Molecular Docking and Virtual Screening of an Influenza Virus Inhibitor That Disrupts Protein-Protein Interactions.

Influenza is an acute respiratory infection caused by the influenza virus, but few drugs are available for its treatment. Consequently, researchers have been engaged in efforts to discover new antiviral mechanisms that can lay the foundation for novel anti-influenza drugs. The viral RNA-dependent RNA polymerase (RdRp) is an enzyme that plays an indispensable role in the viral infection process, which is directly linked to the survival of the virus. Methods of inhibiting PB1-PB2 (basic polymerase 1-basic polymerase 2) interactions, which are a key part of RdRp enzyme activity, are integral in the design of novel antiviral drugs, a specific PB1-PB2 interactions inhibitor has not been reported. We have screened Enamine's database and conducted a parallel screening of multiple docking schemes, followed by simulations of molecular dynamics to determine the structure of a stable ligand-PB1 complex. We also calculated the free energy of binding between the screened compounds and PB1 protein. Ultimately, we screened and identified a potential PB1-PB2 inhibitor using the ADMET prediction model.

Antivirals Targeting the Surface Glycoproteins of Influenza Virus: Mechanisms of Action and Resistance.

Hemagglutinin and neuraminidase, which constitute the glycoprotein spikes expressed on the surface of influenza A and B viruses, are the most exposed parts of the virus and play critical roles in the viral lifecycle. As such, they make prominent targets for the immune response and antiviral drugs. Neuraminidase inhibitors, particularly oseltamivir, constitute the most commonly used antivirals against influenza viruses, and they have proved their clinical utility against seasonal and emerging influenza viruses. However, the emergence of resistant strains remains a constant threat and consideration. Antivirals targeting the hemagglutinin protein are relatively new and have yet to gain global use but are proving to be effective additions to the antiviral repertoire, with a relatively high threshold for the emergence of resistance. Here we review antiviral drugs, both approved for clinical use and under investigation, that target the influenza virus hemagglutinin and neuraminidase proteins, focusing on their mechanisms of action and the emergence of resistance to them.

A New Bacmid for Customized Protein Glycosylation Pathway Engineering in the Baculovirus-Insect Cell System.

One attractive feature of the baculovirus-insect cell system (BICS) is the baculoviral genome has a large capacity for genetic cargo. This enables construction of viral vectors designed to accept multigene insertions, which has facilitated efforts to produce recombinant multisubunit protein complexes. However, the large genetic capacity of baculovirus vectors has not yet been exploited for multistep pathway engineering. Therefore, we created PolyBac, which is a novel baculovirus shuttle vector, or bacmid, that can be used for this purpose. PolyBac was designed to accept multiple transgene insertions by three different mechanisms at three different sites within the baculovirus genome. After constructing and characterizing PolyBac, we used it to isolate nine derivatives encoding various combinations of up to eight different protein N-glycosylation pathway functions, or glycogenes. We then used these derivatives, which were designed to progressively extend the endogenous insect cell pathway, to assess PolyBac's utility for protein glycosylation pathway engineering. This assessment was enabled by engineering each derivative to produce a recombinant influenza hemagglutinin (rH5), which was used to probe the impact of each glycoengineered PolyBac derivative on the endogenous insect cell pathway. Genetic analyses of these derivatives confirmed PolyBac can accept large DNA insertions. Biochemical analyses of the rH5 products showed each had distinct N-glycosylation profiles. Finally, the major N-glycan on each rH5 product was the predicted end product of the engineered N-glycosylation pathways encoded by each PolyBac derivative. These results generally indicate that PolyBac has utility for multistep metabolic pathway engineering and directly demonstrate that this new bacmid can be used for customized protein glycosylation pathway engineering in the BICS.

Tannic acid-functionalized HEPA filter materials for influenza virus capture.

Influenza, one of the most contagious and infectious diseases, is predominantly transmitted through aerosols, leading to the development of filter-based protective equipment. Though the currently available filters are effective at removing submicron-sized particulates, filter materials with enhanced virus-capture efficiency are still in demand. Coating or chemically modifying filters with molecules capable of binding influenza viruses has received attention as a promising approach for the production of virus-capturing filters. For this purpose, tannic acid (TA), a plant-derived polyphenol, is a promising molecule for filter functionalization because of its antiviral activities and ability to serve as a cost-efficient adhesive for various materials. This study demonstrates the facile preparation of TA-functionalized high-efficiency particulate air (HEPA) filter materials and their efficiency in influenza virus capture. Polypropylene HEPA filter fabrics were coated with TA via a dipping/washing process. The TA-functionalized HEPA filter (TA-HF) exhibits a high in-solution virus capture efficiency of up to 2,723 pfu/mm2 within 10 min, which is almost two orders of magnitude higher than that of non-functionalized filters. This result suggests that the TA-HF is a potent anti-influenza filter that can be used in protective equipment to prevent the spread of pathogenic viruses.

