K-State-led research consortium uses artificial intelligence to find promising drugs for COVID-19 treatment
Kansas State University is leading a new research consortium that focuses on speeding up research for COVID-19 drug treatments. The consortium is making all its findings freely available to researchers worldwide.
Ho-Leung Ng, K-State associate professor of biochemistry and molecular biophysics, is the founder of the Open Source COVID-19, or OSC19, research consortium that is using computational chemistry to minimize the traditional, slow research lab work for COVID-19 drug treatments.
A focus of OSC19 is Mpro protease, an enzyme that controls viral replication. Ng said researchers can stop SARS-CoV-2 — the virus that causes COVID-19 — from replicating by disrupting the function of this enzyme. The challenge is to find pharmaceuticals that can safely cause the disruption.
The OSC19 deep-learning research effort screens known pharmaceuticals, ones that doctors have a good handle on their safety against the Mpro protease. Once effective drugs are found, OSC19 also screens chemically similar molecules to identify novel pharmaceuticals. With a collection of promising potential drugs, success against COVID-19 increases compared to identifying only one potential drug, Ng said.
“Our current computational and experimental results are that GC376 and boceprevir are the most promising for potential chemical optimization," Ng said. "We are currently synthesizing and testing analogs of these two drugs against COVID-19."
Researchers are identifying which anti-COVID-19 molecules exhibit the necessary chemical properties, such as solubility, low toxicity, and drug activity. Ng said an advantage of this approach is that it helps researchers move away from conventional molecules to those that experienced professionals would not have predicted. Experimental validation of OSC19 compounds by enzyme assays, crystallography and antiviral activity is being led by Troy Messick at the Wistar Institute.
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