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planemo upload commit b9501ecca66b6a66c8cb87b945ad5f95181d7790-dirty
author marpiech
date Thu, 06 Oct 2016 07:09:26 -0400
parents 75f2b4087722
children
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1 #! /usr/bin/env python
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2 #
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3 # Substitute for rbtether of rDock. Will align input molecules to a reference fragment defined by a smarts string,
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4 # it will add a TETHERED ATOM property field to the output SDF that is correctly understood by rDock
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5 # rDock will restrain the matching atom positions to the reference molecule coordinates.
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6 #
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7 # Initially implemented with a conformational search algorithm to better match target coordinates.
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8 # But had problems with OBabel FF generating non-sense conformers. So in this version the conformer search is commented out.
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9 # Now if the input molecule do not have a good conformation, might not align well with the target. This effect will be
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10 # dimished or even vanish if the SMARTS string is defined for a rigid region (like a ring).
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11 # I'm still trying to incorporate somehow this conformational search.
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12 #
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13 # Script distributed under GNU LGPL 3.0 along rDock software.
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14 #
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15 # Author: Daniel Alvarez-Garcia
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16 # Date: 08-11-2013
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17
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18 import math
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19 import pybel
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20 import numpy as npy
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21
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22 def superpose3D(ref, target, weights=None,refmask=None,targetmask=None,returnRotMat=False):
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23 """superpose3D performs 3d superposition using a weighted Kabsch algorithm : http://dx.doi.org/10.1107%2FS0567739476001873 & doi: 10.1529/biophysj.105.066654
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24 definition : superpose3D(ref, target, weights,refmask,targetmask)
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25 @parameter 1 : ref - xyz coordinates of the reference structure (the ligand for instance)
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26 @type 1 : float64 numpy array (nx3)
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27 ---
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28 @parameter 2 : target - theoretical target positions to which we should move (does not need to be physically relevant.
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29 @type 2 : float 64 numpy array (nx3)
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30 ---
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31 @parameter 3: weights - numpy array of atom weights (usuallly between 0 and 1)
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32 @type 3 : float 64 numpy array (n)
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33 @parameter 4: mask - a numpy boolean mask for designating atoms to include
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34 Note ref and target positions must have the same dimensions -> n*3 numpy arrays where n is the number of points (or atoms)
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35 Returns a set of new coordinates, aligned to the target state as well as the rmsd
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36 """
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37 if weights == None :
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38 weights=1.0
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39 if refmask == None :
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40 refmask=npy.ones(len(ref),"bool")
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41 if targetmask == None :
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42 targetmask=npy.ones(len(target),"bool")
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43 #first get the centroid of both states
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44 ref_centroid = npy.mean(ref[refmask]*weights,axis=0)
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45 #print ref_centroid
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46 refCenteredCoords=ref-ref_centroid
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47 #print refCenteredCoords
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48 target_centroid=npy.mean(target[targetmask]*weights,axis=0)
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49 targetCenteredCoords=target-target_centroid
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50 #print targetCenteredCoords
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51 #the following steps come from : http://www.pymolwiki.org/index.php/OptAlign#The_Code and http://en.wikipedia.org/wiki/Kabsch_algorithm
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52 # Initial residual, see Kabsch.
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53 E0 = npy.sum( npy.sum(refCenteredCoords[refmask] * refCenteredCoords[refmask]*weights,axis=0),axis=0) + npy.sum( npy.sum(targetCenteredCoords[targetmask] * targetCenteredCoords[targetmask]*weights,axis=0),axis=0)
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54 reftmp=npy.copy(refCenteredCoords[refmask])
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55 targettmp=npy.copy(targetCenteredCoords[targetmask])
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56 #print refCenteredCoords[refmask]
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57 #single value decomposition of the dotProduct of both position vectors
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58 try:
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59 dotProd = npy.dot( npy.transpose(reftmp), targettmp* weights)
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60 V, S, Wt = npy.linalg.svd(dotProd )
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61 except Exception:
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62 try:
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63 dotProd = npy.dot( npy.transpose(reftmp), targettmp)
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64 V, S, Wt = npy.linalg.svd(dotProd )
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65 except Exception:
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66 print >> sys.stderr,"Couldn't perform the Single Value Decomposition, skipping alignment"
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67 return ref, 0
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68 # we already have our solution, in the results from SVD.
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69 # we just need to check for reflections and then produce
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70 # the rotation. V and Wt are orthonormal, so their det's
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71 # are +/-1.
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72 reflect = float(str(float(npy.linalg.det(V) * npy.linalg.det(Wt))))
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73 if reflect == -1.0:
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74 S[-1] = -S[-1]
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75 V[:,-1] = -V[:,-1]
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76 rmsd = E0 - (2.0 * sum(S))
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77 rmsd = npy.sqrt(abs(rmsd / len(ref[refmask]))) #get the rmsd
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78 #U is simply V*Wt
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79 U = npy.dot(V, Wt) #get the rotation matrix
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80 # rotate and translate the molecule
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81 new_coords = npy.dot((refCenteredCoords), U)+ target_centroid #translate & rotate
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82 #new_coords=(refCenteredCoords + target_centroid)
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83 #print U
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84 if returnRotMat :
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85 return U, ref_centroid, target_centroid, rmsd
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86 return new_coords,rmsd
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87
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88
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89 def squared_distance(coordsA, coordsB):
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90 """Find the squared distance between two 3-tuples"""
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91 sqrdist = sum( (a-b)**2 for a, b in zip(coordsA, coordsB) )
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92 return sqrdist
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93
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94 def rmsd(allcoordsA, allcoordsB):
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95 """Find the RMSD between two lists of 3-tuples"""
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96 deviation = sum(squared_distance(atomA, atomB) for
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97 (atomA, atomB) in zip(allcoordsA, allcoordsB))
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98 return math.sqrt(deviation / float(len(allcoordsA)))
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99
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100 def mapToCrystal(xtal, pose):
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101 """Some docking programs might alter the order of the atoms in the output (like Autodock Vina does...)
