Screening of world approved drugs against highly dynamical spike glycoprotein of SARS-CoV-2 using CaverDock and machine learning

The new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes pathological pulmonary symptoms. Most efforts to develop vaccines and drugs against this virus target the spike glycoprotein, particularly its S1 subunit, which is recognised by angiotensin-converting enzyme 2. Here we use in-house developed tool CaverDock perform virtual screening glycoprotein using a cryogenic electron microscopy structure (PDB-ID: 6VXX) representative structures of five most populated clusters from previously published molecular dynamics simulation. dataset ligands was obtained ZINC database consists approved for clinical worldwide. Trajectories passage individual through tunnel homotrimer, their binding energies within tunnel, duration contacts with trimer’s three subunits were computed full dataset. Multivariate statistical methods then used establish structure-activity relationships select top candidate movement inhibition. This protocol rapid globally (4359 ligands) in multi-state protein (6 states) showed high robustness rate finished calculations. universal can be applied any an experimental tertiary containing tunnels or channels. will implemented next version CaverWeb ( https://loschmidt.chemi.muni.cz/caverweb/ ) make it accessible wider scientific community.