TEMPy.protein.scoring_functions.ScoringFunctions.SMOC
- 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
- Parameters:
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.
- Returns:
- 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:
Dictionary