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awesome-protein-design-software
A collection of software for protein structure prediction and design
https://github.com/pansapiens/awesome-protein-design-software
Last synced: 5 days ago
JSON representation
-
Structure prediction
- paper - [blog](https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/) - [web app](https://alphafoldserver.com/)
- ColabFold - [Colab notebooks](https://github.com/sokrypton/ColabFold#making-protein-folding-accessible-to-all-via-google-colab) - [paper](https://doi.org/10.5281/zenodo.5123296)
- ParaFold - [paper](https://arxiv.org/abs/2111.06340)
- OpenFold - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/aqlaboratory/openfold/blob/main/notebooks/OpenFold.ipynb) - [paper](https://www.biorxiv.org/content/10.1101/2022.11.20.517210)
- OmegaFold - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/beta/omegafold.ipynb) - [paper](https://www.biorxiv.org/content/10.1101/2022.07.21.500999v1)
- FastFold - [paper](https://arxiv.org/abs/2203.00854)
- RoseTTAFold - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/RoseTTAFold.ipynb) - [paper](https://www.science.org/doi/10.1126/science.abj8754)
- ManyFold - [paper](https://doi.org/10.1093/bioinformatics/btac773)
-
Design
- InstructPLM - [paper](https://doi.org/10.1101/2024.04.17.589642)
- ESMFold-based constraint based design via "Protein programming language" - [paper](https://www.biorxiv.org/content/10.1101/2022.12.21.521526v1.full) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/facebookresearch/esm/blob/main/examples/protein-programming-language/tutorial.ipynb)
- ESM-2 language model design - [paper](https://www.biorxiv.org/content/10.1101/2022.12.21.521521v1.full) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/facebookresearch/esm/blob/main/examples/lm-design/free_generation.ipynb) | [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/facebookresearch/esm/blob/main/examples/lm-design/fixed_backbone.ipynb)
- ColabDesign
- ProteinMPNN - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabDesign/blob/v1.1.0/mpnn/examples/proteinmpnn_in_jax.ipynb) - [paper](https://www.biorxiv.org/content/10.1101/2022.06.03.494563v1)
- ECNet - [paper](https://www.nature.com/articles/s41467-021-25976-8)
- ProteinSolver - [paper](https://doi.org/10.1016/j.cels.2020.08.016) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/ostrokach/proteinsolver/blob/master/notebooks/20_protein_demo.ipynb)
- RFDiffusion - [paper](https://www.biorxiv.org/content/10.1101/2022.12.09.519842v1) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabDesign/blob/v1.1.1/rf/examples/diffusion.ipynb)
- LM-Design - [paper](https://arxiv.org/abs/2302.01649)
- ESM-IF1 (inverse folding) - [paper](https://doi.org/10.1101/2022.04.10.487779)
- BindCraft - [paper](https://doi.org/10.1101/2024.09.30.615802) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/martinpacesa/BindCraft/blob/main/notebooks/BindCraft.ipynb)
-
Sequence generation
- ProtGPT2 - [paper](https://www.nature.com/articles/s41467-022-32007-7)
- EvoDiff - [paper](https://www.biorxiv.org/content/10.1101/2023.09.11.556673v1)
- PoET - [paper](https://doi.org/10.48550/arXiv.2306.06156)
- EvoProtGrad - [paper](https://doi.org/10.1088/2632-2153/accacd)
-
Uncurated searches
-
Multimer structure prediction
- AF2Complex - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/FreshAirTonight/af2complex/blob/main/notebook/AF2Complex_notebook.ipynb) - [paper](https://www.nature.com/articles/s41467-022-29394-2)
- MoLPC - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/patrickbryant1/MoLPC/blob/master/MoLPC.ipynb) - [paper](https://www.nature.com/articles/s41467-022-33729-4)
- PeSTo - [paper](https://www.nature.com/articles/s41467-023-37701-8) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/LBM-EPFL/PeSTo/blob/main/apply_model.ipynb) - [web app](https://pesto.epfl.ch/)
- TCRdock - [paper](https://elifesciences.org/articles/82813)
- AlphaPulldown - [paper](https://doi.org/10.1093/bioinformatics/btac749) - [website](https://www.embl-hamburg.de/AlphaPulldown/)
- Uni-Fold Symmetry (UF-Symmetry) - [paper](https://doi.org/10.1101/2022.08.30.505833)
- Boltz-1
-
Peptide and ligand binding
- Solubility aware protein-binding peptide design with AfDesign - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/ohuelab/Solubility_AfDesign/blob/solubility/design.ipynb) - [paper](https://www.mdpi.com/2227-9059/10/7/1626)
- DiffBindFR
- AlphaFill - [web app](https://alphafill.eu/) - [paper](https://www.nature.com/articles/s41592-022-01685-y)
- PepMLM - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/drive/1u0i-LBog_lvQ5YRKs7QLKh_RtI-tV8qM?usp=sharing) - [paper](https://doi.org/10.48550/arXiv.2310.03842)
- PepMLM and EvoProtGrad
- AlphaFold encodes the principles to identify high affinity peptide binders (pre-print)
- ColabDesign/AfDesign peptide binder design - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabDesign/blob/main/af/examples/peptide_binder_design.ipynb)
-
Sequence similarity search and (structural) alignment
-
General protein language models
- ProtTrans - [paper](https://ieeexplore.ieee.org/document/9477085) - a transformer model of protein sequence (ProtT5)
- structure prediction using EMBER2 and trRosetta - lower resource but can't match Alphafold2
-
Other lists
- List of papers about Proteins Design using Deep Learning (Peldom)
- Papers on machine learning for proteins (yangkky)
- Awesome AI-based Protein Design (opendilab)
- Scientific Large Language Models (Sci-LLMs)
- awesome-protein-design (johnnytam100)
- awesome-protein-representation-learning
- folding_tools - folded prediction tools list
Programming Languages
Categories
Sub Categories
Keywords
protein-structure
10
alphafold2
6
deep-learning
6
bioinformatics
5
protein
5
pytorch
4
protein-sequences
4
protein-design
3
alphafold
3
protein-folding
3
multiple-sequence-alignment
2
protein-sequence
2
alphafold-multimer
2
structural-biology
2
generative-model
2
protein-engineering
2
protein-structure-prediction
2
protein-protein-interaction
2
python
1
research
1
protein-complexes
1
protein-protein-docking
1
geometric-deep-learning
1
protein-binding-site
1
protein-protein-interface
1
graph-neural-networks
1
jax
1
protein-representation-learning
1
parallelism
1
habana-gaudi
1
gpu
1
evoformer
1
cuda
1
representation-learning
1
parallelization
1
parafold
1
binder
1
structure-prediction
1
design
1
pyrosetta
1
structural-bioinformatics
1
protein-function
1
molecular-biology
1
bioinformatics-tool
1
text
1
survey
1
scientific-languages
1
science-research
1
sci-llm
1
multimodal
1