Boltz Workflow: Protein-Ligand 101

{
  "io": {
    "inputs": [
      {
        "ui": {
          "rows": 6,
          "control": "textarea"
        },
        "name": "protein_sequence",
        "label": "Target Protein Sequence",
        "format": "sequence",
        "maps_to": "protein_ligand_setup.protein_sequence",
        "required": false,
        "value_type": "string",
        "description": "Amino-acid sequence for the curated teaching target; maps directly to the Boltz-2 protein input."
      },
      {
        "ui": {
          "rows": 3,
          "control": "textarea"
        },
        "name": "ligand_smiles",
        "label": "Ligand SMILES",
        "format": "smiles",
        "maps_to": "protein_ligand_setup.ligand_smiles",
        "required": false,
        "value_type": "string",
        "description": "SMILES string for the curated teaching ligand; maps directly to the Boltz-2 ligand input."
      },
      {
        "ui": {
          "control": "file"
        },
        "file": {
          "accept": [
            ".a3m",
            ".fasta",
            ".fa"
          ]
        },
        "name": "msa_path",
        "label": "Precomputed MSA Path",
        "format": "a3m",
        "maps_to": "protein_ligand_setup.msa_path",
        "required": false,
        "value_type": "file",
        "description": "Optional path to a precomputed MSA file; leave unset when the configured Boltz MSA server is used."
      },
      {
        "name": "use_msa_server",
        "label": "Use MSA Server",
        "default": true,
        "maps_to": "protein_ligand_setup.run_options.use_msa_server",
        "value_type": "boolean",
        "description": "Use Boltz's MSA server instead of requiring a precomputed MSA file."
      },
      {
        "name": "sampling_steps",
        "label": "Sampling Steps",
        "default": 200,
        "maps_to": "protein_ligand_setup.run_options.sampling_steps",
        "value_type": "integer",
        "description": "Number of Boltz sampling steps for structure generation."
      },
      {
        "name": "recycling_steps",
        "label": "Recycling Steps",
        "default": 3,
        "maps_to": "protein_ligand_setup.run_options.recycling_steps",
        "value_type": "integer",
        "description": "Number of structure recycling steps."
      },
      {
        "name": "diffusion_samples",
        "label": "Diffusion Samples",
        "default": 1,
        "maps_to": "protein_ligand_setup.run_options.diffusion_samples",
        "value_type": "integer",
        "description": "Number of Boltz diffusion samples to generate."
      },
      {
        "name": "output_format",
        "label": "Output Format",
        "default": "mmcif",
        "maps_to": "protein_ligand_setup.run_options.output_format",
        "value_type": "string",
        "description": "Structure artifact format emitted by Boltz.",
        "allowed_values": [
          "mmcif",
          "pdb"
        ]
      },
      {
        "ui": {
          "rows": 6,
          "control": "json"
        },
        "name": "run_options",
        "label": "Boltz Run Options",
        "format": "json",
        "maps_to": "protein_ligand_setup.run_options",
        "advanced": true,
        "required": false,
        "value_type": "record",
        "description": "Optional structured controls for the Boltz workflow, including sampling settings and interpretation scope."
      }
    ],
    "outputs": [
      {
        "name": "scenario_context",
        "label": "Workflow Scenario Context",
        "maps_to": "protein_ligand_tutorial_context.scenario_context",
        "description": "Source-backed target, ligand, use-case, provenance, and caveat context for this Boltz workflow."
      },
      {
        "name": "assembled_boltz_request",
        "label": "Assembled Boltz Request",
        "maps_to": "protein_ligand_setup.assembled_boltz_request",
        "description": "Traceable summary of the protein, ligand, MSA, and run options prepared for Boltz."
      },
      {
        "name": "affinity_summary",
        "label": "Affinity-Style Summary",
        "maps_to": "boltz_boltz2_affinity_predictor.affinity_summary",
        "description": "Parsed Boltz-2 binder probability and affinity-like outputs for this protein-ligand prediction."
