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Sourcecode: python-biopython version File versions


# Copyright Yair Benita Y.Benita@pharm.uu.nl
# Biopython (http://biopython.org) license applies

import sys
import ProtParamData, IsoelectricPoint
from ProtParamData import kd  # Added by Iddo to enable the gravy method
from Bio.Seq import Seq
from Bio.Alphabet import IUPAC
from Bio.Data import IUPACData
#from BioModule import 

00012 class ProteinAnalysis:
      This class contains methods for protein analysis.  The class init method takes
      only one argument, the protein sequence as a string and build a sequence
      object using the Bio.Seq module. This is done just to make sure the sequence
      is a protein sequence and not anything else.
      Simply counts the number times an amino acid is repeated in the protein
      sequence. Returns a dictionary {AminoAcid:Number} and also stores the
      dictionary in self.amino_acids_content.
      The same as count_amino_acids only returns the Number in percentage of entire
      sequence. Returns a dictionary and stores the dictionary in
      Calculates the molecular weight of a protein.
      Calculates the aromaticity value of a protein according to Lobry, 1994. It is
      simply the relative frequency of Phe+Trp+Tyr.
      Implementation of the method of Guruprasad et al. (Protein Engineering
      4:155-161,1990). This method tests a protein for stability. Any value above 40
      means the protein is unstable (=has a short half life). 
      Implementation of the flexibility method of Vihinen et al. (Proteins. 1994 Jun;19(2):141-9).
      This method uses the module IsoelectricPoint to calculate the pI of a protein.
      This methods returns a list of the fraction of amino acids which tend to be in Helix, Turn or Sheet.
      Amino acids in helix: V, I, Y, F, W, L.
      Amino acids in Turn: N, P, G, S.
      Amino acids in sheet: E, M, A, L.
      The list contains 3 values: [Helix, Turn, Sheet].
      protein_scale(Scale, WindwonSize, Edge):
      An amino acid scale is defined by a numerical value assigned to each type of
      amino acid. The most frequently used scales are the hydrophobicity or
      hydrophilicity scales and the secondary structure conformational parameters
      scales, but many other scales exist which are based on different chemical and
      physical properties of the amino acids.  You can set several  parameters that
      control the computation  of a scale profile, such as the window size and the
      window edge relative weight value.  WindowSize: The window size is the length
      of the interval to use for the profile computation. For a window size n, we
      use the i- ( n-1)/2 neighboring residues on each side of residue it compute
      the score for residue i. The score for residue is  the sum of the scale values
      for these amino acids,  optionally weighted according to their position in the
      window.  Edge: The central amino acid of the window always has a weight of 1.
      By default, the amino acids at the remaining window positions have the same
      weight, but  you can make the residue at the center of the window  have a
      larger weight than the others by setting the edge value for the  residues at
      the beginning and end of the interval to a value between 0 and 1. For
      instance, for Edge=0.4 and a window size of 5 the weights will be: 0.4, 0.7,
      1.0, 0.7, 0.4.  The method returns a list of values which can be plotted to
      view the change along a protein sequence.  Many scales exist. Just add your
      favorites to the ProtParamData modules.
      def __init__(self, ProtSequence):
            if ProtSequence.islower():
                  self.sequence = Seq(ProtSequence.upper(), IUPAC.protein)
                  self.sequence = Seq(ProtSequence, IUPAC.protein)
            self.amino_acids_content = None
            self.amino_acids_percent = None
            self.length = len(self.sequence)
      def count_amino_acids(self):
            ProtDic = dict([ (k, 0) for k in IUPACData.protein_letters])
            for i in ProtDic.keys():
            self.amino_acids_content = ProtDic
            return ProtDic
      """Calculate the amino acid content in percents.
      input is the dictionary from CountAA.
      output is a dictionary with AA as keys."""
      def get_amino_acids_percent(self):
            if not self.amino_acids_content:
            PercentAA = {}
            for i in self.amino_acids_content.keys():
                  if self.amino_acids_content[i] > 0:
                        PercentAA[i] = 0
            self.amino_acids_percent = PercentAA
            return PercentAA

      # Calculate MW from Protein sequence
      # Calculate MW from Protein sequence
      def molecular_weight (self):
            # make local dictionary for speed
            MwDict = {}
            # remove a molecule of water from the amino acid weight.
            for i in IUPACData.protein_weights.keys():
                  MwDict[i] = IUPACData.protein_weights[i] - 18.02
            MW = 18.02 # add just one water molecule for the whole sequence.
            for i in self.sequence:
                  MW += MwDict[i]
            return MW

