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Evolutionary-scale prediction of atomic-level protein structure with a language model

9/10 importance · solved · protein science · 2023 · validator confidence 95% · research

The problem

Predicting the 3D structures of the exponentially growing catalog of protein sequences was too slow with existing methods, requiring a breakthrough in folding speed.

Why it matters

Atomic-level protein structures underpin biology and medicine at evolutionary scale, and slow prediction blocked characterization of billions of sequences.

What the AI did

A large protein language model (up to 15B parameters) was trained on millions of sequences and directly infers atomic-resolution structure from primary sequence.

Results

Order of magnitude speed-up in high-resolution structure prediction; structure prediction at resolution of individual atoms as models scale

Impact

The abstract claims this extends high-resolution structure prediction to the scale of hundreds of millions of cataloged proteins.

How important is this problem?

9/10 — major — millions of lives, an industry or a field

Abstract states structure prediction extended to two hundred million cataloged proteins and billions of sequences, with 617 million structures characterized and 225 million high-confidence predictions, a foundational advance.

stated — the source itself gives scale or impact evidence for this rating.

Scale stated in source: billions of protein sequences; 617 million structures characterized, 225 million high-confidence

Ratings use a published rubric and are AI-assisted, not measured or peer-reviewed. Method

Sources & verification

Primary source
https://doi.org/10.1126/science.ade2574
Model / method
Large language model of proteins, up to 15B parameters
Organization
not stated in source
Validator notes
glm-5.3: ok (confidence 95) | Top peer-reviewed venue; AI is the solution; concrete speed-up stated; abstract truncated.
Keywords
protein structure, language model, ESM, deep learning, folding, genomics

A second-stage review judged this entry against the primary source; status “verified”. “Verified” means the evidence supported the claim — it does not mean the underlying result was independently reproduced.

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