      },
      {
        "name": "confidence_summary",
        "label": "Structure Confidence Summary",
        "maps_to": "boltz_boltz2_affinity_predictor.confidence_summary",
        "description": "Parsed Boltz-2 confidence outputs for the predicted protein-ligand complex."
      },
      {
        "name": "structure_artifacts",
        "label": "Predicted Complex Structure Artifacts",
        "maps_to": "boltz_boltz2_affinity_predictor.structure_artifacts",
        "description": "File-backed predicted complex structures used by the 3D visualisation."
      },
      {
        "name": "run_metadata",
        "label": "Boltz Run Metadata",
        "maps_to": "boltz_boltz2_affinity_predictor.run_metadata",
        "description": "Runtime status, command metadata, logs, and caveats for the latest Boltz invocation."
      },
      {
        "name": "prediction_evidence",
        "label": "Conservative Prediction Evidence",
        "maps_to": "boltz_prediction_interpreter.prediction_evidence",
        "description": "Interpreted Boltz output evidence with request traceability and explicit scientific caveats."
      }
    ]
  },
  "tags": [
    "boltz-workflow",
    "boltz",
    "protein-ligand",
    "affinity",
    "structural-biology",
    "guided-workflow",
    "gpu"
  ],
  "title": "Boltz Workflow: Protein-Ligand 101",
  "models": [
    {
      "path": "models/context",
      "alias": "protein_ligand_tutorial_context",
      "parameters": {
        "scenario": {
          "caveat": "Boltz-2 outputs are computational structure and affinity-style predictions for hypothesis generation; they are not experimental binding, potency, selectivity, clinical, or efficacy evidence.",
          "ligand_role": "teaching ligand",
          "disease_area": "training workflow",
          "target_family": "teaching protein-ligand example",
          "workflow_name": "Protein-Ligand 101",
          "workflow_context": "Guided single protein-ligand Boltz-2 example",
          "workflow_question": "How does a source-backed protein sequence and ligand SMILES become a Boltz-2 complex prediction?",
          "interpretation_scope": "Learning and early hypothesis generation only",
          "protein_sequence_length": 384
        },
        "integration_step": 0.01
      }
    },
    {
      "path": "models/input_assembler",
      "alias": "protein_ligand_setup",
      "parameters": {
        "workflow_kind": "single",
        "workflow_name": "Protein-Ligand 101",
        "integration_step": 0.01,
        "default_run_options": {
          "workflow_name": "Protein-Ligand 101",
          "workflow_context": "Guided single protein-ligand Boltz-2 example",
          "interpretation_scope": "Learning and early hypothesis generation only"
        },
        "default_ligand_smiles": "N[C@@H](Cc1ccc(O)cc1)C(=O)O",
        "default_protein_sequence": "MVTPEGNVSLVDESLLVGVTDEDRAVRSAHQFYERLIGLWAPAVMEAAHELGVFAALAEAPADSGELARRLDCDARAMRVLLDALYAYDVIDRIHDTNGFRYLLSAEARECLLPGTLFSLVGKFMHDINVAWPAWRNLAEVVRHGARDTSGAESPNGIAQEDYESLVGGINFWAPPIVTTLSRKLRASGRSGDATASVLDVGCGTGLYSQLLLREFPRWTATGLDVERIATLANAQALRLGVEERFATRAGDFWRGGWGTGYDLVLFANIFHLQTPASAVRLMRHAAACLAPDGLVAVVDQIVDADREPKTPQDRFALLFAASMTNTGGGDAYTFQEYEEWFTAAGLQRIETLDTPMHRILLARRATEPSAVPEGQASENLYFQ"
      }
    },
    {
      "path": "models/core",
      "alias": "boltz_boltz2_affinity_predictor",
      "parameters": {
        "override": true,
        "accelerator": "gpu",
        "runtime_mode": "managed",
        "output_format": "mmcif",
        "sampling_steps": 200,
        "use_msa_server": true,
        "recycling_steps": 3,
        "diffusion_samples": 1
      }
    },
    {
      "path": "models/interpreter",
