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ProteinMPNN-ddG API

Estimate changes in protein stability upon point mutation

A modification of ProteinMPNN to use full sequence context. It introduces a decoding scheme to improve computational efficiency and enable saturation mutagenesis studies at scale.

Example presets

Send {"preset": "readme/AF-A0A7L5GP87"} to load an example and its bundled inputs. Add other request fields to override its settings. The schema includes all presets under tool.presets.

presetDescription
readme/AF-A0A7L5GP87Official README example. The AlphaFold PDB and documented chain, seed, and v_48_020 model settings are included. Source ↗

These local CLI options are not applicable to Bio Web and are omitted from its inputs:

  • outpath: The service creates a separate output path for each job and archives the prediction CSV.
Request body

Fields

The same names the web form posts. See the field type table for what each kind means over HTTP.

Name Type Required Default Description
job_name string text no proteinmpnn-ddg-demo Job name A label for this run and its results. up to 80 characters.
pdb_path string file yes Protein structure PDB structure whose point mutations will be scored. In this form: Upload PDB text or choose the preset containing the official AlphaFold example structure. file types .pdb,.ent.
chains string text no A Chains to load Comma-separated PDB chains used as structural and sequence context, e.g. A,B,C. By default, substitutions are predicted for the first chain. up to 100 characters.
chain_to_predict string text no Chain to predict Optional chain whose substitutions are predicted. It is moved to the front of the loaded chain list; blank uses the first chain above. up to 1 characters.
model_name string select no v_48_020 ProteinMPNN model 48-neighbor ProteinMPNN checkpoint trained with the indicated backbone noise. One of: v_48_002, v_48_010, v_48_020, v_48_030.
seed number number no 42 Random seed Seed used to split the per-repeat JAX random keys. minimum 0, maximum 2147483647, step 1.
nrepeats number number no 1 Model repeats Run with this many keys split from the input seed and average the resulting predictions. minimum 1, maximum 100, step 1.
without_ddG_correction boolean checkbox no false Disable the ddG correction Write raw logit differences without the paper's single-residue ddG correction. The correction is defined only for v_48_020, so this must be enabled with every other model.
Example

A request that runs

These are the defaults, exactly as the web form would post them.

curl -X POST https://athanortools.com/api/proteinmpnn_ddg/ \
  -H 'Content-Type: application/json' \
  -d '{
  "job_name": "proteinmpnn-ddg-demo",
  "pdb_path": "",
  "chains": "A",
  "chain_to_predict": "",
  "model_name": "v_48_020",
  "seed": 42,
  "nrepeats": 1,
  "without_ddG_correction": false
}'

The reply is 202 with a queued job; poll its status_url until status is succeeded or failed. See the quick start for the whole exchange.

Responses

What comes back

statusMeaning
queued Accepted, waiting for the jobs ahead of it. `position` counts how many those are.
running The tool is executing now.
succeeded Finished; `result` holds the tool's output and `license` the terms it came under.
failed Finished; `error` holds a code and a message.
cancelled Abandoned at the submitter's request; there is no result. A job cancelled before its turn never ran at all.

Errors

codeMeaning
invalid_input The client supplied invalid or incomplete input.
tool_unavailable The requested third-party dependency is not available on this host.
execution_failed A configured third-party tool exited unsuccessfully.
internal_error An adapter failed in a way it does not describe. The detail is in the server log, not the response.
not_found No job has that id. Finished jobs are dropped eventually.