flowdock/params.json

{
    "params": {
        "input_receptor": {
            "type": "string",
            "description": "Protein sequence(s) in single-letter amino acid code. Multiple chains separated by '|'",
            "default": "YNKIVHLLVAEPEKIYAMPDPTVPDSDIKALTTLCDLADRELVVIIGWAKHIPGFSTLSLADQMSLLQSAWMEILILGVVYRSLFEDELVYADDYIMDEDQSKLAGLLDLNNAILQLVKKYKSMKLEKEEFVTLKAIALANSDSMHIEDVEAVQKLQDVLHEALQDYEAGQHMEDPRRAGKMLMTLPLLRQTSTKAVQHFYNKLEGKVPMHKLFLEMLEAKV",
            "required": true,
            "pipeline_io": "input",
            "var_name": "params.input_receptor",
            "examples": [
                "YNKIVHLLVAEPEKIYAMPDPTVPDSDIKALTTLCDLADRELVVIIGWAKHIPGFSTLSLADQMSLLQSAWMEILILGVVYRSLFEDELVYADDYIMDEDQSKLAGLLDLNNAILQLVKKYKSMKLEKEEFVTLKAIALANSDSMHIEDVEAVQKLQDVLHEALQDYEAGQHMEDPRRAGKMLMTLPLLRQTSTKAVQHFYNKLEGKVPMHKLFLEMLEAKV",
                "MYTVKPGDTMWKIAVKYQIGISEIIAANPQIKNPNLIYPGQKINIP|MYTVKPGDTMWKIAVKYQIGISEIIAANPQIKNPNLIYPGQKINIP"
            ],
            "pattern": "^[ACDEFGHIKLMNPQRSTVWY|]+$",
            "enum": [],
            "validation": {},
            "notes": "For multi-chain proteins, separate sequences with '|' character."
        },
        "input_ligand": {
            "type": "string",
            "description": "Ligand SMILES string for docking",
            "default": "c1cc2c(cc1O)CCCC2",
            "required": true,
            "pipeline_io": "input",
            "var_name": "params.input_ligand",
            "examples": [
                "c1cc2c(cc1O)CCCC2",
                "CC(=O)NC1C(O)OC(CO)C(OC2OC(CO)C(O)C(O)C2NC(C)=O)C1O"
            ],
            "pattern": ".*",
            "enum": [],
            "validation": {},
            "notes": "SMILES notation for the ligand molecule."
        },
        "input_template": {
            "type": "file",
            "description": "Optional template PDB structure for protein. If empty, ESMFold will predict the structure",
            "default": "",
            "required": false,
            "pipeline_io": "input",
            "var_name": "params.input_template",
            "examples": [
                "/path/to/template.pdb",
                ""
            ],
            "pattern": ".*\\.pdb$",
            "enum": [],
            "validation": {},
            "notes": "Providing a template can improve docking quality. Leave empty to use ESMFold-predicted structure."
        },
        "sample_id": {
            "type": "string",
            "description": "Unique identifier for the prediction sample",
            "default": "flowdock_sample",
            "required": false,
            "pipeline_io": "parameter",
            "var_name": "params.sample_id",
            "examples": [
                "6i67",
                "T1152",
                "my_protein_ligand"
            ],
            "pattern": "^[a-zA-Z0-9_-]+$",
            "enum": [],
            "validation": {},
            "notes": "Used for naming output directories and files."
        },
        "outdir": {
            "type": "folder",
            "description": "Directory for FlowDock output results",
            "default": "s3://omic/eureka/flowdock/output/",
            "required": true,
            "pipeline_io": "output",
            "var_name": "params.outdir",
            "examples": [
                "./flowdock_output",
                "/data/predictions/flowdock"
            ],
            "pattern": ".*",
            "enum": [],
            "validation": {},
            "notes": "Directory where PDB structures and logs will be stored."
        },
        "n_samples": {
            "type": "integer",
            "description": "Number of prediction samples to generate",
            "default": 5,
            "required": false,
            "pipeline_io": "parameter",
            "var_name": "params.n_samples",
            "examples": [1, 5, 10, 40],
            "pattern": "^[1-9][0-9]*$",
            "enum": [],
            "validation": {
                "min": 1,
                "max": 100
            },
            "notes": "Higher values provide more conformational diversity but increase computation time."
        }
    }
}