Broad-Spectrum Coronavirus Inhibitors Discovered by Modeling Viral Fusion Dynamics

Charles B Reilly¹Joel Moore¹Shanda Lightbown¹Austin Paul¹Sylvie G Bernier¹Kenneth E Carlson¹Donald Ingber^1,2,3*

• ¹Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, United States
• ²Department of Bioengineering, John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, United States
• ³Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, United States

Development of oral, broad-spectrum therapeutics targeting SARS-CoV-2, its variants, and related coronaviruses could curb the spread of COVID-19 and avert future pandemics. We created a novel computational discovery pipeline that employed molecular dynamics simulation (MDS), artificial intelligence (AI)-based docking predictions, and medicinal chemistry to design viral entry inhibitors that target a conserved region in the SARS-CoV-2 spike (S) protein that mediates membrane fusion. DrugBank library screening identified the orally available, FDAapproved AXL kinase inhibitor bemcentinib as binding this site and we demonstrated that it inhibits viral entry in a kinase-independent manner. Novel analogs predicted to bind to the same region and disrupt S protein conformational changes were designed using MDS and medicinal chemistry. These compounds significantly suppressed SARS-CoV-2 infection and blocked the entry of S protein-bearing pseudotyped a, b ,g, d, o variants as well as SARS-CoV and MERS-CoV in human ACE2-expressing cells or DPP4-expressing more effectively than bemcentinib.When administered orally, the optimized lead compound also significantly inhibited SARS-CoV2 infection in mice. This computational design strategy may accelerate drug discovery for a broad range of applications.