Identifying protein targets in SARS-CoV-2 via machine learning

The coronavirus disease 2019 (COVID-19) pandemic has affected nearly 271 million people and has claimed 5.32 million lives, the most recent episode being of the delta variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic just adds to the list of infectious diseases that were potential global threats like severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), Ebola, and Zika. Infections like these highlight the need for the development of therapeutic agents to combat emerging pathogens. The process of developing therapeutic solutions to novel viruses is tedious and prohibitively long, taking up to 10 to 15 years of time. The initial step of determining interesting molecules and therapeutic targets for further investigation is crucial due to the vast size of the chemical space, which prevents an exhaustive search using costly experiments and trials.