--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/ob_spectrophore_search.py	Sat May 20 08:38:05 2017 -0400
@@ -0,0 +1,66 @@
+#!/usr/bin/env python
+"""
+    Input: tabular format file with one column storing the unique id for the compounds and any other with the Spectrophores(TM) descriptors.
+    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.
+    Copyright 2012, Bjoern Gruening and Xavier Lucas
+"""
+import sys, os
+import argparse
+import openbabel
+openbabel.obErrorLog.StopLogging()
+import pybel
+import math
+import numpy as np
+
+#TODO get rid of eval()
+
+global spectrophore
+spectrophore = pybel.ob.OBSpectrophore()
+
+def parse_command_line():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--target', required=True, help='target file name in sdf format with Spectrophores(TM) descriptors stored as meta-data')
+    parser.add_argument('--library', required=True, help='library of compounds with pre-computed physico-chemical properties, including Spectrophores(TM) in tabular format')
+    parser.add_argument('-c', '--column', required=True, type=int, help='#column containing the Spectrophores(TM) descriptors in the library file')
+    parser.add_argument('-o', '--output', required=True, help='output file name')
+    parser.add_argument('-n', '--normalization', default="ZeroMeanAndUnitStd", choices=['No', 'ZeroMean', 'UnitStd', 'ZeroMeanAndUnitStd'], help='Normalization method')
+    parser.add_argument('-a', '--accuracy', default="20", choices=['1', '2', '5', '10', '15', '20', '30', '36', '45', '60'], help='Accuracy expressed as angular stepsize')
+    parser.add_argument('-s', '--stereo', default="No", choices=['No', 'Unique', 'Mirror', 'All'], help='Stereospecificity of the cage')
+    parser.add_argument('-r', '--resolution', type=float, default="3.0", help='Resolution')
+    return parser.parse_args()
+
+def set_parameters(args):
+    if args.normalization == 'No':
+        spectrophore.SetNormalization( spectrophore.NoNormalization )
+    else:
+        spectrophore.SetNormalization( eval('spectrophore.NormalizationTowards' + args.normalization) )
+    spectrophore.SetAccuracy( eval('spectrophore.AngStepSize' + args.accuracy) )
+    spectrophore.SetStereo( eval('spectrophore.' + args.stereo + 'StereoSpecificProbes') )
+    spectrophore.SetResolution( args.resolution )
+    return True
+
+def Compute_Spectrophores_distance(target_spectrophore, args):
+    outfile = open(args.output, 'w')
+    for mol in open(args.library, 'r'):
+        try:
+            distance = ( ( np.asarray( target_spectrophore, dtype=float ) - np.asarray( mol.split('\t')[ args.column - 1 ].strip().split(', '), dtype=float) )**2).sum()
+        except ValueError:
+            distance = 0
+        outfile.write( '%s\t%f\n' % (mol.strip(), distance ) )
+    outfile.close()
+
+def __main__():
+    """
+        Computation of Spectrophores(TM) distances to a target molecule.
+    """
+    args = parse_command_line()
+    # This sets up the parameters for the Spectrophore generation. Parameters are set to fit those of our standard parsing tool
+    set_parameters(args)
+
+    mol = pybel.readfile('sdf', args.target).next()
+    target_spectrophore = mol.data["Spectrophores(TM)"].strip().split(', ')
+    # Compute the paired-distance between every molecule in the library and the target
+    distances = Compute_Spectrophores_distance(target_spectrophore, args)
+
+if __name__ == "__main__" :
+    __main__()