Establishment of a rapid ELISPOT assay for influenza virus titration and neutralizing antibody detection.

Seasonal influenza is an acute respiratory infection causing around 500 000 global deaths annually. There is an unmet medical need to develop more effective antiviral drugs and vaccines against influenza infection. A rapid, accurate, high-throughput titration assay for influenza virus particles or neutralizing antibodies would be extremely useful in these research fields. However, commonly used methods such as tissue culture infective dose and plaque-forming units (PFU) for virus particle quantification, and the plaque reduction neutralization test (PRNT) for antibody determination are time-consuming, laborious, and have limited accuracy. In this study, we developed an efficient assay based on the enzyme-linked immunospot (ELISPOT) technique for the influenza virus and neutralizing antibody titration. Two broad-spectrum antibodies recognizing the nucleoproteins of influenza A and B viruses were used in the assay to broadly and highly sensitively detect influenza virus-infected cells at 16 hours postinfection. An optimized cell culture medium with no tosyl phenylalanyl chloromethyl ketone trypsin and high dose oseltamivir acid was used to improve quantitation accuracy. This ELISPOT assay displayed a good correlation (R2 = 0.9851) with the PFU assay when used to titrate 30 influenza virus isolates. The assay was also applied to measure influenza-neutralizing antibodies in 40 human sera samples, showing a good correlation (R2 = 0.9965) with the PRNT assay. This ELISPOT titration assay is a rapid, accurate, high-throughput assay for quantification of influenza virus and neutralizing antibodies, and provides a powerful tool for research into and development of drugs and vaccines against influenza.

The balance between side-chain and backbone-driven association in folding of the α-helical influenza A transmembrane peptide.

The correct balance between attractive, repulsive and peptide hydrogen bonding interactions must be attained for proteins to fold correctly. To investigate these important contributors, we sought a comparison of the folding between two 25-residues peptides, the influenza A M2 protein transmembrane domain (M2TM) and the 25-Ala (Ala25 ). M2TM forms a stable α-helix as is shown by circular dichroism (CD) experiments. Molecular dynamics (MD) simulations with adaptive tempering show that M2TM monomer is more dynamic in nature and quickly interconverts between an ensemble of various α-helical structures, and less frequently turns and coils, compared to one α-helix for Ala25 . DFT calculations suggest that folding from the extended structure to the α-helical structure is favored for M2TM compared with Ala25 . This is due to CH⋯O attractive interactions which favor folding to the M2TM α-helix, and cannot be described accurately with a force field. Using natural bond orbital (NBO) analysis and quantum theory atoms in molecules (QTAIM) calculations, 26 CH⋯O interactions and 22 NH⋯O hydrogen bonds are calculated for M2TM. The calculations show that CH⋯O hydrogen bonds, although individually weaker, have a cumulative effect that cannot be ignored and may contribute as much as half of the total hydrogen bonding energy, when compared to NH⋯O, to the stabilization of the α-helix in M2TM. Further, a strengthening of NH⋯O hydrogen bonding interactions is calculated for M2TM compared to Ala25 . Additionally, these weak CH⋯O interactions can dissociate and associate easily leading to the ensemble of folded structures for M2TM observed in folding MD simulations.

Broadly Neutralizing Antibodies to Highly Antigenically Variable Viruses as Templates for Vaccine Design.

Development of vaccines to highly variable viruses such as Human Immunodeficiency Virus and influenza A viruses faces multiple challenges. In this article, these challenges are described and reverse vaccinology approaches to generate universal vaccines against both pathogens are laid out and compared.

Comprehensive overview of COVID-19 based on current evidence.

In December 2019, twenty-seven pneumonia patients with unknown causes originated in South China seafood market in Wuhan. The virus infection spread rapidly and swept through China in less than a month. Subsequently, the virus was proven a novel coronavirus and named SARS-CoV-2. The outbreak of novel coronavirus has been determined as a Public Health Emergency of International Concern (PHEIC) by WHO on January 31, 2020. Similar to other coronaviruses like the Middle East Respiratory Syndrome (MERS) CoV and Severe Acute Respiratory Syndrome (SARS) CoV, the novel coronavirus was reported to spread via respiratory droplets and close contact from human to human, which means the virus is highly infectious and dangerous. Unfortunately, till now the virus has spread to over 200 countries/territories/areas around the world and the Coronavirus Disease 2019 (COVID-19) outbreak is continuing to grow. Currently, information sharing and transparency are essential for risk assessment and epidemic control in all endemic areas. In this article, we compared SARS-CoV-2 with SARS-CoV and influenza virus, discussed current researching progress of COVID-19, including clinical characteristics, pathological changes, treatment measures, and so on.

