A next-gen AI protein folder that could help science? Meta's good for something
ESM-2 is the largest model of its kind, and apparently predicts structures faster than similar systems; it is up to 60X faster than previous state-of-the-art systems like AlphaFold or Rosetta, which can take over ten minutes to generate an output, according to Meta.
The model was able to create the ESM Metagenomic Atlas, predicting over 600 million structures from theprotein database in just two weeks running on 2,000 GPUs. On a single Nvidia V100 GPU, it takes just 14.2 seconds to simulate a protein made up of 384 amino acids. It seems from the paper that Meta said its system mostly, but not fully, matched AlphaFold on accuracy though its speed is the key thing, allowing it to predict more proteins.
"With current state-of-the-art computational tools, predicting structures for hundreds of millions of protein sequences in a practical time frame could take years, even using the resources of a major research institution. To make predictions at the scale of metagenomics a breakthrough in prediction speed is critical," the Facebook owner said.
Meta hopes ESM-2 and the ESM Metagenomic Atlas will help advance science by aiding scientists studying evolutionary history or tackling disease and climate change."To extend this work even further, we're studying how language models can be used to design new proteins and contribute to solving challenges in health, disease, and the environment," the biz concluded. ®
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