Exploring SARS-CoV-2 Spike RBD Pockets as Targets for Generic Drugs: A Combined Computational, Biophysical, and Biological Approach

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was a pandemic that killed over 6 million people worldwide, with devastating social and economic impacts still being felt today. Despite the recent and successful development of RNA vaccines, there remains a need for antiviral drugs to treat patients at risk for drug resistance, immunological disorders, or reduced treatment efficacy. In this regard, several computational approaches have been carried out to find small molecules targeting the SARS-CoV-2 Spike S protein, and drug repurposing strategies have been applied to find rapid and accessible candidates for clinical use. In this work, we conduct an exhaustive computational study of the receptor binding domain (RBD) of the spike S protein to identify and characterize druggable pockets and to identify generic drugs as blockers of SARS-CoV-2 entry. The combination of computational screening, biophysical studies in both the RBD (Wuhan-Hu-1 and Omicron BA.1 variants) and Spike protein (Wuhan variant), and the <i>in vitro</i> assays in SARS-CoV-2 Wuhan-Hu-1, Delta, and Omicron BA.1 has led to the identification of generic drugs with S protein binding properties and antiviral activity. Based on <i>in vitro</i> antiviral activity and mechanism of action analysis at the atomic/molecular level, fingolimod exhibited the most promising profile for a possible SARS-CoV-2 antiviral treatment.