High-complexity extracellular barcoding using a viral hemagglutinin.

While single-cell sequencing technologies have revealed tissue heterogeneity, resolving mixed cellular libraries into cellular clones is essential for many pooled screens and clonal lineage tracing. Fluorescent proteins are limited in number, while DNA barcodes can only be read after cell lysis. To overcome these limitations, we used influenza virus hemagglutinins to engineer a genetically encoded cell-surface protein barcoding system. Using antibodies paired to hemagglutinins carrying combinations of escape mutations, we developed an exponential protein barcoding system which can label 128 clones using seven antibodies. This study provides a proof of principle for a strategy to create protein-level cell barcodes that can be used in vivo in mice to track clonal populations.

Potential Role of Endonuclease Inhibition and Other Targets in the Treatment of Influenza.

BACKGROUND: Influenza is a single-stranded RNA virus that is highly contagious and infects millions of people in the U.S. annually. Due to complications, approximately 959,000 people were hospitalized and another 79,400 people died during the 2017-2018 flu season. While the best methods of prevention continue to be vaccination and hygiene, antiviral treatments may help reduce symptoms for those who are infected. Until recently, the only antiviral drugs in use have been the neuraminidase inhibitors: oseltamivir, zanamivir, and peramivir. OBJECTIVE: We reviewed novel drug targets that can be used in the treatment of influenza, particularly in the case of neuraminidase inhibitor-resistant strains that may emerge. RESULTS: More recently, a drug with a new mechanism of action has been approved. Baloxavir marboxil inhibits the influenza cap-dependent endonuclease that is needed for the virus to initiate replication within the host cell. This endonuclease target is within the polymerase acid (PA) subunit of RNA polymerase. Since the RNA-dependent RNA polymerase consists of two other subunits, polymerase basic 1 and 2, RNA polymerase has several targets that prevent viral replication. Other targets still under investigation include viral kinases, endocytosis, and viral fusion. CONCLUSION: Due to the possibility of viral mutations and resistance, it is important to have antivirals with different mechanisms available, especially in the case of a new pandemic strain. Several novel antivirals are within various stages of development and may represent new classes of treatments that can reduce symptoms and complications in those patients who may be at higher risk.

Incorporating G-C Pair-Recognizing Guanidinium into PNAs for Sequence and Structure Specific Recognition of dsRNAs over dsDNAs and ssRNAs.

Recognition of RNAs under physiological conditions is important for the development of chemical probes and therapeutic ligands. Nucleobase-modified dsRNA-binding PNAs (dbPNAs) are promising for the recognition of dsRNAs in a sequence and structure specific manner under near-physiological conditions. Guanidinium is often present in proteins and small molecules for the recognition of G bases in nucleic acids, in cell-penetrating carriers, and in bioactive drug molecules, which might be due to the fact that guanidinium is amphiphilic and has unique hydrogen bonding and stacking properties. We hypothesized that a simple guanidinium moiety can be directly incorporated into PNAs to facilitate enhanced molecular recognition of G-C pairs in dsRNAs and improved bioactivity. We grafted a guanidinium moiety directly into a PNA monomer (designated as R) using a two-carbon linker as guided by computational modeling studies. The synthetic scheme of the PNA R monomer is relatively simple compared to that of the previously reported L monomer. We incorporated the R residue into various dbPNAs for binding studies. dbPNAs incorporated with R residues are excellent in sequence specifically recognizing G-C pairs in dsRNAs over dsDNA and ssRNAs. We demonstrated that the R residue is compatible with unmodified T and C and previously developed modified L and Q residues in dbPNAs for targeting model dsRNAs, the influenza A viral panhandle duplex structure, and the HIV-1 frameshift site RNA hairpin. Furthermore, R residues enhance the cellular uptake of PNAs.

Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis.

Influenza A virus is recognized today as one of the most challenging viruses that threatens both human and animal health worldwide. Understanding the control mechanisms of influenza infection and dynamics is crucial and could result in effective future treatment strategies. Many kinetic models based on differential equations have been developed in recent decades to capture viral dynamics within a host. These models differ in their complexity in terms of number of species elements and number of reactions. Here, we present a new approach to understanding the overall structure of twelve influenza A virus infection models and their relationship to each other. To this end, we apply chemical organization theory to obtain a hierarchical decomposition of the models into chemical organizations. The decomposition is based on the model structure (reaction rules) but is independent of kinetic details such as rate constants. We found different types of model structures ranging from two to eight organizations. Furthermore, the model's organizations imply a partial order among models entailing a hierarchy of model, revealing a high model diversity with respect to their long-term behavior. Our methods and results can be helpful in model development and model integration, also beyond the influenza area.

