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Computing – Modeling COVID dynamics

ORNL has modeled the spike protein that binds the novel coronavirus to a human cell for better understanding of the dynamics of COVID-19. Credit: Stephan Irle/ORNL, U.S. Dept. of Energy

To better understand the spread of SARS-CoV-2, the virus that causes COVID-19, Oak Ridge National Laboratory researchers have harnessed the power of supercomputers to accurately model the spike protein that binds the novel coronavirus to a human cell receptor.

These simulations also shed light on the ligand molecules that can inhibit such binding, pointing the way to potential drug therapies.

An ultrafast quantum chemical modeling method provides information about the critical electronic interactions between protein and ligand chemicals, going beyond the classical interaction models that are normally employed in computational drug discovery.

The findings will enable accurate predictions of the performance of currently available inhibitors and inform the future development of even more potent, novel inhibitor compounds, demonstrating the effectiveness of quantum chemical approaches in simulation for drug discovery.

“Quantum mechanics on supercomputers accelerates computational COVID-19 drug discovery by accurately describing inhibitor–virus protein interactions,” said ORNL’s Stephan Irle.

Learn more about ORNL research in the fight against COVID-19.