| <h1 align="center">Boltz-1: | |
| Democratizing Biomolecular Interaction Modeling | |
| </h1> | |
| Boltz-1 is an open-source model which predicts the 3D structure of proteins, rna, dna and small molecules; it handles modified residues, covalent ligands and glycans, as well as condition the generation on pocket residues. | |
| For more information about the model, see our [technical report](https://gcorso.github.io/assets/boltz1.pdf). | |
| ## Installation | |
| Install boltz with PyPI (recommended): | |
| ``` | |
| pip install boltz | |
| ``` | |
| or directly from GitHub for daily updates: | |
| ``` | |
| git clone https://github.com/jwohlwend/boltz.git | |
| cd boltz; pip install -e . | |
| ``` | |
| > Note: we recommend installing boltz in a fresh python environment | |
| ## Inference | |
| You can run inference using Boltz-1 with: | |
| ``` | |
| boltz predict input_path | |
| ``` | |
| Boltz currently accepts three input formats: | |
| 1. Fasta file, for most use cases | |
| 2. A comprehensive YAML schema, for more complex use cases | |
| 3. A directory containing files of the above formats, for batched processing | |
| To see all available options: `boltz predict --help` and for more informaton on these input formats, see our [prediction instructions](docs/prediction.md). | |
| ## Training | |
| If you're interested in retraining the model, see our [training instructions](docs/training.md). | |
| ## Contributing | |
| We welcome external contributions and are eager to engage with the community. Connect with us on our [Slack channel](https://boltz-community.slack.com/archives/C0818M6DWH2) to discuss advancements, share insights, and foster collaboration around Boltz-1. | |
| ## Coming very soon | |
| - [ ] Pocket conditioning support | |
| - [ ] More examples | |
| - [ ] Full data processing pipeline | |
| - [ ] Colab notebook for inference | |
| - [ ] Confidence model checkpoint | |
| - [ ] Support for custom paired MSA | |
| - [ ] Kernel integration | |
| ## License | |
| Our model and code are released under MIT License, and can be freely used for both academic and commercial purposes. |