LLNL COVID-19 Research and Response
by Lawrence Livermore National Laboratory
November 17, 2020
A machine learning model developed by a team of Lawrence Livermore National Laboratory (LLNL) scientists to aid in COVID-19 drug discovery efforts is a finalist for the Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research.
Using Sierra, the world’s third fastest supercomputer, LLNL scientists created a more accurate and efficient generative model to enable COVID-19 researchers to produce novel compounds that could possibly treat the disease. The team trained the model on an unprecedented 1.6 billion small molecule compounds and one million additional promising compounds for COVID-19, reducing the model training time from one day to just 23 minutes.
“This capability will have a dramatic impact on drug discovery,” said paper co-author and LLNL computer scientist Ian Karlin. “This ability to quickly create high-quality machine learning models changes the time-to-insight from a compute-limited issue to a human-limited one.”
Since the early days of the pandemic, LLNL scientists have been using machine learning to discover countermeasures capable of binding to protein sites in the SARS-CoV-2 virus that causes COVID-19. Lab researchers plan to incorporate the improved generative model into the small molecule drug design loop to create more diverse and potentially more effective drug compounds to synthesize for experimental testing, a critical factor in the race to find new COVID-19 therapeutics….
