hemagglutinin

Currently available flu medications only target the virus after it has already established an infection, but what if a drug could prevent infection in the first place? Now, scientists have designed drug-like molecules to do just that, by thwarting the first stage of influenza infection. Currently available flu medications only target the virus after it has already established an infection, but what if a drug could prevent infection in the first place? Now, scientists at Scripps Research and the Albert Einstein College of Medicine have designed drug-like molecules to do just that, by thwarting the first stage of influenza infection. The drug-like inhibitors block the virus from entering the body's respiratory cells -- specifically, they target hemagglutinin, a protein on the surface of type A influenza viruses. The findings, published in the Proceedings of the National Academy of Sciences on May 16, 2024, represent an important step forward in developing a drug that can prevent influenza infection. "We're trying to target the very first stage of influenza infection since it would be better to prevent infection in the first place, but these molecules could also be used to inhibit the spread of the virus after one's infected," says corresponding author Ian Wilson, DPhil, the Hansen Professor of Structural Biology at Scripps Research. The inhibitors will need to be further optimized and tested before they can be assessed as antivirals in humans, but the researchers say that these molecules ultimately have the potential to help prevent and treat seasonal flu infections. And, unlike vaccines, the inhibitors likely wouldn't need to be updated yearly. The researchers had previously identified a small molecule, F0045(S), with a limited capacity to bind and inhibit H1N1 type A influenza viruses. "We began by developing a high-throughput hemagglutinin binding assay that allowed us to rapidly screen large libraries of small molecules and found the lead compound F0045(S) with this process," says corresponding author Dennis Wolan, PhD, senior principal scientist at Genentech and former associate professor at Scripps Research. In this study, the team aimed to optimize F0045(S)'s chemical structure to design molecules with better drug-like properties and more specific binding ability to the virus. To start, the Wolan lab used "SuFEx click-chemistry," which was first developed by two-time Nobel laureate and co-author K. Barry Sharpless, PhD, to generate a large library of candidate molecules with various tweaks to F0045(S)'s original structure. When they screened this library, the researchers identified two molecules -- 4(R) and 6(R) -- with superior binding affinity compared to F0045(S). Next, Wilson's lab produced X-ray crystal structures of 4(R) and 6(R) bound to the flu hemagglutinin protein so that they could identify the molecules' binding sites, determine the mechanisms behind their superior binding ability, and identify areas for improvement. "We showed that these inhibitors bind much more tightly to the viral antigen hemagglutinin than the original lead molecule did," says Wilson. "By using click-chemistry, we basically extended the compounds' ability to interact with influenza by making them target additional pockets on the antigen surface." When the researchers tested 4(R) and 6(R) in cell culture to verify their antiviral properties and safety, they found 6(R) was non-toxic and had more than 200-times improved cellular antiviral potency compared to F0045(S). Finally, the researchers used a targeted approach to further optimize 6(R) and develop compound 7, which proved to have even better antiviral ability. "This is the most potent small-molecule hemagglutinin inhibitor developed to date," says corresponding author Seiya Kitamura, who worked on the project as a postdoctoral fellow at Scripps Research and is now an assistant professor at the Albert Einstein College of Medicine. In future studies, the team plans to continue to optimize compound 7 and to test the inhibitor in animal models of influenza. "In terms of potency, it will be hard to improve the molecule any further, but there are many other properties to consider and optimize, for example, pharmacokinetics, metabolism and aqueous solubility," says Kitamura. Because the inhibitors developed in this study only target H1N1 strains of influenza, researchers are also working to develop equivalent drug-like inhibitors to target other strains of influenza such as H3N2 and H5N1. This work was supported by the NIH, the Nathan Shock Institute of Aging Research, and Einstein-Montefiore.

