AlphaFold 2
Original AlphaFold; monomer and multimer structure prediction from sequence.
Google DeepMind
What it does
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.
Commercial use
Commercial use OKLicence 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.
Is commercial use free of charge?
Free for commercial useFree: 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.
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.
Facts
- Maker
- Google DeepMind
- Cost for commercial use
- Free for commercial use
- Category
- Structure and complex prediction
- Compute
- Heavy GPU
- Open weights
- Yes
- Licence
- Apache License 2.0 (code); CC BY 4.0 (model parameters)
- Official site / repo
- github.com/google-deepmind/alphafold
- Paper
- nature.com
- Last verified
Get told when a licence changes
Licences on these tools do change. One short email when a status flips or a tool is added. No other use of your address.