Highlights d This work extends our MANORAA platform for analyzing protein-ligand interactions d We provide algorithms to interpret drug binding affinities proven experimentally d Molecular anchors and effects of distance descriptors guide drug design d MANORAA also pinpoints the drug's side effects and target organs

With the rapid rate of SARS-CoV-2 Main protease (Mpro) structures deposition, a computational method that can combine all the useful structural features becomes crucial. This research focuses on the frequently occurring atoms and residues to find a generalized strategy for inhibitor design given a large amount of protein complexes from SARS-CoV in contrast to SARS-CoV-2 Mpro. By superposing large numbers of the ligands onto the protein template and grid box, we can analyse which part of the structure is conserved from position-specific interaction for both data sets for the development of pan-Mpro antiviral design. The difference in conserved recognition sites from the crystal structures can be used to determine specificity determining residues for designing selective drugs. We can display pictures of the imaginary shape of the ligand by unionising all atoms from the ligand. We also pinpoint the most probable atom adjustments to imitate the frequently found densities from the ligand atoms statistics. With molecular docking, Molecular Dynamics simulation, and MM-PBSA methods, a carbonyl replacement at the nitrile warhead (N5) of Paxlovid’s Nirmatrelvir (PF-07321332) was suggested. By gaining insights into the selectivity and promiscuity regions for proteins and ligands, crucial residues are highlighted, and the antiviral design strategies are proposed.