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Researchers convey modern AI and simulation instruments to the COVID-19 battlefront


Argonne collaborations bring computational tools to the forefront of COVID-19 research
ALCF’s AI- and simulation-enabled extension of the Theta supercomputer, ThetaGPU. Credit score: Argonne Nationwide Laboratory

In its on-going marketing campaign to disclose the interior workings of the Sar-CoV-2 virus, the U.S. Division of Power’s (DOE) Argonne Nationwide Laboratory is main efforts to couple synthetic intelligence (AI) and cutting-edge simulation workflows to raised perceive organic observations and speed up drug discovery.

Argonne collaborated with tutorial and business analysis companions to attain close to real-time suggestions between simulation and AI approaches to grasp how two proteins within the SARS-CoV-2 viral genome, nsp10 and nsp16, work together to assist the virus replicate and elude the host’s immune system.

The group achieved this milestone by coupling two distinct {hardware} platforms: Cerebras CS-1, a processor-packed silicon wafer deep studying accelerator; and ThetaGPU, an AI- and simulation-enabled extension of the Theta supercomputer, housed on the Argonne Management Computing Facility, a DOE Workplace of Science Consumer Facility.

To allow this functionality, the group developed Stream-AI-MD, a novel utility of the AI methodology known as deep studying to drive adaptive molecular dynamics (MD) simulations in a streaming method. Information from simulations is streamed from ThetaGPU onto the Cerebras CS-1 platform to concurrently analyze how the 2 proteins work together.

Argonne collaborations bring computational tools to the forefront of COVID-19 research
Cerebras CS-1 is a processor-packed silicon wafer deep studying accelerator. Credit score: Argonne Nationwide Laboratory

“This must be completed at a scale that’s unprecedented for the reason that knowledge era and AI parts need to run side-by-side,” mentioned Argonne computational biologist Arvind Ramanathan, a member of the analysis group. “The thought is, if one machine is nice at doing MD simulations and one other is superb at AI, then why not couple the 2 to provide a a lot bigger system that provides extra throughput with AI,” defined Ramanathan.

One of many AI strategies that they are utilizing is named a variational autoencoder, which learns to seize probably the most important info from MD simulations. The dimensions of the simulation knowledge units is lowered in a technique to make it simpler for researchers to grasp the dynamics occurring within the simulation.

By operating their deep studying element on Cerebras CS-1, they will establish binding pockets—tiny areas which may develop throughout the formation of the 2 proteins—that may be focused for small-molecule drug design.

These workflows will in the end allow drug discoveries that deal with each the SARS-CoV-2 virus and different ailments, when the bodily processes underlying particular organic features are characterised, mentioned Ramanathan. And whereas the examine at present doesn’t concentrate on vaccines, the event of extra advanced fashions might result in vaccine design.

“This iterative workflow of supporting streaming AI and MD strategies on rising {hardware} platforms will pave the best way for advancing our data of how proteins operate,” mentioned Ramanathan. “Within the context of the SARS-CoV-2 virus, a elementary understanding of molecular processes, such because the nsp16-nsp10 interplay, is necessary if we wish to design medication that may cease the virus in its path.”

The analysis was revealed within the proceedings from the Platform for Superior Scientific Computing Convention (PASC ’21), July 5–9, 2021, Geneva, Switzerland. ACM, New York, NY, USA.


The AI-driven initiative that is hastening the invention of medication to deal with COVID-19


Extra info:
Alexander Brace et al, Stream-AI-MD, Proceedings of the Platform for Superior Scientific Computing Convention (2021). DOI: 10.1145/3468267.3470578

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Argonne Nationwide Laboratory


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