Model of influenza virus acidification.

Internal acidification of the influenza virus, mediated by the M2 proton channel, is a key step in its life cycle. The interior M1 protein shell dissolves at pH~5.5 to 6.0, allowing the release of vRNA to the cytoplasm upon fusion of the viral envelope with the endosomal membrane. Previous models have described the mechanisms and rate constants of M2-mediated transport but did not describe the kinetics of pH changes inside the virus or consider exterior pH changes due to endosome maturation. Therefore, we developed a mathematical model of M2-mediated virion acidification. We find that ~32,000 protons are required to acidify a typically-sized virion. Predicted acidification kinetics were consistent with published in vitro experiments following internal acidification. Finally, we applied the model to the in vivo situation. For all rates of endosomal maturation considered, internal acidification lagged ~1 min behind endosomal acidification to pH 6. For slow endosomal maturation requiring several minutes or more, internal and endosomal pH decay together in pseudo-equilibrium to the late endosomal pH~5.0. For fast endosomal maturation (≲2 min), a lag of tens of seconds continued toward the late endosomal pH. Recent experiments suggest in vivo maturation is in this "fast" regime where lag is considerable. We predict that internal pH reaches the threshold for M1 shell solvation just before the external pH triggers membrane fusion mediated by the influenza protein hemagglutinin, critical because outward proton diffusion through a single small fusion pore is faster than the collective M2-mediated transport inward.

Weak Multivalent Binding of Influenza Hemagglutinin Nanoparticles at a Sialoglycan-Functionalized Supported Lipid Bilayer.

Quantification of the multivalent interactions of influenza viruses binding at interfaces may provide ways to tackle key biological questions regarding influenza virulence and zoonoses. Yet, the deconvolution of the contributions of molecular and interfacial parameters, such as valency, interaction area, and receptor density, to the binding of whole viruses is hindered by difficulties in the direct determination of these parameters. We report here a chemical platform technology to study the binding of multivalent recombinant hemagglutinin (rHA) nanoparticles at artificial sialoglycan cell receptor-presenting interfaces in which all these parameters can be derived, thus allowing the desired full and quantitative binding analysis. SiO2 substrates were functionalized with supported lipid bilayers containing a targeted and tunable fraction of a biotinylated lipid, followed by the adsorption of streptavidin and biotinylated polyvalent 2,3- or 2,6-sialyl lactosamine (SLN). rHA nanoparticles were used as a virus mimic to provide a good prediction of the number of interactions involved in binding. Low nanomolar affinities and selectivities for binding at the 2,6-SLN platforms were observed for rHA particles from three different virus variants. When fitting the data to a multivalency model, the nanomolar overall affinity appears to be achieved by 6-9 HA-sugar molecular interaction pairs, which individually present a rapid association/dissociation behavior. This dynamic behavior may be an essential biological attribute in the functioning of the influenza virus.

Prediction of the binding affinity of aptamers against the influenza virus.

Thousands of investigations on quantitative structure-activity/property relationships (QSARs/QSPRs) have been reported. However, few publications can be found that deal with QSARs for aptamers, because calculating two-dimensional and three-dimensional descriptors directly from aptamers (typically with 15-45 nucleotides) is difficult. This paper describes calculating molecular descriptors from amino acid sequences that are translated from DNA aptamer sequences with DNAMAN software, and developing QSAR models for the aptamers' binding affinity to the influenza virus. General regression neural network (GRNN) based on Parzen windows estimation was used to build the QSAR model by applying six molecular descriptors. The optimal spreading factor σ of Gaussian function of 0.3 was obtained with the circulation method. The correlation coefficients r from the GRNN model were 0.889 for the training set and 0.892 for the test set. Compared with the existing model for aptamers' binding affinity to the influenza virus, our model is accurate and competes favourably. The feasibility of calculating molecular descriptors from an amino acid sequence translated from DNA aptamer sequences to develop a QSAR model for the anti-influenza aptamers was demonstrated.

Molecular characterization of influenza viruses from women and infants in Sarlahi, Nepal.

