| --- |
| license: apache-2.0 |
| tags: |
| - biology |
| - protein-structure-prediction |
| - biomolecular-structure-prediction |
| --- |
| |
| # K-Fold |
|
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| K-Fold v1.0.0b1 is a beta release under active development. |
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| K-Fold predicts biomolecular complex structures and binding-induced conformational changes. |
| Through an apo-to-holo diffusion bridge, K-Fold aims to capture conformational changes in systems such as G protein-coupled receptors (GPCRs). |
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| K-Fold supports proteins, DNA, RNA, small molecules, and chemical modifications without multiple sequence alignments (MSAs). |
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| By default, K-Fold prepares protein component structures with [AtlasFold](https://github.com/SeonghwanSeo/atlasfold). |
| You can also provide apo structures from experiments or other prediction tools. |
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| This repository provides K-Fold model weights. Source code, examples, and documentation are available on [GitHub](https://github.com/SeonghwanSeo/kfold). |
|
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| ## Installation and inference |
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| K-Fold requires Python 3.11 or later. |
|
|
| ```bash |
| pip install kfold |
| kfold --input query.yaml --out-dir predictions/ --seeds 42 |
| ``` |
|
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| Use `--kernel {triton,cuequiv,torch}` to select the backend for K-Fold complex prediction. |
| Automatic selection prefers Triton, then cuEquivariance, then PyTorch, depending on availability. |
| Install the `cuequiv` extra (`pip install 'kfold[cuequiv]'`) to enable cuEquivariance kernels. |
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| Model weights and the chemical component dictionary (CCD) are downloaded automatically on first use. |
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| See the [inference guide](https://github.com/SeonghwanSeo/kfold/blob/main/docs/inference.md) for input formats and options, or the [Python API guide](https://github.com/SeonghwanSeo/kfold/blob/main/docs/python_api.md) for use in Python. |
|
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| ## Beta release |
|
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| K-Fold v1.0.0b1 is a beta release. |
| Interfaces and prediction results may change before the stable release. |
|
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| ## License |
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| Copyright © 2026 Korea Advanced Institute of Science and Technology (KAIST). |
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| K-Fold is licensed under the [Apache License 2.0](https://github.com/SeonghwanSeo/kfold/blob/main/LICENSE). |
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