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LocalFold

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pLDDT

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pTM

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ipTM

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LocalFold

AlphaFold 3 model parameters

These are Google DeepMind's parameters. They are not available for commercial use and carry a prohibited-use policy.

OpenBind-0 runs the same architecture under Apache 2.0. It is a different model, and so is every other choice below.

AlphaFold 3 weights terms · prohibited use policy · about OpenBind-0

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Credits

LocalFold began as a fork of AlphaFold2 WebGPU by Martin Steinegger. The viewer is py2Dmol, and the alignment search is the ColabFold MMseqs2 server (Milot Mirdita, Martin Steinegger).

The models beyond AlphaFold 2 are ported from and checked against sokrypton/alphafold3, with work by Marielle Russo (@maraxen), ChoongHwanLee (@chlee19990109-cloud), juliabuhmann (@juliabuhmann) and Milot Mirdita (@milot-mirdita).

Methods borrowed

Blitz (Vinay Saji Mathew, Soundar Kumara, Gretta Kellogg, William K. M. Lai): the diffusion sampler's exponential update and geometric noise schedule, used by every AlphaFold 3-family model here.
Synthyra: the ESMFold2 confidence head (pLDDT, PAE, pTM), trained on ESMFold2's frozen trunk - FastPLMs, ESMFold2-600.
af3x (Konstantin Gilep, Agnieszka Obarska-Kosinska, Jan Kosinski): crosslinks modelled explicitly, the crosslinker as a ligand bonded to the two residues it joined, and its crosslinker definitions - preprint.

Models

AlphaFold 2 and AlphaFold 3 - Google DeepMind
OpenBind-0 (OpenFold3 v0.5.0) - OpenBind
OpenDDE - Aureka Research
Boltz-2 - the Boltz team
Protenix-2 - ByteDance
Mol-1 - Molence Bio
IntelliFold-2 - IntelliGen AI
RoseTTAFold3 - Baker lab / RosettaCommons
ESMFold2 and ESM-C - Biohub
BioEmu2 - Microsoft Research