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The novel Wuhan coronavirus known as SARS-CoV-2 has brought almostunprecedented effects for a non-wartime setting, hitting social, economic andhealth systems hard.~ Being able to bring to bear pharmaceutical interventionsto counteract its effects will represent a major turning point in the fight toturn the tides in this ongoing battle.~ Recently, the World's most powerfulsupercomputer, SUMMIT, was used to identify existing small moleculepharmaceuticals which may have the desired activity against SARS-CoV-2 througha high throughput virtual screening approach. In this communication, wedemonstrate how the use of Bayesian optimization can provide a valuable servicefor the prioritisation of these calculations, leading to the acceleratedidentification of high-performing candidates, and thus expanding the scope ofthe utility of HPC systems for time critical screening

Using Bayesian Optimization to Accelerate Virtual Screening for the Discovery of Therapeutics Appropriate for Repurposing for COVID-19