| --- |
| license: apache-2.0 |
| library_name: nesso |
| tags: |
| - structure-based-drug-design |
| - binding-affinity |
| - protein-ligand |
| - drug-discovery |
| pipeline_tag: other |
| --- |
| |
| # Model Card for Nesso-1 |
|
|
| Nesso-1 is a fast, structure-based protein–ligand binding-affinity model. Given a |
| protein sequence and a ligand (SMILES / CCD code / SDF), it predicts a binding |
| affinity scalar along with a binder/non-binder score. |
|
|
| - **Developed by:** [Valence Labs](https://valencelabs.com) ([Recursion](https://recursion.com)) |
| - **Input modality:** Protein Amino-Acid sequence + Ligand (SMILES, CCD code, or SDF) |
| - **License:** [Apache License 2.0](https://huggingface.co/recursionpharma/nesso/blob/main/LICENSE) |
| - **Paper:** [Technical Report](https://www.valencelabs.com/wp-content/uploads/2026/07/nesso1.pdf) |
|
|
| For full method details and evaluations, see the [Technical Report](https://www.valencelabs.com/wp-content/uploads/2026/07/nesso1.pdf) and [Github](https://github.com/recursionpharma/nesso/) |
|
|
| ## Documentation |
|
|
| Install the package, run predictions, and explore examples from the GitHub repository: |
|
|
| - [README](https://github.com/recursionpharma/nesso) — installation, quick start, and development setup |
| - [docs/prediction.md](https://github.com/recursionpharma/nesso/blob/main/docs/prediction.md) — CLI options, input YAML schema, and output format |
| - [tutorial/](https://github.com/recursionpharma/nesso/tree/main/tutorial) — runnable YAML examples and feature extraction |
| - [Issues](https://github.com/recursionpharma/nesso/issues) - For questions related to weights, model code, please raise issues here. |
|
|
