Our program is focused on two specific proteins of the coronavirus. The first protein is the main protease, Mpro, which is an enzyme of the virus that severs a large poly-peptide into functional proteins that enable the virus to replicate in the human host. The program is attempting to identify molecules that inhibit the function of this enzyme, and potentially stop or slow down the virus’ ability to replicate and cause disease. Since this protease does not have human analogs, potential inhibitors may not affect any human proteins and therefore toxic side effects may be minimized. Several crystal structures of this enzyme have been published, including a high resolution image published on March 20, 2020 (Science 2020, DOI 10.1126/science.abb3405). Using high performance computing and artificial intelligence, we are identifying molecules in various libraries comprised of 1.2 billion compounds, which might inhibit this protein.
The second target is an endoribonuclease, which plays a role in breaking up the ribonucleic acid, or the genetic content, of the virus. Recent studies have demonstrated that the endoribonuclease of many viruses, including the SARS virus of 2003 and, it is believed the SARS-CoV-2, binds to a human host protein. This protein-protein interaction appears to dramatically increase the infectivity of the virus. Because this interaction between a viral protein and a human protein appears to be common to many viruses, compounds that are able to effectively disrupt this interaction, could function as broad spectrum anti-virals in addition to addressing Covid-19.
After identifying promising molecules through in silico screening, we are evaluating the molecules’ potential side effects, as well as their drug-like characteristics. The molecules are being synthesized and their activity evaluated with certain types of assays, which may include binding assays, cellular assays, and the ability to reduce viral activity. The lead compounds are being tested in animals to determine which compound may be appropriate for clinical evaluation.
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