus detection. By incorporating a high specific recognizer, the proposed technique has the potential to be used in applications and development of other emerging or re-emerging microbe detection platforms.

Measuring Protein Interactions by Optical Biosensors

This unit gives an introduction to the basic techniques of optical biosensing for measuring equilibrium and kinetics of reversible protein interactions. Emphasis is placed on description of robust approaches that will provide reliable results with few assumptions. How to avoid the most commonly encountered problems and artifacts is also discussed. © 2017 by John Wiley & Sons, Inc.

Surface Plasmon Resonance Analysis of Heparin-Binding Angiogenic Growth Factors

Surface plasmon resonance (SPR) is an optical technique to evaluate biomolecular interactions. Briefly, SPR measures the capacity of two molecules to bind each other by detecting reflected light from a prism-gold film interface. One of the two putative interactants (called ligand) is chemically immobilized onto the gold film. When the sensor is exposed to a sample containing the second interactant (called analyte), its binding to the immobilized ligand causes a change of the refractive index of the material above the gold surface that is monitored as a real-time graph of the response units against time, producing a real-time graph called sensorgram. SPR has become a golden standard technology for label-free, real-time interaction analysis in basic research and drug discovery in a wide array of biomedical areas, including oncology and virology [1, 2]. Here we describe the exploitation of SPR for the study of the capacity of the pro-oncogenic, pro-angiogenic HIV-1 p17 matrix protein [3, 4] to bind to heparin, a structural analog of heparan sulfate proteoglycans (HSPGs) receptors, and for the identification of novel HSPGs-antagonists to be used as anti-p17 drugs.

Merging colloidal nanoplasmonics and surface plasmon resonance spectroscopy for enhanced profiling of multiple myeloma-derived exosomes

A novel approach for sorting exosomes from multiple myeloma (MM), monoclonal gammopathy of undetermined significance (MGUS) and healthy individuals is presented. The method is based on the combination of colloidal gold nanoplasmonics and surface plasmon resonance (SPR) biosensing and probes distinctive colloidal properties of MM-derived exosomes, such as molar concentration and cell membrane binding preferences. It allowed to discover that MM patients produce about four folds more exosomes than MGUS and healthy individuals. In addition, it showed that among the analyzed exosomes, only the MM-derived ones bind heparin - a structural analog of heparan sulfate proteoglycans known to mediate exosome endocytosis - with an apparent dissociation constant (Kd) equal to about 1 nM, indicating a high affinity binding. This plasmonic method complements the classical biochemical profiling approach to exosomes, expanding the MM biomarker panel and adding biosensors to the toolbox to diagnose MM. It may find applications for other diseases and has wider interest for fundamental and translational research involving exosomes.

The agmatine-containing poly(amidoamine) polymer AGMA1 binds cell surface heparan sulfates and prevents attachment of mucosal human papillomaviruses

The agmatine-containing poly(amidoamine) polymer AGMA1 was recently shown to inhibit the infectivity of several viruses, including human papillomavirus 16 (HPV-16), that exploit cell surface heparan sulfate proteoglycans (HSPGs) as attachment receptors. The aim of this work was to assess the antiviral activity of AGMA1 and its spectrum of activity against a panel of low-risk and high-risk HPVs and to elucidate its mechanism of action. AGMA1 was found to be a potent inhibitor of mucosal HPV types (i.e., types 16, 31, 45, and 6) in pseudovirus-based neutralization assays. The 50% inhibitory concentration was between 0.34 μg/ml and 0.73 μg/ml, and no evidence of cytotoxicity was observed. AGMA1 interacted with immobilized heparin and with cellular heparan sulfates, exerting its antiviral action by preventing virus attachment to the cell surface. The findings from this study indicate that AGMA1 is a leading candidate compound for further development as an active ingredient of a topical microbicide against HPV and other sexually transmitted viral infections.