ScoringFunctions.SMOC(map_target, resolution_densMap, structure_instance=None, win=11, rigid_body_file=None, sim_map=None, sigma_map=0.225, write=False, c_mode=True, sigma_thr=2.5, fragment_score=True, dist=5.0, atom_centre='CA', calc_metric='smoc', get_coord=True)[source]

Calculate the local Mander’s Overlap for each residue in a protein model

SMOC can be calculated in two ways:

  • SMOCf: The SMOC score is calculated for residues adjacent in sequence, using a sliding and overlapping window.

  • SMOCd: Pixels are scored in a spherical radius around each residue

  • map_target – Target Map Instance.

  • resolution_densMap – Resolution of the target map.

  • structure_instance – Model structure instance.

  • win – Overlapping Window length to calculate the score

  • rigid_body_file – Path to rigid-body file.

  • sim_map – Precomputed simulated map. If None, sim_map is calculated automatically.

  • sigma_map – Parameter need for Structure Blurrer. Full explanation here

  • write – Deprecated, not used.

  • c_mode – Deprecated, not used.

  • sigma_thr – Parameter used to label pixels near each atom in the model. Explained in further detail here

  • fragment_score – If True, use SMOCf method. If False, use SMOCd method.

  • dist – Deprecated, not used.

  • atom_centre – Which atom type should be considered the centre of residues.

  • calc_metric – Which method to use for calculating the local score at each residue. Can be "smoc" or "sccc"

  • get_coord – Return additional dict_chain_CA dictionary.


The dictionaries dict_chain_scores, dict_chain_res.

dict_chain_CA is returned additionally if get_coord = True

  • dict_chain_scores: 2D dictionary containing the SMOC scores for each residue. Keys are chain_label for first dictionary and residue_number for second dictionary, e.g.: dict_chain_scores[chain_label][residue_number] = SMOC_score

  • dict_chain_res: Dictionary with chain labels (e.g. "A") as keys and a list of all residue numbers for a given chain as values.

  • dict_chain_CA: 2D dictionary containing a list for each residue, containing the amino acid type of each residue and its 3D coordinates. Keys are chain_label for first dictionary and residue_number for second dictionary, e.g.: dict_chain_CA[chain_label][residue_number] = residue_info where, residue_info = [residue_type, x, y, z]

Return type: