Module protkit.metrics.structure_eval
Implements class StructureEval for evaluating protein structures.
Various scores, such as RMSD, TMScore, GDT TS and Fnat, can be calculated to evaluate the quality of a protein structure. These scores can be used to compare two structures or to evaluate a single structure against a reference structure.
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#!/usr/bin/env python3
# -*- coding:utf-8 -*-
# Authors: Fred Senekal (FS)
# Contact: fred@silicogenesis.com
# License: GPLv3
"""
Implements class `StructureEval` for evaluating protein structures.
Various scores, such as RMSD, TMScore, GDT TS and Fnat, can be calculated to evaluate
the quality of a protein structure. These scores can be used to compare two structures
or to evaluate a single structure against a reference structure.
"""
from typing import List
class StructureEval:
@staticmethod
def RMSD(coordinates: List[List[float]], reference: List[List[float]]):
"""
Calculates the root-mean-square deviation (RMSD) between two sets of coordinates.
It provides a measure of the average distance between atoms of two superimposed structures.
See https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions.
Args:
coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated.
reference (List[List[float]]): A list of lists containing the reference coordinates.
Returns:
float: A float representing the RMSD between the two sets of coordinates.
"""
rmsd = 0.0
for i in range(len(coordinates)):
rmsd += (coordinates[i][0] - reference[i][0])**2 + (coordinates[i][1] - reference[i][1])**2 + (coordinates[i][2] - reference[i][2])**2
return (rmsd / len(coordinates))**0.5
@staticmethod
def TMscore(coordinates: List[List[float]], reference: List[List[float]]):
"""
Calculates the template modelling (TM-score) between two sets of coordinates.
The TM-score is a measure of the structural similarity between two protein structures.
It is intended to be more robust to variations in protein length than the RMSD. It
provides a score in the range (0, 1] where 1 indicates a perfect match. See
https://en.wikipedia.org/wiki/Template_modeling_score
Args:
coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated.
reference (List[List[float]]): A list of lists containing the reference coordinates.
Returns:
float: A float representing the TM-score between the two sets of coordinates.
"""
raise NotImplementedError("TMscore() not implemented yet.")
@staticmethod
def GDT_TS(coordinates: List[List[float]], reference: List[List[float]]):
"""
Calculates the GDT_TS score between two sets of coordinates.
Args:
coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated.
reference (List[List[float]]): A list of lists containing the reference coordinates.
Returns:
float: A float representing the GDT_TS score between the two sets of coordinates.
"""
raise NotImplementedError("GDS_TS() not implemented yet.")
@staticmethod
def Fnat():
"""
Calculates the fraction of native contacts (Fnat).
"""
raise NotImplementedError("Fnat() score not implemented yet.")Classes
class StructureEval-
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class StructureEval: @staticmethod def RMSD(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the root-mean-square deviation (RMSD) between two sets of coordinates. It provides a measure of the average distance between atoms of two superimposed structures. See https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions. Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the RMSD between the two sets of coordinates. """ rmsd = 0.0 for i in range(len(coordinates)): rmsd += (coordinates[i][0] - reference[i][0])**2 + (coordinates[i][1] - reference[i][1])**2 + (coordinates[i][2] - reference[i][2])**2 return (rmsd / len(coordinates))**0.5 @staticmethod def TMscore(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the template modelling (TM-score) between two sets of coordinates. The TM-score is a measure of the structural similarity between two protein structures. It is intended to be more robust to variations in protein length than the RMSD. It provides a score in the range (0, 1] where 1 indicates a perfect match. See https://en.wikipedia.org/wiki/Template_modeling_score Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the TM-score between the two sets of coordinates. """ raise NotImplementedError("TMscore() not implemented yet.") @staticmethod def GDT_TS(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the GDT_TS score between two sets of coordinates. Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the GDT_TS score between the two sets of coordinates. """ raise NotImplementedError("GDS_TS() not implemented yet.") @staticmethod def Fnat(): """ Calculates the fraction of native contacts (Fnat). """ raise NotImplementedError("Fnat() score not implemented yet.")Static methods
def Fnat()-
Calculates the fraction of native contacts (Fnat).
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@staticmethod def Fnat(): """ Calculates the fraction of native contacts (Fnat). """ raise NotImplementedError("Fnat() score not implemented yet.") def GDT_TS(coordinates: List[List[float]], reference: List[List[float]])-
Calculates the GDT_TS score between two sets of coordinates.
Args
coordinates:List[List[float]]- A list of lists containing the coordinates to be evaluated.
reference:List[List[float]]- A list of lists containing the reference coordinates.
Returns
float- A float representing the GDT_TS score between the two sets of coordinates.
Expand source code
@staticmethod def GDT_TS(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the GDT_TS score between two sets of coordinates. Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the GDT_TS score between the two sets of coordinates. """ raise NotImplementedError("GDS_TS() not implemented yet.") def RMSD(coordinates: List[List[float]], reference: List[List[float]])-
Calculates the root-mean-square deviation (RMSD) between two sets of coordinates.
It provides a measure of the average distance between atoms of two superimposed structures. See https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions.
Args
coordinates:List[List[float]]- A list of lists containing the coordinates to be evaluated.
reference:List[List[float]]- A list of lists containing the reference coordinates.
Returns
float- A float representing the RMSD between the two sets of coordinates.
Expand source code
@staticmethod def RMSD(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the root-mean-square deviation (RMSD) between two sets of coordinates. It provides a measure of the average distance between atoms of two superimposed structures. See https://en.wikipedia.org/wiki/Root-mean-square_deviation_of_atomic_positions. Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the RMSD between the two sets of coordinates. """ rmsd = 0.0 for i in range(len(coordinates)): rmsd += (coordinates[i][0] - reference[i][0])**2 + (coordinates[i][1] - reference[i][1])**2 + (coordinates[i][2] - reference[i][2])**2 return (rmsd / len(coordinates))**0.5 def TMscore(coordinates: List[List[float]], reference: List[List[float]])-
Calculates the template modelling (TM-score) between two sets of coordinates.
The TM-score is a measure of the structural similarity between two protein structures. It is intended to be more robust to variations in protein length than the RMSD. It provides a score in the range (0, 1] where 1 indicates a perfect match. See https://en.wikipedia.org/wiki/Template_modeling_score
Args
coordinates:List[List[float]]- A list of lists containing the coordinates to be evaluated.
reference:List[List[float]]- A list of lists containing the reference coordinates.
Returns
float- A float representing the TM-score between the two sets of coordinates.
Expand source code
@staticmethod def TMscore(coordinates: List[List[float]], reference: List[List[float]]): """ Calculates the template modelling (TM-score) between two sets of coordinates. The TM-score is a measure of the structural similarity between two protein structures. It is intended to be more robust to variations in protein length than the RMSD. It provides a score in the range (0, 1] where 1 indicates a perfect match. See https://en.wikipedia.org/wiki/Template_modeling_score Args: coordinates (List[List[float]]): A list of lists containing the coordinates to be evaluated. reference (List[List[float]]): A list of lists containing the reference coordinates. Returns: float: A float representing the TM-score between the two sets of coordinates. """ raise NotImplementedError("TMscore() not implemented yet.")