      # calculate the aromaticity according to Lobry, 1994.
      # Arom=sum of relative frequency of Phe+Trp+Tyr       
      def aromaticity(self):
            if not self.amino_acids_percent:
            Arom= self.amino_acids_percent['Y']+self.amino_acids_percent['W']+self.amino_acids_percent['F']
            return Arom

      # a function to calculate the instability index according to:
      # Guruprasad K., Reddy B.V.B., Pandit M.W.    Protein Engineering 4:155-161(1990).
      def instability_index(self):
            #make the dictionary local for speed.
            for i in range(self.length - 1):
                  score += DiPeptide
            return (10.0/self.length) * score
      # Calculate the flexibility according to Vihinen, 1994.
      # No argument to change window size because parameters are specific for a window=9. 
      # the parameters used are optimized for determining the flexibility.
      def flexibility(self):
            Flex = ProtParamData.Flex.copy()
            for i in range(self.length - Window):
                  score = 0.0
                  for j in range(Window/2):
                        score += (Flex[SubSeq[j]]+Flex[SubSeq[Window-j-1]]) * Weights[j]
                  score += Flex[SubSeq[Window/2+1]]
            return List

      # calculate the gravy according to kyte and doolittle.
      def gravy(self):
            for i in self.sequence:
                  ProtGravy += kd[i]
            return ProtGravy/self.length

      # this method is used to make a list of relative weight of the
      # window edges compared to the window center. The weights are linear.
      # it actually generates half a list. For a window of size 9 and edge 0.4
      # you get a list of [0.4, 0.55, 0.7, 0.85]. 
      def _weight_list(self, window, edge):
            unit = ((1.0-edge)/(window-1))*2
            list = [0.0]*(window/2)
            for i in range(window/2):
                  list[i] = edge + unit * i
            return list
      # this method allows you to compute and represent the profile produced
      # by any amino acid scale on a selected protein.
      # Similar to expasy's ProtScale: http://www.expasy.org/cgi-bin/protscale.pl
      # The weight list returns only one tail. If the list should be [0.4,0.7,1.0,0.7,0.4]
      # what you actually get from _weights_list is [0.4,0.7]. The correct calculation is done
      # in the loop.
      def protein_scale(self, ParamDict, Window, Edge=1.0):
            # generate the weights
            weight = self._weight_list(Window,Edge)
            list = []
            # the score in each Window is divided by the sum of weights
            sum_of_weights = 0.0
            for i in weight: sum_of_weights += i
            # since the weight list is one sided:
            sum_of_weights = sum_of_weights*2+1
            for i in range(self.length-Window+1):
                  subsequence = self.sequence[i:i+Window]
                  score = 0.0
                  for j in range(Window/2):
                        # walk from the outside of the Window towards the middle.
                        # Iddo: try/except clauses added to avoid raising an exception on a non-standad amino acid
                                    score += weight[j] * ParamDict[subsequence[j]] + weight[j] * ParamDict[subsequence[Window-j-1]]
                              except KeyError:
                                    sys.stderr.write('warning: %s or %s is not a standard amino acid.\n' %

                  # Now add the middle value, which always has a weight of 1.
                  if subsequence[Window/2] in ParamDict:
                        score += ParamDict[subsequence[Window/2]]
                        sys.stderr.write('warning: %s  is not a standard amino acid.\n' % (subsequence[Window/2]))
            return list

      # calculate the isoelectric point.  
      def isoelectric_point(self):
            if not self.amino_acids_content:
            X = IsoelectricPoint.IsoelectricPoint(self.sequence, self.amino_acids_content)
            return X.pi()
      # calculate fraction of helix, turn and sheet
      def secondary_structure_fraction (self):
            if not self.amino_acids_percent:
            Helix = self.amino_acids_percent['V'] + self.amino_acids_percent['I'] + self.amino_acids_percent['Y'] + self.amino_acids_percent['F'] + self.amino_acids_percent['W'] + self.amino_acids_percent['L']
            Turn = self.amino_acids_percent['N'] + self.amino_acids_percent['P'] + self.amino_acids_percent['G'] + self.amino_acids_percent['S']
            Sheet = self.amino_acids_percent['E'] + self.amino_acids_percent['M'] + self.amino_acids_percent['A'] + self.amino_acids_percent['L']
            return Helix, Turn, Sheet

print X.count_amino_acids()
print X.get_amino_acids_percent()
print X.molecular_weight()
print X.aromaticity()
print X.instability_index()
print X.flexibility()
print X.pi()
print X.secondary_structure_fraction()
print X.protein_scale(ProtParamData.kd, 9, 0.4)

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