Article Synopsis
- Researchers have created ESM3, a powerful language model that can generate functional proteins based on over 3 billion years of evolutionary biology.
- ESM3 processes various aspects of proteins—sequence, structure, and function—allowing it to respond to complex requests and enhance its output accuracy.
- In tests, ESM3 successfully generated a bright fluorescent protein with only 58% similarity to existing ones, simulating around 500 million years of evolutionary divergence.
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Article Abstract
More than 3 billion years of evolution have produced an image of biology encoded into the space of natural proteins. Here, we show that language models trained at scale on evolutionary data can generate functional proteins that are far away from known proteins. We present ESM3, a frontier multimodal generative language model that reasons over the sequence, structure, and function of proteins. ESM3 can follow complex prompts combining its modalities and is highly responsive to alignment to improve its fidelity. We have prompted ESM3 to generate fluorescent proteins. Among the generations that we synthesized, we found a bright fluorescent protein at a far distance (58% sequence identity) from known fluorescent proteins, which we estimate is equivalent to simulating 500 million years of evolution.
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| http://dx.doi.org/10.1126/science.ads0018 | DOI Listing |
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