We used RT-PCR-electrospray ionization-mass spectrometry to identify subtypes and strains of influenza viruses detected during a maternal influenza immunization study in Nepal from May 2011 to April 2014. Hemagglutinin (HA) gene amino acid (aa) sequences of inferred reference strains were compared to those of the vaccines to determine impact of aa relatedness on vaccine efficacy (VE) and disease severity. Three influenza subtypes and many strains were identified. A(H3N2) strains with less than 13 aa differences in HA compared to vaccine strains (matched) showed higher VE than strains with 13 or more differences (mismatched). Yamagata lineage B strains, which were mismatched to the Victoria strain in the vaccine, demonstrated lower VE compared to Victoria strains. Differences in VE were not statistically significant. All A(H1N1pdm) matched the vaccine strain, with 10 or fewer aa differences. Except for women infected with vaccine-matched strains of influenza A, clinical signs and symptoms did not differ between vaccinated and unvaccinated participants.

Structured illumination microscopy combined with machine learning enables the high throughput analysis and classification of virus structure.

Optical super-resolution microscopy techniques enable high molecular specificity with high spatial resolution and constitute a set of powerful tools in the investigation of the structure of supramolecular assemblies such as viruses. Here, we report on a new methodology which combines Structured Illumination Microscopy (SIM) with machine learning algorithms to image and classify the structure of large populations of biopharmaceutical viruses with high resolution. The method offers information on virus morphology that can ultimately be linked with functional performance. We demonstrate the approach on viruses produced for oncolytic viriotherapy (Newcastle Disease Virus) and vaccine development (Influenza). This unique tool enables the rapid assessment of the quality of viral production with high throughput obviating the need for traditional batch testing methods which are complex and time consuming. We show that our method also works on non-purified samples from pooled harvest fluids directly from the production line.

A Perspective on Nanoparticle Universal Influenza Vaccines.

Annually recurring seasonal influenza causes massive economic loss and poses severe threats to public health worldwide. The current seasonal influenza vaccines are the most effective means of preventing influenza infections but possess major weaknesses. Seasonal influenza vaccines require annual updating of the vaccine strains. However, it is an unreachable task to accurately predict the future circulating strains. Vaccines with mismatched strains dramatically compromise the vaccine efficacy. In addition, the seasonal influenza vaccines are ineffective against an unpredictable pandemic. A universal influenza vaccine would overcome these weaknesses of the seasonal vaccines and abolish the threat of influenza pandemics. One approach under investigation is to design influenza vaccine immunogens based on conserved, type-specific amino acid sequences and conformational epitopes, rather than strain-specific. Such vaccines can elicit broadly reactive humoral and cellular immunity. Universal influenza vaccine development has intensively employed nanotechnology because the structural and morphological properties of nanoparticles dramatically improve vaccine immunogenicity and the induced immunity duration. Layered protein nanoparticles can decrease off-target immune responses, fine-tune antigen recognition and processing, and facilitate comprehensive immune response induction. Herein, we review the designs of effective nanoparticle universal influenza vaccines, the recent discoveries of specific nanoparticle features that contribute to immunogenicity enhancement, and recent progress in clinical trials.

Fluorometric detection of influenza viral RNA using graphene oxide.

Simple and reliable detection of influenza viruses is important for timely prescription of antiviral therapy. Here, we developed a facile fluorometric system for detection of influenza subtype viral genes using graphene oxide (GO). A fluorescent DNA probe complementary to hemagglutinin gene of influenza virus is degraded by the 5' to 3' exonuclease activity of Taq polymerase during PCR. Upon addition of GO, the released fluorophore retains fluorescence without adsorption onto GO, whereas the intact fluorescent DNA probe is adsorbed onto GO with fluorescence quenching. Our multi well plate system can detect as low as 3.8 pg of influenza viral RNA.

Avenues to Characterize the Interactions of Extended N-Glycans with Proteins by NMR Spectroscopy: The Influenza Hemagglutinin Case.

Long-chain multiantenna N-glycans are extremely complex molecules. Their inherent flexibility and the presence of repetitions of monosaccharide units in similar chemical environments hamper their full characterization by X-ray diffraction or standard NMR methods. Herein, the successful conformational and interaction analysis of a sialylated tetradecasaccharide N-glycan presenting two LacNAc repetitions at each arm is presented. This glycan has been identified as the receptor of the hemagglutinin protein of pathogenic influenza viruses. To accomplish this study, a N-glycan conjugated with a lanthanide binding tag has been synthesized, enabling analysis of the system by paramagnetic NMR. Under paramagnetic conditions, the NMR signals of each sugar unit in the glycan have been determined. Furthermore, a detailed binding epitope of the tetradecasaccharide N-glycan in the presence of HK/68 hemagglutinin is described.