bio_tools 0.1.3

Install, run, and inspect computational biology and chemistry tools, e.g. AlphaFold, Boltz, RFdiffusion3, and ProteinMPNN
Documentation
{
  "fields": [
    {
      "name": "job_name",
      "label": "Job name",
      "kind": "text",
      "default": "proteinmpnn-ddg-demo",
      "required": false,
      "help": "A label for this run and its results.",
      "options": [],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": 80,
      "accept": "",
      "task": "",
      "group": "Inputs"
    },
    {
      "name": "pdb_path",
      "label": "Protein structure",
      "kind": "file",
      "default": "",
      "required": true,
      "help": "PDB structure whose point mutations will be scored.",
      "options": [],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": null,
      "accept": ".pdb,.ent",
      "task": "",
      "group": "Inputs",
      "help_note": "Upload PDB text or choose the preset containing the official AlphaFold example structure."
    },
    {
      "name": "chains",
      "label": "Chains to load",
      "kind": "text",
      "default": "A",
      "required": false,
      "help": "Comma-separated PDB chains used as structural and sequence context, e.g. A,B,C. By default, substitutions are predicted for the first chain.",
      "options": [],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": 100,
      "accept": "",
      "task": "",
      "group": "Inputs"
    },
    {
      "name": "chain_to_predict",
      "label": "Chain to predict",
      "kind": "text",
      "default": "",
      "required": false,
      "help": "Optional chain whose substitutions are predicted. It is moved to the front of the loaded chain list; blank uses the first chain above.",
      "options": [],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": 1,
      "accept": "",
      "task": "",
      "group": "Inputs"
    },
    {
      "name": "model_name",
      "label": "ProteinMPNN model",
      "kind": "select",
      "default": "v_48_020",
      "required": false,
      "help": "48-neighbor ProteinMPNN checkpoint trained with the indicated backbone noise.",
      "options": [
        {
          "value": "v_48_002",
          "label": "v_48_002 (0.02 Å training noise)"
        },
        {
          "value": "v_48_010",
          "label": "v_48_010 (0.10 Å training noise)"
        },
        {
          "value": "v_48_020",
          "label": "v_48_020 (0.20 Å training noise)"
        },
        {
          "value": "v_48_030",
          "label": "v_48_030 (0.30 Å training noise)"
        }
      ],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": null,
      "accept": "",
      "task": "",
      "group": "Model and averaging"
    },
    {
      "name": "seed",
      "label": "Random seed",
      "kind": "number",
      "default": 42,
      "required": false,
      "help": "Seed used to split the per-repeat JAX random keys.",
      "options": [],
      "rows": null,
      "minimum": 0,
      "maximum": 2147483647,
      "step": 1,
      "maxlength": null,
      "accept": "",
      "task": "",
      "group": "Model and averaging"
    },
    {
      "name": "nrepeats",
      "label": "Model repeats",
      "kind": "number",
      "default": 1,
      "required": false,
      "help": "Run with this many keys split from the input seed and average the resulting predictions.",
      "options": [],
      "rows": null,
      "minimum": 1,
      "maximum": 100,
      "step": 1,
      "maxlength": null,
      "accept": "",
      "task": "",
      "group": "Model and averaging"
    },
    {
      "name": "without_ddG_correction",
      "label": "Disable the ddG correction",
      "kind": "checkbox",
      "default": false,
      "required": false,
      "help": "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.",
      "options": [],
      "rows": null,
      "minimum": null,
      "maximum": null,
      "step": null,
      "maxlength": null,
      "accept": "",
      "task": "",
      "group": "Model and averaging"
    }
  ],
  "tasks": [],
  "field_groups": [
    {
      "label": "Inputs",
      "docs_url": "https://github.com/PeptoneLtd/proteinmpnn_ddg/blob/98302b5e7d6b2962aa03336cf950196c33f2c3a1/README.md#usage"
    },
    {
      "label": "Model and averaging",
      "docs_url": "https://github.com/PeptoneLtd/proteinmpnn_ddg/blob/98302b5e7d6b2962aa03336cf950196c33f2c3a1/predict.py"
    }
  ],
  "_comment": "Field names and defaults follow predict.py. The service manages outpath. ProteinMPNN-ddG always scores every standard point mutation for one chain; top-k filtering is not part of its public CLI."
}