📖 Table of contents

• Predictors
• Tools and Extensions
• Databases and Datasets
• Webservers
• Discontinued

💡 Notes

• The following lists are curated by humans, as such may be incomplete
• We only include software targeting the folding problem combining learnings from AlphaFold 2 and protein language models. You may find other ML on protein tools at Kevin's incredible ML for proteins list.
• We do not wish to advertize one tool over any other, but simply list the tools we are aware of in either random or alphabetical order
• Any suggestions for improvements and additions are welcome as issues or pull requests
• Projects we identify as discontinued are marked with 💀 and in a section at the end

⚡️ Brought to you by:

• @sacdallago
• @sokrypton

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Predictors

[in alphabetical order]

• MSA-based (uses Multiple Sequence Alignments (MSAs) as input)

  • AlphaFold2
    • The original AlphaFold 2 method
    • Features: monomer, multimer
    • Other: Colab Notebook
  • ColabFold
    • Faster AF2 compiling and MSA generations
    • Features: monomer, multimer
    • Other: localcolabfold
  • FastFold
    • Runtime improvements to OpenFold (see below)
    • Features: monomer
  • HelixFold
    • Reimplementation of AF2 in PaddlePaddle
    • Features: monomer
  • MEGA-Fold
    • Reimplementation of AF2 in MindSpore; provides training code, training dataset and new model params.
    • Features: monomer
  • OpenFold
    • Reimplementation of AF2 in PyTorch; provides training code, training dataset and new model params.
    • Features: monomer
    • Other: Colab Notebook
  • RoseTTAFold
    • Reproduced AF2 in PyTorch before details of AF2 were available; new model parameters.
    • Features: monomer
    • Other: Unofficial Colab Notebook
  • Uni-Fold
    • Reimplementation of AF2 in PyTorch; provides training code and new (monomer/multimer) model parameters.
    • Features: monomer, multimer
    • Resources: Colab Notebook
  • Uni-Fold-jax
    • Implementation of AF2's training code.

• pLM-based (using embeddings from protein Language Models (pLMs) as input)

  • ESM-Fold
    • Features: monomer
    • Other: Unofficial Colab notebook,API
  • EMBER3D
    • Features: monomer
  • HelixFold-single
    • Features: monomer
    • Resource: https://paddlehelix.baidu.com/app/drug/protein-single/forecast
  • IgFold
    • pLM focused on antibody sequences
    • Features: monomer
    • Other: Colab Notebook
  • OmegaFold
    • Features: monomer
    • Other: Unofficial Colab Notebook, [tweet] Martin comparing structures, [tweet] Sergey's positional encoding observation
  • RGN2 Github
    • Uses AlphaFold's structure module (AF2Rank's template protocol) for final structure refinement.

• Other

  • EquiFold
    • Diffusion model to predict protein structures (specifically antibodies)
    • Features: monomer

• Conformational change and dynamics (TODO)

  • AFcluster
  • AFsample
  • etc

• AlphaFold3 and friends

  • AlphaFold3
    • Source Code (~Nov 2024)
    • Paper
  • HelixFold3
    • Source Code, Server, Paper
  • Chai-1
    • Has support for using pLMs (instead of MSA), and defining of constraints (crosslinks, epitope, etc)
    • Limited Source Code, Server, Paper
  • Ligo-Biosciences (monomers only)
    • Source Code
  • Lucidrain et al. (code only)
    • Source Code
  • OpenFold3
    • Source Code (~Oct/Nov 2024)

Tools and Extensions

• gget (AF2)
• alphafold_finetune
  • finetune AlphaFold for Protein-Peptide prediction
  • Other: [tweet] Amir's announcement
• AlphaPulldown
  • protein-protein interaction screens using AlphaFold-Multimer
• ColabDesign
  • Backprop through AlphaFold for protein design
• AF2Rank
  • Rank Decoy Structures/Sequences using AlphaFold
  • Resource: Colab Notebook
• protein_structure_module_of_AF2
  • IPA implementation in pytorch

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Databases of predictions

• AlphaFold Database
  • All sequences in UniRef90 - viral sequences; Based on AlphaFold 2
  • Resource: https://alphafold.ebi.ac.uk
• Eukaryotic interactormes
  • Protein-Protein interactions; Based on RoseTTAFold and AlphaFold 2
  • Resource: https://www.ebi.ac.uk/pdbe/news/predicted-complexes-modelarchive-now-pdbe-kb-pages
• Structures of human-transcriptome isoforms
  • Based on ColabFold (AlphaFold 2)
  • Resource: https://www.isoform.io
• AlphaFill
  • Enriching the AlphaFold models with ligands and co-factors (AlphaFold 2)
  • Resource: https://alphafill.eu/
• IgFold Database
  • Predictions specific to antibody sequences; based on OAS dataset and IgFold
  • Resource: https://data.graylab.jhu.edu/igfold_oas_paired95.tar.gz

Datasets for training

• OpenProteinSet
  • 16 million MSAs for PDB, and AF2 structure predictions
  • Manuscript: https://arxiv.org/abs/2308.05326
  • Resource: https://registry.opendata.aws/openfold/
• MindSpore
  • MSAs for 570K PDBs + 745K Distillation
  • Manuscript: https://arxiv.org/abs/2206.12240
  • Resource: http://ftp.cbi.pku.edu.cn/psp/

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Webservers

• Lambda PredictProtein
  • Based on ColabFold; Limited to sequences up to 500AAs
  • Resource: http://embed.predictprotein.org/
• Robetta
  • Based on RoseTTAFold
  • Resource: https://robetta.bakerlab.org/

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Discontinued

• 💀 Moonbear
  • Resource: https://www.getmoonbear.com/
  • Other: [tweet] Stephanie's announcement
• 💀 Lucidrains' AlphaFold2
  • AF2 reproduction attempt
  • Features: monomer
• 💀 Lupoglaz's OpenFold2
  • AF2 reproduction attempt
  • Features: monomer