📖 Table of contents
💡 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:
[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
- AlphaFold2
-
pLM-based (using embeddings from protein Language Models (pLMs) as input)
- ESM-Fold
- Features: monomer
- Other: [tweet] Alex's announcement
- 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
- ESM-Fold
- 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
- 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
- OpenFold
- MSAs for 132K PDBs + 270K UniClust30 predictions for distilation
- 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/
- 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/
- 💀 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