      "alias": "boltz_prediction_interpreter",
      "parameters": {
        "mode": "single",
        "caveat": "Boltz-2 outputs are computational structure and affinity-style predictions for hypothesis generation; they are not experimental binding, potency, selectivity, clinical, or efficacy evidence.",
        "core_alias": "boltz_boltz2_affinity_predictor",
        "workflow_name": "Protein-Ligand 101",
        "integration_step": 0.01
      }
    },
    {
      "path": "models/visualisation",
      "alias": "visualisation",
      "parameters": {
        "mode": "boltz",
        "lab_title": "Boltz Workflow: Protein-Ligand 101",
        "source_alias": "boltz_boltz2_affinity_predictor",
        "context_alias": "protein_ligand_tutorial_context",
        "assembler_alias": "protein_ligand_setup",
        "integration_step": 0.01,
        "interpreter_alias": "boltz_prediction_interpreter"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "protein_ligand_setup.scenario_context",
        "boltz_prediction_interpreter.scenario_context",
        "visualisation.protein_ligand_tutorial_context_scenario_context"
      ],
      "from": "protein_ligand_tutorial_context.scenario_context"
    },
    {
      "to": [
        "boltz_boltz2_affinity_predictor.protein_sequence"
      ],
      "from": "protein_ligand_setup.protein_sequence"
    },
    {
      "to": [
        "boltz_boltz2_affinity_predictor.ligand_smiles"
      ],
      "from": "protein_ligand_setup.ligand_smiles"
    },
    {
      "to": [
        "boltz_boltz2_affinity_predictor.msa_path"
      ],
      "from": "protein_ligand_setup.msa_path"
    },
    {
      "to": [
        "boltz_boltz2_affinity_predictor.run_options"
      ],
      "from": "protein_ligand_setup.run_options"
    },
    {
      "to": [
        "boltz_prediction_interpreter.assembled_boltz_request",
        "visualisation.protein_ligand_setup_assembled_boltz_request"
      ],
      "from": "protein_ligand_setup.assembled_boltz_request"
    },
    {
      "to": [
        "visualisation.boltz_boltz2_affinity_predictor_affinity_summary",
        "boltz_prediction_interpreter.boltz_boltz2_affinity_predictor_affinity_summary"
      ],
      "from": "boltz_boltz2_affinity_predictor.affinity_summary"
    },
    {
      "to": [
        "visualisation.boltz_boltz2_affinity_predictor_confidence_summary",
        "boltz_prediction_interpreter.boltz_boltz2_affinity_predictor_confidence_summary"
      ],
      "from": "boltz_boltz2_affinity_predictor.confidence_summary"
    },
    {
      "to": [
        "visualisation.boltz_boltz2_affinity_predictor_structure_artifacts",
        "boltz_prediction_interpreter.boltz_boltz2_affinity_predictor_structure_artifacts"
      ],
      "from": "boltz_boltz2_affinity_predictor.structure_artifacts"
    },
    {
      "to": [
        "visualisation.boltz_boltz2_affinity_predictor_run_metadata",
        "boltz_prediction_interpreter.boltz_boltz2_affinity_predictor_run_metadata"
      ],
      "from": "boltz_boltz2_affinity_predictor.run_metadata"
    },
    {
      "to": [
        "visualisation.boltz_prediction_interpreter_prediction_evidence"
      ],
      "from": "boltz_prediction_interpreter.prediction_evidence"
    }
  ],
  "package": "boltz-protein-ligand-101-workflow",
  "runtime": {
    "duration": 0.01,
    "settle_steps": 1,
    "initial_inputs": {},
    "python_version": "3.10",
    "communication_step": 0.01
  },
  "version": "1.0.0",
  "description": "Guided Boltz-2 workflow for learning how a protein sequence and ligand SMILES become a predicted complex, binder probability, affinity-like value, confidence metrics, and reproducible report context.",
  "schema_version": "2.0"
}