Model Book/RoseTTAFold All-Atom

RoseTTAFold All-Atom

B+

UW Baker Lab

Structure PredictionComplex PredictionSmall Molecule Bindingopen
Updated 1 month ago
NextIn take

RoseTTAFold-AA is betting that the future is unified all-atom models, and they're probably right — the question is whether the Baker Lab or the Boltz team gets there first with production-grade accuracy.

Specifications

ArchitectureThree-track neural network extended to all-atom representation including small molecules and ions
Parameters~100M
Training DataPDB structures including protein-ligand and protein-nucleic acid complexes
LicenseBSD license. Fully open weights and code from the Baker Lab.
Hardware1x A100 40GB for most predictions
Inference CostSelf-hosted — ~$0.02/prediction on cloud GPU
API AvailableNo
Weights AvailableYes

Benchmark Performance

BenchmarkScore
CASP150.79 GDT-TS (avg)
PoseBusters52% valid

When to Use This

  • +Predictions involving non-standard molecules (cofactors, ions, modified residues)
  • +When you need an all-atom open-source alternative to AF3

When NOT to Use This

  • Pure protein structure prediction — Boltz-1 is more accurate
  • High-accuracy ligand docking — Boltz-2 or AF3 are better

Production Readiness

research

Known Users

  • Baker Lab collaborators
  • Academic structural biology groups

Grade Rationale

B+

The most ambitious open model — attempting to handle proteins, ligands, nucleic acids, and ions in one framework. The all-atom approach is the right long-term architecture, but accuracy still lags specialized models on each individual task.

Sources

Update History

2026-02-15Initial entry