Package · PyPI

protenix

PyPI · v2.0.0 · Apache 2.0 License

A trainable PyTorch reproduction of AlphaFold 3.

Tentative categories were assigned with moderate confidence (0.5 to 0.75): they are shown, but they do not count toward a category’s momentum. How categories work

Install

pip install protenix

Adoption

Adoption
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Popularity
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Dependents
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Maintenance
0.62
DerivedRelease cadence and recency, 0 to 1
Releases per year
35
50 versions over its life

Growth by period

PyPI publishes no adoption figure, so there is no growth to derive. Nothing is estimated in its place.

7 days
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30 days
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90 days
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1 year
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Adoption history

Adoption history

PyPI publishes no adoption count, so there is no history to chart. That is a fact about the registry, not a gap in ours: the package’s releases and maintenance are measured instead.

Facts from the registry

Latest version
v2.0.0
50 versions
First published
NOV 8, 2024
Last release
APR 7, 2026
7mo ago
Licence
Apache 2.0 License

Repository

In the Crest catalog

bytedance/Protenix

Toward High-Accuracy Open-Source Biomolecular Structure Prediction.

Stars
2.1K
Forks
316
Language
Python
Last push
34d ago
Last release
7mo ago

Linked by the package’s own registry metadata.GitHub (opens in a new tab)

Dependencies latest version · v2.0.0

Runtime 32

  • PyYAML==6.0.2
  • biopython==1.85
  • biotite==1.4.0
  • cuequivariance-ops-torch-cu12==0.8.0
  • cuequivariance-torch==0.8.0
  • deepspeed==0.17.5
  • fair-esm==2.0.0
  • gemmi==0.6.7
  • icecream==2.1.7
  • ipdb==0.13.13
  • ipywidgets==8.1.7
  • matplotlib==3.10.5
  • ml_collections==1.1.0
  • modelcif==1.4
  • networkx>=3.4.2
  • numpy==2.4.1
  • optree==0.17.0
  • pandas==2.3.1
  • pdbeccdutils==1.0.0
  • protobuf==6.31.1
  • py3Dmol==2.5.2
  • pydantic>=2.0.0
  • rdkit==2025.9.3
  • scikit-learn==1.7.1
  • scikit-learn-extra==0.3.0
  • scipy>=1.9.0
  • torch==2.7.1
  • torchaudio==2.7.1
  • torchvision==0.22.1
  • tqdm==4.67.1
  • triton==3.3.1
  • wandb==0.21.1

Related news

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