AlphaFold 2

Original AlphaFold; monomer and multimer structure prediction from sequence.

Developer: Google DeepMind

Commercial use OKFree for commercial use

Overview

Developer
Google DeepMind
Commercial rights
Commercial OK
Commercial cost
Free commercially
Compute
Heavy GPU
Open weights
Yes
Last verified

Capabilities

Predicts protein structure from sequence. Input: FASTA (monomer or multimer); output: 5 ranked all-atom models with pLDDT and PAE, plus MSAs. Still the workhorse for binder-design filtering and the engine inside BindCraft/ColabFold.

When to use it

Still the workhorse for monomer and protein-protein complex prediction and the engine inside many binder pipelines. Weaker on ligands and nucleic acids than AF3/Boltz-2, and MSA generation is the slow step.

Input / Output

Input
FASTA (monomer or multimer)
Output
5 ranked all-atom models with pLDDT and PAE, plus MSAs

Compute

Heavy GPU. Other tools with this compute profile →

Commercial Licensing

Commercial rights — may a company use it?

Commercial use OK

Licence as writtenApache License 2.0 (code); CC BY 4.0 (model parameters)

README's 'Model Parameters License' section states parameters are made available under CC BY 4.0, which replaced the earlier CC BY-NC 4.0 terms; attribution required. Some mirrored MSA databases carry their own CC BY-SA 4.0 terms.

The licence read at the source allows use by a company. Attribution or copyleft conditions may still apply — read the note.

Commercial cost — is commercial use free of charge?

Free for commercial use

Free: code Apache-2.0, parameters CC BY 4.0 (changed from CC BY-NC in January 2022). Attribution is the only cost.

Price and rights are separate: this panel is about money, the panel above is about permission.

  • Commercial OK ≠ Free of charge. A tool can be licensed for company use and still need a paid licence for a dependency (BindCraft → PyRosetta).
  • Free download ≠ Commercially licensed. Weights you can download at no cost may still forbid commercial use (AlphaFold 3).
  • Unverified ≠ Commercially permitted. If no published statement settles it, treat it as unknown — not as a yes.
  • Every component counts. Each status considers the code licence, the model-weights terms, required dependencies and any terms of use.

Model Weights

Open weights. A separate weights licence is Not documented as its own field; where weights carry different terms from the code, that is stated in the licence explanation above.

Dependencies

Not documented as a separate field. Any dependency that affects commercial use (for example a paid PyRosetta licence) is named in the licence and cost explanations above.

Official References

From the makers of FoldScout

From AI Design to Wet-Lab Validation

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