Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement
Mathew A. Coban,
Juliet Morrison,
Sushila Maharjan,
David Hyram Hernandez Medina,
Wanlu Li,
Yu Shrike Zhang,
William D. Freeman,
Evette S. Radisky,
Karine G. Le Roch,
Carla M. Weisend,
Hideki Ebihara,
Thomas R. Caulfield
Affiliations
Mathew A. Coban
Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA
Juliet Morrison
Department of Microbiology and Plant Pathology, University of California, 900 University, Riverside, CA 92521, USA
Sushila Maharjan
Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 65 Landsdowne St, Cambridge, MA 02139, USA
David Hyram Hernandez Medina
Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 65 Landsdowne St, Cambridge, MA 02139, USA
Wanlu Li
Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 65 Landsdowne St, Cambridge, MA 02139, USA
Yu Shrike Zhang
Division of Engineering in Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, 65 Landsdowne St, Cambridge, MA 02139, USA
William D. Freeman
Department of Neurology, Mayo Clinic, 4500 San Pablo South, Jacksonville, FL 32224, USA
Evette S. Radisky
Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA
Karine G. Le Roch
Department of Molecular, Cell and Systems Biology, University of California, 900 University, Riverside, CA 92521, USA
Carla M. Weisend
Department of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA
Hideki Ebihara
Department of Molecular Medicine, Mayo Clinic, Rochester, MN 55905, USA
Thomas R. Caulfield
Department of Cancer Biology, Mayo Clinic, 4500 San Pablo Road South, Jacksonville, FL 32224, USA
COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has already infected over 160 million (>20% located in United States) and killed more than 3.3 million people around the world (>20% deaths in USA). As we face one of the most challenging times in our recent history, there is an urgent need to identify drug candidates that can attack SARS-CoV-2 on multiple fronts. We have therefore initiated a computational dynamics drug pipeline using molecular modeling, structure simulation, docking and machine learning models to predict the inhibitory activity of several million compounds against two essential SARS-CoV-2 viral proteins and their host protein interactors—S/Ace2, Tmprss2, Cathepsins L and K, and Mpro—to prevent binding, membrane fusion and replication of the virus, respectively. All together, we generated an ensemble of structural conformations that increase high-quality docking outcomes to screen over >6 million compounds including all FDA-approved drugs, drugs under clinical trial (>3000) and an additional >30 million selected chemotypes from fragment libraries. Our results yielded an initial set of 350 high-value compounds from both new and FDA-approved compounds that can now be tested experimentally in appropriate biological model systems. We anticipate that our results will initiate screening campaigns and accelerate the discovery of COVID-19 treatments.