Simulating 500 million years of evolution with a language model
Paper cited by one technology page, indexed on Europe PMC as PubMed record 39818825 and published in Science; the citing page links this DOI, which is how the record was matched.
Overview
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.
Indexed on Europe PMC as PubMed record 39818825 (DOI 10.1126/science.ads0018). Matched by DOI alone: one technology page cites this DOI among its external links (the pages are listed under Related), and this page was written so that the citation resolves inside OnCo. No figure has been checked by an editor.
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