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annotate ob_spectrophore_search.py @ 7:d2e6d682bcd0 draft

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author bgruening
date Tue, 07 May 2019 13:37:26 -0400
parents a3c767e30424
children 43167f164076
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1 #!/usr/bin/env python
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2 """
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3 Input: tabular format file with one column storing the unique id for the compounds and any other with the Spectrophores(TM) descriptors.
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4 Output: parse the target file using the same protocol used to generate the databases in our servers. Physico-chemical properties are computed and stored as metadata in the sdf output file.
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5 Copyright 2012, Bjoern Gruening and Xavier Lucas
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6 """
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7 import sys, os
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8 import argparse
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9 import openbabel
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10 openbabel.obErrorLog.StopLogging()
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11 import pybel
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12 import math
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13 import numpy as np
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15 #TODO get rid of eval()
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17 global spectrophore
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18 spectrophore = pybel.ob.OBSpectrophore()
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20 def parse_command_line():
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21 parser = argparse.ArgumentParser()
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22 parser.add_argument('--target', required=True, help='target file name in sdf format with Spectrophores(TM) descriptors stored as meta-data')
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23 parser.add_argument('--library', required=True, help='library of compounds with pre-computed physico-chemical properties, including Spectrophores(TM) in tabular format')
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24 parser.add_argument('-c', '--column', required=True, type=int, help='#column containing the Spectrophores(TM) descriptors in the library file')
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25 parser.add_argument('-o', '--output', required=True, help='output file name')
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26 parser.add_argument('-n', '--normalization', default="ZeroMeanAndUnitStd", choices=['No', 'ZeroMean', 'UnitStd', 'ZeroMeanAndUnitStd'], help='Normalization method')
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27 parser.add_argument('-a', '--accuracy', default="20", choices=['1', '2', '5', '10', '15', '20', '30', '36', '45', '60'], help='Accuracy expressed as angular stepsize')
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28 parser.add_argument('-s', '--stereo', default="No", choices=['No', 'Unique', 'Mirror', 'All'], help='Stereospecificity of the cage')
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29 parser.add_argument('-r', '--resolution', type=float, default="3.0", help='Resolution')
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30 return parser.parse_args()
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31
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32 def set_parameters(args):
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33 if args.normalization == 'No':
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34 spectrophore.SetNormalization( spectrophore.NoNormalization )
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35 else:
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36 spectrophore.SetNormalization( eval('spectrophore.NormalizationTowards' + args.normalization) )
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37 spectrophore.SetAccuracy( eval('spectrophore.AngStepSize' + args.accuracy) )
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38 spectrophore.SetStereo( eval('spectrophore.' + args.stereo + 'StereoSpecificProbes') )
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39 spectrophore.SetResolution( args.resolution )
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40 return True
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42 def Compute_Spectrophores_distance(target_spectrophore, args):
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43 outfile = open(args.output, 'w')
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44 for mol in open(args.library, 'r'):
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45 try:
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46 distance = ( ( np.asarray( target_spectrophore, dtype=float ) - np.asarray( mol.split('\t')[ args.column - 1 ].strip().split(', '), dtype=float) )**2).sum()
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47 except ValueError:
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48 distance = 0
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49 outfile.write( '%s\t%f\n' % (mol.strip(), distance ) )
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50 outfile.close()
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51
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52 def __main__():
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53 """
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54 Computation of Spectrophores(TM) distances to a target molecule.
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55 """
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56 args = parse_command_line()
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57 # This sets up the parameters for the Spectrophore generation. Parameters are set to fit those of our standard parsing tool
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58 set_parameters(args)
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59
3
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60 mol = next(pybel.readfile('sdf', args.target))
0
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61 target_spectrophore = mol.data["Spectrophores(TM)"].strip().split(', ')
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62 # Compute the paired-distance between every molecule in the library and the target
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63 distances = Compute_Spectrophores_distance(target_spectrophore, args)
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64
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65 if __name__ == "__main__" :
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66 __main__()