lfelipesv / folding_tools

A collection of *fold* tools

📖 Table of contents

• Predictors
• Tools
• Extensions
• Databases
• Webservers

💡 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 💀

⚡️ Brought to you by:

• @sacdallago
• @sokrypton

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Predictors

[in alphabetical order]

• MSA-based (uses Multiple Sequence Alignment as input)

  • AlphaFold2 (JAX)
    • Manuscript: https://www.nature.com/articles/s41586-021-03819-2
    • Code: https://github.com/deepmind/alphafold
  • ColabFold (JAX - faster AF2 compiling and MSA generations)
    • Manuscript: https://www.nature.com/articles/s41592-022-01488-1
    • Code: https://github.com/sokrypton/ColabFold
    • Code: https://github.com/YoshitakaMo/localcolabfold
  • FastFold (Pytorch)
    • Manuscript: https://arxiv.org/abs/2203.00854
    • Code: https://github.com/hpcaitech/FastFold
  • HelixFold (PaddlePaddle)
    • Manuscript: https://arxiv.org/abs/2207.05477
    • Code: https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/protein_folding/helixfold
  • MineSpore-Fold (mindspore)
    • Manuscript: https://arxiv.org/abs/2206.12240
    • Code: https://gitee.com/mindspore/mindscience/tree/master/MindSPONGE/applications/MEGAProtein
  • OpenFold (PyTorch)
    • Manuscript?
    • Code: https://github.com/aqlaboratory/openfold
  • RoseTTAFold (PyTorch)
    • Manuscript: https://www.science.org/doi/10.1126/science.abj8754
    • Code: https://github.com/RosettaCommons/RoseTTAFold
  • Uni-Fold (PyTorch/JAX)
    • Manuscript: https://doi.org/10.1101/2022.08.04.502811
    • Code (PyTorch): https://github.com/dptech-corp/Uni-Fold
    • Code (JAX): https://github.com/dptech-corp/Uni-Fold-jax

• pLM-based (uses Protein Language Model as input)

  • ESM-Fold (PyTorch)
    • Manuscript: https://doi.org/10.1101/2022.07.20.500902
    • Code: ? (potentially: https://github.com/facebookresearch/esm)
    • Other: [tweet] Alex's announcement,
  • EMBER3D (PyTorch):
    • Manuscript: ?
    • Code: https://github.com/kWeissenow/EMBER3D
  • HelixFold-single (PaddlePaddle)
    • Manuscript: https://arxiv.org/abs/2207.13921
    • Code: https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/protein_folding/helixfold-single
    • Resource: https://paddlehelix.baidu.com/app/drug/protein-single/forecast
  • OmegaFold (PyTorch)
    • Manuscript: https://doi.org/10.1101/2022.07.21.500999
    • Code: https://github.com/HeliXonProtein/OmegaFold
    • Other: [tweet] Martin comparing structures, [tweet] Sergey's positional encoding observation,

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Predictors specific to antibody sequences

• DeepAB (PyTorch)
  • Manuscript: https://www.cell.com/patterns/pdf/S2666-3899(21)00280-4.pdf
  • Code: https://github.com/RosettaCommons/DeepAb
• IgFold (PyTorch)
  • Manuscript: https://www.biorxiv.org/content/10.1101/2022.04.20.488972v1.full.pdf
  • Code: https://github.com/Graylab/IgFold

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Tools

• gget (AF2)
  • Manuscript: https://doi.org/10.1101/2022.05.17.492392
  • Code: https://github.com/pachterlab/gget#gget-alphafold-
• 💀 Lucidrains AF2 (AF2)
  • Code: https://github.com/lucidrains/alphafold2
• 💀 Lupoglaz OpenFold2 (AF2)
  • Code: https://github.com/lupoglaz/OpenFold2

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Extensions

• alphafold_finetune - finetune AlphaFold for Protein-Peptide prediction
  • Manuscript: https://www.biorxiv.org/content/10.1101/2022.07.12.499365v1
  • Code: https://github.com/phbradley/alphafold_finetune
  • Other: [tweet] Amir's announcement
• AlphaPulldown - protein-protein interaction screens using AlphaFold-Multimer
  • Manuscript: https://www.biorxiv.org/content/10.1101/2022.08.05.502961v1
  • Code: https://www.embl-hamburg.de/AlphaPulldown/
• ColabDesign - Backprop through AlphaFold for protein design
  • Code: https://github.com/sokrypton/ColabDesign
• AF2Rank - Rank Decoy Structures/Sequences using AlphaFold
  • Manuscript: https://www.biorxiv.org/content/10.1101/2022.03.11.484043v3
  • Code: https://github.com/jproney/AF2Rank
  • Resource: Colab Notebook

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Databases of predictions

• AlphaFold Database (UniRef90 | AF2)
  • Manuscript: https://doi.org/10.1093/nar/gkab1061
  • Resource: https://alphafold.ebi.ac.uk
• Eukaryotic interactormes (Protein-Protein interactions | RF/AF2)
  • Manuscript: https://www.science.org/doi/10.1126/science.abm4805
  • Resource: https://www.ebi.ac.uk/pdbe/news/predicted-complexes-modelarchive-now-pdbe-kb-pages
• Structures of human-transcriptome isoforms (ColabFold/AF2)
  • Manuscript: https://doi.org/10.1101/2022.06.08.495354
  • Resource: https://www.isoform.io
• AlphaFill - enriching the AlphaFold models with ligands and co-factors (AF2)
  • Manuscript: https://www.biorxiv.org/content/10.1101/2021.11.26.470110v1
  • Resource: https://alphafill.eu/

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Databases of predictions specific to antibody sequences

• IgFold Database (OAS | IgFold)
  • Manuscript: https://www.biorxiv.org/content/10.1101/2022.04.20.488972v1.full.pdf
  • Resource: https://data.graylab.jhu.edu/igfold_oas_paired95.tar.gz

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Webservers

• Lambda PredictProtein (ColabFold|limit:500AA)
  • Manuscript: https://doi.org/10.1101/2022.08.04.502750
  • Resource: http://embed.predictprotein.org/
• 💀 Moonbear
  • Resource: https://www.getmoonbear.com/
  • Other: [tweet] Stephanie's announcement