GSK and Vir Biotechnology struck up their influenza R&D collaboration three years ago, aiming to build on a respiratory drug relationship forged at the start of the Covid-19 pandemic. The British pharmaceutical giant ended the Covid alliance last year. Now the influenza partnership is winding down too. The two companies have terminated their research collaboration on Vir’s antibodies for influenza, Vir said in its report of fourth quarter and full year 2023 financial results on Thursday. San Francisco-based Vir retains rights to these antibodies and is now free to seek other partners to advance their development. The end of the influenza collaboration follows the Phase 2 failure of one of the partnered programs, VIR-2482. This antibody, which came from Vir’s proprietary antibody discovery platform, is designed to target a region on the neuromindase protein found on the surface of both influenza A and B strains. A mid-stage clinical trial was evaluating VIR-2482 for the prevention of seasonal influenza A illness. Last July, Vir reported preliminary results showing the antibody did not meet either primary or secondary efficacy goals of the trial. In its report of financial results, Vir said it expects a full analysis of the trial data will publish in a scientific journal in the second quarter of this year. Leerink Partners analyst Roanna Ruiz wrote in Friday research note that the termination of the alliance makes sense, given the Phase 2 failure of VIR-2482. But she added that Vir executives said they are pursuing partnerships for their next-generation influenza programs, which span antibodies and antibody drug conjugates. VIR-2981, an antibody drug candidate for both influenza A and influenza B, is one of the programs Vir said it expects will have an investigational new drug application filed with the FDA in the next 12 to 24 months. The company is also developing VIR-2482 as a prophylactic for influenza A. This antibody targets hemagglutinin, a protein on the surface of the influenza virus. Vir said lab test results show that this antibody has been able to cover all major strains influenza A strains since the 1918 flu pandemic. When GSK and Vir began working together in 2020, the focus was Covid-19 drug R&D. The pharma giant made a $250 million equity investment in its new partner to begin that partnership, which yielded the antibody drug sotrovimab. Though the drug, brand name Xevudy, landed FDA authorization during the pandemic, the FDA later withdrew that regulatory status as the drug proved ineffective against the omicron strain. The influenza partnership began in 2021 with GSK paying Vir $225 million up front and increasing its equity stake by $120 million. Vir stood to receive up to $200 million more upon the achievement of milestones. Vir’s internal pipeline includes a drug candidate in Phase 2 testing for chronic hepatitis delta and another program in Phase 2 testing for chronic hepatitis B. VIR-1388, a T cell vaccine for preventing HIV, is in Phase 1 testing. Vir’s Covid-19 R&D is also continuing without GSK. VIR-7229 is a next-generation Covid antibody that Vir says is AI-engineered to have increased potency, breadth, and resistance to viral escape. The company expects to file the regulatory paperwork later this year to support evaluating this antibody in a Phase 1 clinical trial. Vir reported having $1.6 billion in cash, cash equivalents, and investments as of the end of 2023. “Our financial strength allows us to fund multiple clinical programs through major inflection points while enabling the flexibility to invest in external innovation opportunities,” Vir CEO Marianne De Backer said in a prepared statement. Image by Flickr user quapan via a Creative Commons license

Researchers have shed new light on how viral evolution, population immunity, and the co-circulation of other flu viruses shape seasonal flu epidemics. Researchers have shed new light on how viral evolution, population immunity, and the co-circulation of other flu viruses shape seasonal flu epidemics. The research, published today as a Reviewed Preprint in eLife, explores the relationships among evolutionary and epidemiological quantities in influenza, and presents fundamental findings that substantially advance our understanding of the drivers of influenza epidemics, according to the eLife editors. The authors used a rich set of data sources to provide what the editors say is compelling evidence on the roles of genetic distance, influenza subtype dynamics, and epidemiological indicators in predicting flu epidemics. The findings highlight genetic distance and subtype interference as key factors in determining the timing and severity of annual outbreaks. Influenza viruses continually accumulate genetic changes in two key proteins displayed on their surface -- called haemagglutinin (HA) and neuraminidase (NA) -- a process known as antigenic drift. Antigenic drift allows the virus to escape immune recognition in people who have been vaccinated or had a previous infection, leaving them exposed to re-infection. Of the two types of influenza viruses that routinely circulate together in humans (influenza A and B), influenza A, and particularly subtype A(H3N2), has the fastest rates of antigenic drift and causes the most severe illness