Dyna-1
Predict micro-millisecond protein dynamics from sequence and/or structure
Dyna-1 predicts the probability that each residue experiences micro-millisecond motions. You can provide either a protein sequence, a structure (PDB ID or file), or both for the best performance.
Instructions
- Authorize access to ESM-3 by logging in to HuggingFace (required for ESM-3)
- Enter a protein sequence using standard amino acid letters (optional)
- Provide a PDB ID (e.g., "1ubq") or upload a PDB file (optional)
- Specify the chain ID if using a structure (default: A)
- Choose whether to use the sequence from the PDB structure
You can toggle between using the ESM-3 and ESM-2 versions of the Dyna-1 model. To run with ESM-3, make sure you already
have access to the EvolutionaryScale/esm3-sm-open-v1
weights here.
Note: The model will automatically set up the required environment on first run.
Use of this HF Space is subject to a Non-Commercial Use License.
Label | Protein Sequence | PDB ID | Chain ID | Use sequence from PDB |
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Visualization
We visualize probabilities of exchange on protein structures using PyMol. To re-create the putty visualization on your protein, import the pdb file into PyMol and copy-paste the following commands into the PyMol command line:
cartoon putty; set cartoon_putty_transform, 6; set cartoon_putty_radius, 0.25; set cartoon_putty_range, 0.1; set cartoon_putty_scale_max, 10
Annotated:
cartoon putty
set cartoon_putty_transform, 6 #scaled linear transformation
set cartoon_putty_radius, 0.25 # min radius for p=0
set cartoon_putty_range, 0.1 # min_radius / max_radius, sets max_radius=2.5
set cartoon_putty_scale_max, 10 #max_radius / min_radius
This HuggingFace Space was created by Gina El Nesr @ginaelnesr.
If you are using our code, datasets, or model, please use the following citation:
@article {Dyna-1,
author = {Wayment-Steele, Hannah K. and El Nesr, Gina and Hettiarachchi, Ramith and Kariyawasam, Hasindu and Ovchinnikov, Sergey and Kern, Dorothee},
title = {Learning millisecond protein dynamics from what is missing in NMR spectra},
year = {2025},
doi = {10.1101/2025.03.19.642801},
journal = {bioRxiv}
}