name: alphafold2
description: >
Predict protein structure for monomers and multimers with AlphaFold2 via the
ColabFold runner (Mirdita et al. 2022, github.com/sokrypton/ColabFold;
AlphaFold2 Jumper et al. 2021). Reach for this skill to fold a sequence or
complex with the AF2/AF2-Multimer evoformer, to validate designed sequences
by self-consistency pLDDT, ipTM, and RMSD, or to run a quick MSA-backed
prediction using the public MMseqs2 server.
license: Apache-2.0
category: biomodels
requirements: [gpu]
metadata:
display-name: AlphaFold2
README #model-parameters-license: "AlphaFold parameters … CC BY 4.0".
SKILL.md body: "the public MMseqs2 server" (api.colabfold.com — user's
sequence is POSTed there for MSA). verified 2026-06-30
third_party:
- kind: weights
name: AlphaFold2
provider: Google DeepMind
license: CC-BY-4.0
terms_url: https://github.com/google-deepmind/alphafold#model-parameters-license
# api.colabfold.com has no published ToS or privacy policy. The GitHub
# wiki is the closest data-use reference (info_url, not terms_url).
# Hostname in so the user sees exactly where their sequence goes.
- kind: service
name: ColabFold MSA server (api.colabfold.com)
provider: Steinegger Lab
info_url: