fetch_alphafold
Fetch protein structures predicted by AlphaFold from UniProt accession, using confidence-based coloring to identify reliable versus disordered regions.
Instructions
Fetches a predicted structure from AlphaFold DB by UniProt accession.
These are predictions, not experimental structures, so the model is coloured by pLDDT confidence rather than the usual style — dark blue is reliable, orange is essentially unmodelled. Read the orange and yellow regions as "probably disordered or wrong", not as flexible loops.
Note that pLDDT rides in the B-factor column, so bfactor_view and
putty_view will mis-colour these models (they assume low = rigid,
which is backwards for confidence). Use plddt_view instead.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| replace | No | Clear the session first, so this is the only structure loaded. Pass False to add to what is already loaded — which is how you get two structures into one session for superposition_view. | |
| fragment | No | Fragment number for long proteins split across models (F1, F2, …). Most entries only have F1. | |
| obj_name | No | Optional custom name for the object in PyMOL. | |
| uniprot_id | Yes | UniProt accession (e.g. "P69905" for human haemoglobin alpha). An "AF-" prefix is accepted and stripped. | |
| model_version | No | Pin a specific AlphaFold model version. Leave unset (the default) to use whichever version the database currently serves — old versions are retired and stop resolving. |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |