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| 1 |
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---
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| 2 |
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license: cc-by-4.0
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tags:
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- biology
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- proteins
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- intrinsically-disordered-proteins
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- molecular-dynamics
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- CALVADOS
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- trajectories
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- BENDER
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- IDP
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pretty_name: BENDER — Biological ENsembles of Disordered proteins across kingdoms
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size_categories:
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- 10K<n<100K
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task_categories:
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- other
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language:
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- en
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---
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# BENDER — Biological ENsembles of Disordered proteins across kingdoms
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Raw CALVADOS coarse-grained molecular dynamics trajectories for
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**11,533 intrinsically disordered proteins** spanning 13 kingdoms of life.
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Each protein folder contains:
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- `<uniprot_id>.dcd` — CALVADOS Cα trajectory (200 ns+)
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- `top.pdb` — topology file
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---
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## Folder structure
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```
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Kingdom.zip/
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└── <uniprot_id>/
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├── <uniprot_id>.dcd
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└── top.pdb
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```
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---
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## Available zip files
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| File | Kingdom | Sequences |
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|---|---|---|
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| `Bacteria.zip` | Bacteria | 2,850 |
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| `Plants.zip` | Plants | 2,480 |
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| `Fungi.zip` | Fungi | 1,507 |
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| `Mammals.zip` | Mammals | 1,361 |
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| `Parasites_Protists.zip` | Parasites / Protists | 1,049 |
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| `Viruses.zip` | Viruses | 1,025 |
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| `Other_Vertebrates.zip` | Other vertebrates | 711 |
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| `Insects.zip` | Insects | 289 |
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| `Nematodes.zip` | Nematodes | 95 |
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| `Other_Invertebrates.zip` | Other invertebrates | 77 |
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| `Archaea.zip` | Archaea | 76 |
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| `Algae.zip` | Algae | 10 |
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---
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## Loading a trajectory
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```python
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from huggingface_hub import hf_hub_download
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import mdtraj as md
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import zipfile
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# Download zipped kingdom
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zip_path = hf_hub_download(
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repo_id="taseef/BENDER",
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filename="Bacteria.zip",
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repo_type="dataset"
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)
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# Extract specific protein
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with zipfile.ZipFile(zip_path, "r") as z:
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z.extract("N0AZA6/N0AZA6.dcd", path="./trajectories")
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z.extract("N0AZA6/top.pdb", path="./trajectories")
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# Load trajectory
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traj = md.load(
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"./trajectories/N0AZA6/N0AZA6.dcd",
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top="./trajectories/N0AZA6/top.pdb"
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)
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print(traj)
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```
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---
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## Simulation protocol
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| Parameter | Value |
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|---|---|
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| Force field | CALVADOS-2 (Cα coarse-grained, Tesei & Lindorff-Larsen 2023) |
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| Ensemble | NVT, 300 K |
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| Ionic strength | 0.15 M NaCl |
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| Minimum length | 200 ns |
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| Long sequences (>150 res) | Extended — length scaled to residues^1.5 |
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| Equilibration | First 50 % of each trajectory discarded |
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| Clustering | Global CD-HIT at 90 % sequence identity across all kingdoms |
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| Scope | Pure complete IDPs only — no IDR fragments, no domain context |
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| Convergence | 87.4 % of sequences exceed ν fit R² ≥ 0.99 |
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---
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## Prediction targets
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10 ensemble-level targets per sequence:
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**Geometric properties**
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| Target | Description |
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|---|---|
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| `Rg` | Radius of gyration |
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| `Re` | End-to-end distance |
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| `nu` | Flory scaling exponent |
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| `delta` | Asphericity |
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| `A0` | Flory prefactor |
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**Contact network properties**
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| Target | Description |
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|---|---|
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| `global_efficiency` | Global network efficiency |
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| `fragmentation_index` | Fragmentation index |
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| `avg_clustering` | Average clustering coefficient |
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| `transitivity` | Network transitivity |
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| `degree_assortativity` | Degree assortativity |
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---
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## Companion resources
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- **Feature dataset** (80+ computed features per protein):
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[`taseef/BENDER-features`](https://huggingface.co/datasets/taseef/BENDER-features)
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- **KESTREL model** (sequence → ensemble property predictor):
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[`taseef/KESTREL`](https://huggingface.co/taseef/KESTREL)
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---
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## Citation
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```bibtex
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@dataset{bender2026,
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title = {BENDER: Biological ENsembles of Disordered proteins across kingdoms},
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year = {2026},
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url = {https://huggingface.co/datasets/taseef/BENDER}
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}
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```
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---
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## License
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[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) — free to use for any purpose with attribution.
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*BENDER: making IDPs go supersonic.*
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