  uasge:

     prank <command> <dataset.ds> [options]

  commands:

     predict      ... predict pockets (P2RANK)

     eval-predict ... evaluate model on a dataset with known ligands

     rescore      ... rescore previously detected pockets (PRANK)

     eval-rescore ... evaluate rescoring model on a dataset with known ligands

  datasets:

        Dataset files for prediction should contain list of pdb files.
        Dataset files for rescoring should contain list of protein files
        that are outputs of one of the supported pocket prediction methods
        (fpocket, ConCavity). In datasets for evaluation and training they
        must be paired with liganated-proteins (correct solutions).
        See example datasets in test_data/ directory.

  options:

     -f <path>   run on single pdb file instead of a dataset

     -c <path>   use configuration file that overrides default configuration
                 in config/default.groovy, path relative to config/ directory

     -m <path>   use previously trained classifier file relative to models/ directory
                 default: models/default.model

     -o <path>   specify output directory (relative to working dir)
                 default: test_output/<comamnd>_<dataset>

  other parameters:

     -threads <int>         number of execution threads
                            dafault: num. of processors + 1

     -visualizations <0/1>  produce PyMOL visualizations
                            default: true

     -<param> <value>       for full list of parameters see config/default.groovy