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Biophysical Modeling Of The SARS-CoV-2 Viral Cycle Reveals Ideal Antiviral Targets

Brian T. Castle, Carissa Dock, Mahya Hemmat, Susan Kline, Christopher Tignanelli, Radha Rajasingham, David Masopust, Paolo Provenzano, Ryan Langlois, Timothy Schacker, Ashley Haase, David J. Odde

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AbstractEffective therapies for COVID-19 are urgently needed. Presently there are more than 800 COVID-19 clinical trials globally, many with drug combinations, resulting in an empirical process with an enormous number of possible combinations. To identify the most promising potential therapies, we developed a biophysical model for the SARS-CoV-2 viral cycle and performed a sensitivity analysis for individual model parameters and all possible pairwise parameter changes (162 = 256 possibilities). We found that model-predicted virion production is fairly insensitive to changes in most viral entry, assembly, and release parameters, but highly sensitive to some viral transcription and translation parameters. Furthermore, we found a cooperative benefit to pairwise targeting of transcription and translation, predicting that combined targeting of these processes will be especially effective in inhibiting viral production.