Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
awesome-protein-design-software
A collection of software for protein structure prediction and design
https://github.com/pansapiens/awesome-protein-design-software
- paper - [blog](https://blog.google/technology/ai/google-deepmind-isomorphic-alphafold-3-ai-model/) - [web app](https://alphafoldserver.com/)
- Alphafold2 - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/deepmind/alphafold/blob/main/notebooks/AlphaFold.ipynb) - [paper](https://doi.org/10.1038/s41586-021-03819-2)
- 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)
- Evolutionary Scale Modeling (ESM-2, ESMFold) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/ESMFold.ipynb) - [paper](https://www.science.org/doi/abs/10.1126/science.ade2574)
- 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)
- UniFold - [paper](https://doi.org/10.1101/2022.08.04.502811)
- 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)
- Alphafold2-Multimer - [paper](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1)
- Evolutionary Scale Modeling (ESM-2, ESMFold) - [<img src="https://colab.research.google.com/assets/colab-badge.svg">](https://colab.research.google.com/github/sokrypton/ColabFold/blob/main/ESMFold.ipynb) - [paper](https://www.science.org/doi/abs/10.1126/science.ade2574)
- Uni-Fold Symmetry (UF-Symmetry) - [paper](https://doi.org/10.1101/2022.08.30.505833)
- 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/)
- 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)
- ESM-IF1 (inverse folding) - [paper](https://doi.org/10.1101/2022.04.10.487779)
- 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)
- 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)
- 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)
- 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)
- 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)
- DeepBLAST - [paper](https://doi.org/10.1101/2020.11.03.365932)
- TM-vec
- 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
- 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
- Github repos tagged protein-design
Programming Languages
Keywords
protein-structure
9
alphafold2
5
deep-learning
5
pytorch
4
bioinformatics
4
protein
4
alphafold
3
protein-folding
3
protein-design
3
protein-sequences
3
protein-sequence
2
structural-biology
2
protein-structure-prediction
2
protein-protein-interaction
2
alphafold-multimer
2
sci-llm
1
graph-neural-networks
1
protein-protein-interface
1
protein-binding-site
1
geometric-deep-learning
1
protein-protein-docking
1
protein-complexes
1
science-research
1
scientific-languages
1
text
1
parallelism
1
habana-gaudi
1
gpu
1
evoformer
1
cuda
1
protein-embedding
1
protein-modeling
1
parallelization
1
parafold
1
protein-representation-learning
1
representation-learning
1
llms
1
genome
1
cell
1
structural-alignments
1
sequence-alignment
1
neural-networks
1
language-modeling
1
research
1
python
1
jax
1
structural-bioinformatics
1
protein-function
1
protein-engineering
1
molecular-biology
1