PepINVENT/rl_input_example.json at master · lich-uct/PepINVENT · GitHub

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{
  "name": "example_linear",
  "model_type": "mol2mol",
  "model_path": "/home/senovad/PepINVENT/data/models/finetuned_model/checkpoint/model_136.ckpt",
  "input_sequence": "N[C@@H](CCCCN)C(=O)|N[C@@H](CCCNC(=N)N)C(=O)|N[C@@H](CCCNC(=N)N)C(=O)|N[C@@H](Cc1c[nH]c2ccccc12)C(=O)|N[C@@H](CCCNC(=N)N)C(=O)|N[C@@H](CC(=O)N)C(=O)|N[C@@H]([C@H](CC)C)C(=O)|?|?|N[C@@H](CC(C)C)C(=O)|N[C@@H](Cc1ccccc1)C(=O)|?|N[C@@H](CCCCN)C(=O)|N[C@@H]([C@H](CC)C)C(=O)|N[C@@H](CO)C(=O)|N[C@@H](CC(C)C)C(=O)O",
  "learning_configuration": {
    "number_steps": 100,
    "batch_size": 32,
    "score_multiplier": 50,
    "learning_rate": 0.0001
  },
  "scoring_function": {
    "scoring_function": "weighted_average",
    "scoring_components": [
      {
        "name": "maximum_ring_size",
        "weight": 1,
        "specific_parameters": {
          "transformation": {
            "transformation_type": "step",
            "low": 6,
            "high": 7
          }
        }
      },
      {
        "name": "custom_alerts",
        "weight": 1,
        "specific_parameters": {
          "smarts": [
            "N(C)(C=O)C",
            "[F,Cl,Br,I]",
            "[S&!D2]",
            "c1ccccc1OC",
            "N(C)C",
            "C[C@H]1CC[C@@H](C)CC1",
            "[#8][#8]",
            "[#6;+]",
            "[#7;!n][#7;!n]",
            "C#C",
            "[#7;!n][C;!$(C(=[O,N])[N,O])][#7;!n]",
            "[#8;!o][C;!$(C(=[O,N])[N,O])][#8;!o]"
          ]
        }
      }
    ]
  },
  "logging": {
    "logging_path": "/home/senovad/PepINVENT/data/logging/path/tensorboard",
    "result_path": "/home/senovad/PepINVENT/data/logging/path/results"
  },
  "diversity_filter": {
    "name": "NoFilterWithPenalty",
    "score_threshold": 0.1,
    "bucket_size": 25,
    "similarity_threshold": 0.4,
    "penalty": 0.5
  }
}