Virus inactivation prediction-The emergence of new viruses during pandemics has highlighted the need to assess the efficacy of disinfection methods on the variants of concern. 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 due to the low costs and sensitivity. However, genome-based methods underestimate virus inactivation rates by certain disinfectants, such as chlorine and chlorine dioxide, because the viral protein capsids protect the genome from the attack of oxidant molecules. Oxidation of viral proteins, which is a relevant process leading to virus inactivation, yet largely ignored in previous studies compared to the genome characterization. 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.