Quantum Computing Advances in COVID-19 Drug Research
The Oak Ridge National Laboratory (ORNL) is at the forefront of a significant research project aimed at combating COVID-19. This initiative, supported by the DOE Office of Science's National Virtual Biotechnology Laboratory with funding provided by the Coronavirus CARES Act, is utilising the power of supercomputers to refine the screening of potential drug molecules that can disrupt the coronavirus's spike protein.
The research, led by Jeremy Smith of ORNL, is being carried out on two major compute platforms: the Oak Ridge National Laboratory's own ORNL Summit IBM GPU-based system, the #2 fastest supercomputer in the world, and the Stampede2 system of the Texas Advanced Computing Center, which ranks #35 fastest globally and #3 in U.S. academia.
Researchers are employing predictive quantum mechanical methods for the reliable prediction of binding affinity of ligands to the protein. The process begins with a computational prescreening based on a structural model of the target protein's atoms. The top 100 strongest-binding compounds were validated and further refined using FMO-MP2/PCM single point energy calculations.
The ORNL Summit performed about 2.07 million physical docking calculations on a smaller database and 2.4 billion docking calculations with the Enamine REAL database of compounds. The binding energy for one ligand and protein complex can be calculated on Stampede2 in one or two hours. If another computer node is available, the scoring function of several hundred compound complexes can be calculated in a day.
The research group involved in this computer-controlled method for in-silico drug discovery to identify potential drugs that prevent the binding of the coronavirus spike protein to human cells is not explicitly named in the provided search results. However, companies like Merck are known to work on AI-powered drug discovery tools, which may include such computational methods.
The work, published in the Journal of Chemical Information and Modeling with the DOI 10.1021/acs.jcim.0c01010, is part of a larger drug discovery pipeline. The researchers plan to investigate 15 spike protein clusters and refine the binding energies of 150 protein ligand complexes in the pipeline study.
Successful vaccines targeting the coronavirus's spike protein have started to drive down global infections. However, the ongoing research at ORNL is crucial in the continued efforts to combat COVID-19, with nearly four million people having died from the virus and over 180 million people having been infected since December 2019. The research group's work is described as a "supercomputer-driven pipeline for in silico drug discovery."
Funding and support for the drug discovery pipeline work were provided by the Alabama Supercomputer Authority, the National Institutes of Health, a National Science Foundation Graduate Research Fellowship, the Cancer Research Informatics Shared Resource Facility of the University of Kentucky Markey Cancer Center, and the University of Kentucky's Center for Computational Sciences (CCS) high-performance computing resources. Computer time on Summit and Stampede2 was granted by the HPC Covid-19 Consortium.
As the world continues to grapple with the COVID-19 pandemic, the work being done by the ORNL research team offers a glimmer of hope in the fight against the virus. With the power of supercomputers, researchers are able to refine potential drug molecules that can disrupt the spike protein, potentially leading to new treatments and vaccines.
