Virus inactivation prediction. The global spread of viral outbreaks has highlighted the need to assess the efficacy of disinfection methods on the emerging variants. The current gold standard to track the levels of infective viruses before and after the disinfection treatment is culture-based approaches, but a significant number of emerging viruses cannot be cultured easily in laboratory. The degradation of viral biomolecules during the disinfection are relevant to the infectivity loss of viruses. Our current molecular-based virus inactivation prediction is heavily relied on genome-based methods. However, genome-based methods may underestimate virus inactivation because protein reactions also play a role in virus inactivation. To bridge the knowledge gap, we are interested in developing high-throughput and high-sensitive proteomic analysis, and integrating the experimental data with molecular dynamics simulations to develop a molecular-based model for predicting virus inactivation kinetics.
The work if funded by:
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National Science Foundation, Environmental Engineering program, "Insights into biomolecular reactivity and structure for virus inactivation prediction”, award #CBET 2212779
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UB School of Public Health and Health Professions Pilot Funding Program, "Reducing health impacts of airborne exposure to traffic air pollution and virus transmission: An intervention study on bus drivers”
