Biophysical modeling of the SARS-CoV-2 viral cycle reveals ideal antiviral targets

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

Effective 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.