and death. Amanda Perofsky, the lead author of the study and a research scientist at the Brotman Baty Institute, University of Washington, US, and Fogarty International Center, National Institutes of Health, US, says: "In theory, antigenic drift will lead to more susceptible individuals, which in turn should lead to more flu infections and larger or more severe epidemics. However, prior evidence for this in epidemiological data has been mixed. Mutations in HA are considered to cause the majority of antigenic drift, so surveillance efforts to monitor and predict influenza evolution focus on HA. There has been less focus on NA, even though antibodies against NA also correlate with immunity and influence infection severity. Moreover, outside of flu pandemics, little is known about how different cocirculating influenza subtypes potentially interfere with each other, affecting the size of outbreaks." In this study, Perofsky and colleagues from the Fred Hutchinson Cancer Center, the Icahn School of Medicine at Mount Sinai, US Centers for Disease Control and Prevention, and World Health Organization tracked A(H3N2) evolutionary dynamics -- measured by both genetic sequences and serological assays -- and linked this to epidemiological flu surveillance data in the US over 22 influenza seasons before the COVID-19 pandemic. They started out by identifying different indicators of flu evolution each season, using HA and NA genetic sequence data from the Global Initiative on Sharing Avian Influenza Data (GISAID) Epiflu database and serological data on immune cross-reactivity between viruses provided by World Health Organization Global Influenza Surveillance and Response System (GISRS) Collaborating Centres in Tokyo, London, Melbourne and Atlanta. They created phylogenetic trees showing lines of evolution of A(H3N2) viruses over time and measured genetic and antigenic distances between viruses circulating in consecutive seasons, to show how far apart the viruses evolved in that timeframe. Next, the team explored which of these measures of viral 'fitness' are most strongly related to variation across A(H3N2) flu outbreaks in different years. When comparing the predictive performance of sequence-based and serological evolutionary metrics, they found that genetic distances based on broad sets of antigenic sites ("epitopes") in HA and NA had the strongest, most consistent relationship with the disease burden of annual epidemics, rates of virus transmission, and severity of infection, and influenced the dominant subtype of influenza A -- A(H3N2) or A(H1N1) -- circulating in each season. When relating genetic distance in HA versus NA to A(H3N2) epidemiology, antigenic drift of H3 (the HA antigen of the A(H3N2) virus) was more strongly linked to epidemic size, viral transmissibility, the age distribution of cases, and the number of excess deaths caused by the A(H3N2) virus, while antigenic drift of N2 (the NA antigen of the A(H3N2) virus) was more strongly linked to the intensity of epidemics (the "sharpness" of the epidemic curve) and greater prevalence of A(H3N2) cases relative to A(H1N1) cases in the population. Increased drift in N2 was also associated with fewer days from epidemic onset to peak incidence (a measure of the speed of the epidemic). "The direct link between NA antigenic drift and A(H3N2) incidence patterns was a surprising and key result from our study," says Perofsky. "We expected HA to exhibit stronger associations with seasonal incidence, given that it elicits a stronger immune response than NA." Taken together, the authors' results showed that greater antigenic drift in both HA and NA was linked to larger, more intense epidemics, higher transmission, a greater dominance of the A(H3N2) subtype, and more cases in adults than children. Finally, the team applied machine learning models to assess the relative importance of viral evolution, prior population immunity, the co-circulation of other flu viruses, and vaccine coverage and effectiveness in predicting regional A(H3N2) epidemic dynamics. Using one of the models (called a random forest) they could accurately predict regional epidemic size, peak incidence, and subtype dominance patterns of seasonal outbreaks that occurred between 1997 and 2019. Surprisingly, they found that the incidence of A(H1N1) was more predictive of A(H3N2) epidemics than viral evolution, suggesting that interactions between different viral subtypes -- that is, subtype interference -- play a key role in influenza type A infection dynamics. "Our study shows that influenza epidemic dynamics are shaped in part by the virus' antigenic drift in both surface proteins, and that genetic sequence indicators of antigenic drift were more informative than serological (or antibody) data for predicting epidemics in the timeframe analysed," concludes senior author Cécile Viboud, a staff scientist at Fogarty International Center, National Institutes of Health, US. "Our work is the first to link NA antigenic drift to epidemic burden, timing, and the age distribution of infections. The connection between NA drift and seasonal incidence further highlights the importance of monitoring evolution of both HA and NA to inform the selection of strains for annual flu vaccines and epidemic forecasting efforts."