Binding energies along the s-glycoprotein tunnel were calculated for every drug and all six structures. We then compared the results obtained to identify the best ligands for each tunnel position in each conformation. We also analysed each drug to identify the contacts made with each monomeric unit of the s-glycoprotein trimer. This allowed us to select drugs that were predicted to interact with all three monomers and are thus likely to suppress opening of the S1 subunits and thereby prevent the binding of the s-glycoprotein to ACE-2. Finally, we performed quantitative structure-activity analysis (QSAR) to correlate the binding energies of the drugs with their physicochemical properties and used multivariate statistical methods to select top candidates. We are currently implementing this virtual screening methodology into CaverWeb to allow the community to perform automated calculations against other target proteins using the globally approved drug dataset (Figure ).