Highly synergistic combinations of nanobodies that target SARS-CoV-2 reduce viral load in hACE2 transgenic mice

The ongoing emergence of SARS-CoV-2 variants threatens current vaccines and renders current therapeutic antibodies obsolete, demanding powerful new treatments that can resist viral escape. We therefore generated a large nanobody repertoire to saturate the distinct and highly conserved available epitope space of SARS-CoV-2 spike, including the S1 receptor binding domain, N-terminal domain, and the S2 subunit, to identify new nanobody binding sites that may reflect novel mechanisms of viral neutralization. Structural mapping and functional assays show that these highly stable monovalent nanobodies potently inhibit SARS-CoV-2 infection, display numerous neutralization mechanisms, are effective against past and present emerging variants of concern, and are resistant to mutational escape. Rational combinations of these nanobodies that bind dissimilar sites within and between spike subunits exhibit extraordinary synergy and suggest multiple tailored therapeutic and prophylactic strategies. All mouse involved experiments were performed in compliance with the Institutional Animal Care and Use Committee and mice were housed and maintained in a specific pathogen-free conditions at Seattle Children's Research Institute. Infected mice with SARSCoV- 2 were housed in a Biosafety Level 3 facility in an Animal Biohazard Containment Suite. Prophylactic intranasal application of a synergistic pair of unmodified nanobodies in 10-12 week-old female K18-hACE2 transgenic mice, a mouse model of SARS-CoV-2 infection, showed significant reduction in viral load after 3 days post-challenge with SARS-CoV-2, the first demonstration of synergy in vivo. In summary, our results show that our diverse repertoire of nanobodies can neutralize current variants of live SARS-CoV-2, pairs of nanobodies that bind distinct sites on spike show tremendous synergy in neutralizing efficacy in vitro, and the application of synergizing pair of nanobodies translates to an in vivo mouse model of SARSCoV- 2. Research funded by the Mathers Foundation, Robertson Foundation, NIH P41GM109824.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Targeting virus-induced vulnerabilities using synthetic lethality as a new class of host-based antivirals

RNA viruses are the major class of human pathogens responsible for many global health crises, including the COVID-19 pandemic. However, the current repertoire of U.S. Food and Drug Administration (FDA)-approved antivirals is limited to only nine out of the known 214 human-infecting RNAviruses, and almost all these antivirals target viral proteins. Traditional antiviral development generally proceeds in a virus-centric fashion, and successful therapies tend to be only marginally effective as monotherapies, due to dose-limiting toxicity and the rapid emergence of drug resistance. Host-based antivirals have potential to alleviate these shortcomings, but do not typically discriminate between infected and uninfected cells, thus eliciting unintended effects. In infected cells where host proteins are repurposed by a virus, normal host protein functions are compromised;a situation analogous to a loss-of-function mutation, and cells harboring the hypomorph have unique vulnerabilities. As well-established in model systems and in cancer therapeutics, these uniquely vulnerable cells can be selectively killed by a drug that inhibits a functionally redundant protein. This is the foundation of synthetic lethality (SL). To test if viral induced vulnerabilities can be exploited for viral therapeutics, we selectively targeted synthetic lethal partners of GBF1, a Golgi membrane protein and a critical host factor for many RNA viruses including poliovirus, Coxsackievirus, Dengue, Hepatitis C and E virus, and Ebola virus. GBF1 becomes a hypomorph upon interaction with the poliovirus protein 3A. A genome-wide chemogenomic CRISPR screen identified synthetic lethal partners of GBF1 and revealed ARF1 as the top hit. Disruption of ARF1, selectively killed cells that synthesize poliovirus 3A alone or in the context of a poliovirus replicon. Combining 3A expression with sub-lethal amounts of GCA - a specific inhibitor of GBF1 further exacerbated the GBF1-ARF1 SL effect. Together our data demonstrate proof of concept for host-based SL targeting of viral infection. We are currently testing all druggable synthetic lethal partners of GBF1 from our chemogenomic CRISPR-screen, in the context of dengue virus infection for their abilities to selectively kill infected cells and inhibit viral replication and infection. Importantly, these SL gene partners of viral-induced hypomorphs only become essential in infected cells and in principle, targeting them will have minimal effects on uninfected cells. Our strategy to target SL interactions of the viral-induced hypomorph has the potential to change the current paradigm for host-based therapeutics that can lead to broad-spectrum antivirals and can be applied to other intracellular pathogens. This work is supported by National Institutes of Health grants R01 GM112108 and P41 GM109824, R21 AI151344 and foundation grant FDN-167277 from the Canadian Institutes of Health Research.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Designing for the Embedding of Employee Voice

