Assessing the evolutionary safety of mutagenic antiviral drugs in the context of recombination

The COVID-19 pandemic highlighted critical gaps in our antiviral arsenal, with many families of viruses lacking targeted inhibitors. Molnupiravir, a broad-spectrum antiviral drug which works by introducing mutations into viral genomes, showed initial promise as a treatment. However, recent research has shown that in some cases, rather than clearing SARS-CoV-2 infections, this treatment can create viruses with large numbers of mutations, which sometimes continue to spread between patients. Such observations have raised important questions about whether a drug with this mechanism of action could accelerate the evolution of variants of concern that evade existing immunity or have increased transmissibility. To address these issues, we need to better understand the within-host evolutionary processes that drive the evolution of these mutated virus genomes.

This PhD project will combine computational modelling and experimental approaches to understand how viruses evolve under mutagenic drug pressure. The project will particularly focus on the question of whether viral recombination – the process by which viruses can exchange genetic material – is necessary to allow viruses to remove deleterious mutations induced by the drug while preserving adaptive mutations in regions that interact with the immune system. Using existing data for SARS-CoV-2, and in vitro experimental work with other coronaviruses, the student will:

1. Develop computational models to understand how recombination affects viral evolution under drug pressure
2. Analyse existing viral sequence data to track mutation patterns
3. Conduct laboratory experiments to test model predictions using coronavirus systems

This work will provide important information both in interpreting the risks and benefits of existing drugs such as molnupiravir, and in understanding of the safety profiles of the class of drugs with this mechanism of action. It will also seek to understand why previous attempts to model the ‘evolutionary safety’ of molnupiravir yielded results inconsistent with experimental data.

The successful candidate will gain expertise in viral evolution, computational biology, and experimental virology. They will develop and expand skills in genome sequencing, phylogenetic analysis, Python programming, and BSL-2 laboratory techniques. The project offers opportunities to engage with both theoretical and experimental aspects of viral evolution, providing excellent training for future careers in academic or industry research. They will join collaborative teams at LSHTM and RVC, benefiting from complementary expertise in computational and experimental approaches. We are supportive of diverse career paths and welcome applicants with a diversity of backgrounds, experience and ideas. We encourage applications from those with non-traditional academic backgrounds. Informal enquiries are welcome and may be addressed to the principal supervisor.