Previous research on employee voice has sought to design technological solutions that address the challenges of speaking up in the workplace. However, effectively embedding employee voice systems in organisations requires designers to engage with the social processes, power relations and contextual factors of individual workplaces. We explore this process within a university workplace through a research project responding to a crisis in educational service delivery arising from the COVID-19 pandemic. Within a successful three-month staff-led engagement, we examined the intricacies of embedding employee voice, exploring how the interactions between existing actors impacted the effectiveness of the process. We sought to identify specific actions to promote employee voice and overcome barriers to its successful establishment in organisational decision-making. We highlight design considerations for an effective employee voice system that facilitates embedding employee voice, including assurance, bounded accountability and bias reflexivity. © 2023 ACM.

In-Silico Approaches for the Screening and Discovery of Broad-Spectrum Marine Natural Product Antiviral Agents Against Coronaviruses

The urgent need for SARS-CoV-2 controls has led to a reassessment of approaches to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. There are yet no clinically approved broad-spectrum antivirals available for beta-coronaviruses. Discovery pipelines for pan-virus medications against a broad range of betacoronaviruses are therefore a priority. A variety of marine natural product (MNP) small molecules have shown inhibitory activity against viral species. Access to large data caches of small molecule structural information is vital to finding new pharmaceuticals. Increasingly, molecular docking simulations are being used to narrow the space of possibilities and generate drug leads. Combining in-silico methods, augmented by metaheuristic optimization and machine learning (ML) allows the generation of hits from within a virtual MNP library to narrow screens for novel targets against coronaviruses. In this review article, we explore current insights and techniques that can be leveraged to generate broad-spectrum antivirals against betacoronaviruses using in-silico optimization and ML. ML approaches are capable of simultaneously evaluating different features for predicting inhibitory activity. Many also provide a semi-quantitative measure of feature relevance and can guide in selecting a subset of features relevant for inhibition of SARS-CoV-2.

Contemporary Approaches to the Discovery and Development of Broad-Spectrum Natural Product Prototypes for the Control of Coronaviruses.

The pressing need for SARS-CoV-2 controls has led to a reassessment of strategies to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. This review article addresses how contemporary approaches involving computational chemistry, natural product (NP) and protein databases, and mass spectrometry (MS) derived target-ligand interaction analysis can be utilized to expedite the interrogation of NP structures while minimizing the time and expense of extraction, purification, and screening in BioSafety Laboratories (BSL)3 laboratories. The unparalleled structural diversity and complexity of NPs is an extraordinary resource for the discovery and development of broad-spectrum inhibitors of viral genera, including Betacoronavirus, which contains MERS, SARS, SARS-CoV-2, and the common cold. There are two key technological advances that have created unique opportunities for the identification of NP prototypes with greater efficiency: (1) the application of structural databases for NPs and target proteins and (2) the application of modern MS techniques to assess protein-ligand interactions directly from NP extracts. These approaches, developed over years, now allow for the identification and isolation of unique antiviral ligands without the immediate need for BSL3 facilities. Overall, the goal is to improve the success rate of NP-based screening by focusing resources on source materials with a higher likelihood of success, while simultaneously providing opportunities for the discovery of novel ligands to selectively target proteins involved in viral infection.