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102 this will mess up the rmsd calculation with OpenBabel"""
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103 query = pybel.ob.CompileMoleculeQuery(xtal.OBMol)
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104 mapper=pybel.ob.OBIsomorphismMapper.GetInstance(query)
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105 mappingpose = pybel.ob.vvpairUIntUInt()
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106 exit=mapper.MapUnique(pose.OBMol,mappingpose)
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107 return mappingpose[0]
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108
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109 def takeCoords(obmol):
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110 """Take coordinates of an OBMol as a npy array"""
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111 return npy.array([atom.coords for atom in obmol])
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112
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113 def updateCoords(obmol, newcoords):
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114 "Update OBMol coordinates. newcoords is a numpy array"
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115 for i,atom in enumerate(obmol):
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116 atom.OBAtom.SetVector(*newcoords[i])
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117
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118 def prepareAtomString(idlist):
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119 s = ""
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120 n = len(idlist)
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121 for i, id in enumerate(idlist):
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122 s += "%i"%id
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123 if (i+1) == n: s+="\n"
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124 elif (i+1)%35 == 0: s+=",\n"
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125 else: s+=","
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126 return s
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127
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128
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129 if __name__ == "__main__":
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130 import sys
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131
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132 if len(sys.argv) != 5:
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133 sys.exit("USAGE: %s reference.sdf input.sdf output.sdf 'SMARTS'"%sys.argv[0])
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134
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135 refsdf = sys.argv[1]
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136 molsdf = sys.argv[2]
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137 outsdf = sys.argv[3]
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138 smarts = pybel.Smarts(sys.argv[4])
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139
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140 # Read reference pose and get atom list matching smarts query
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141 # if more than 1 match, take the first one
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142 ref = next(pybel.readfile("sdf", refsdf))
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143 refMatchIds = smarts.findall(ref)
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144 numRefMatchs = len(refMatchIds)
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145
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146 if not numRefMatchs:
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147 sys.exit("No match found in the reference structure and the SMARTS string given. Please check it.")
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148
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149 if numRefMatchs > 1:
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150 print "More than one match in the reference molecule for the SMARTS string given. Will tether each input molecule all possible ways."
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151
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152 refIndxPerMatch = [npy.array(rmi) - 1 for rmi in refMatchIds]
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153
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154 # Take coordinates for the reference matched atoms
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155 refCoords = takeCoords(ref)
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156 refMatchCoords = [npy.take(refCoords, refIndx, axis=0) for refIndx in refIndxPerMatch]
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157
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158 # Do the same for molecule in molsdf
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159 out=pybel.Outputfile('sdf', outsdf, overwrite=True)
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160 molSupp = pybel.readfile("sdf", molsdf)
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161 ff = pybel.ob.OBForceField_FindForceField('MMFF94')
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162 for i,mol in enumerate(molSupp):
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163 print "## Molecule %i"%(i+1),
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164 mol.OBMol.DeleteNonPolarHydrogens()
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165 molMatchAllIds = smarts.findall(mol)
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166 numMatchs = len(molMatchAllIds)
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167
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168 if numMatchs == 0:
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169 print "No_Match",
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170 continue
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171 elif numMatchs ==1:
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172 print "Match",
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173 elif numMatchs > 1:
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174 print "Multiple_Match SMART Matches for this molecule (%d)"%numMatchs,
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175
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176 # If more than one match, write an output of the same molecule for each match
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177 # Start a default bestcoord and rmsd for later looping for each pose
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178 bestCoordPerMatch = [[0 for i in range(numMatchs)] for i in range(numRefMatchs)]
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179 bestRMSPerMatch = [[999 for i in range(numMatchs)] for i in range(numRefMatchs)]
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180
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181 # Will do a randomrotorsearch to find conformer with the lower rmsd when superposing
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182 # At least 20 when possible
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183 #ff.Setup(mol.OBMol)
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184 #numats = mol.OBMol.NumAtoms()
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185 #numrot = mol.OBMol.NumRotors()
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186 #print "Atoms: %i, Rotors: %i"%(numats, numrot)
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187 #geomopt = 300
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188 #genconf = 100
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189 # increase iterations if bigger molecule or bigger number of rotatable bonds
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190 # for allowing better sampling
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191 #if numats > 40 and numrot > 5:
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192 # geomopt = 300
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193 # genconf = 150
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194 #if numats > 55 and numrot > 7:
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195 # genconf = 100
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196 # geomopt = 500
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197 #print "\tDoing conformational search with WeightedRotorSearch (%i, %i)..."%(genconf, geomopt),
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198 #ff.SteepestDescent(500, 1.0e-4)
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199 #ff.WeightedRotorSearch(genconf,geomopt)
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200 #ff.ConjugateGradients(500, 1.0e-6)
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201 #ff.GetConformers(mol.OBMol)
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202 #numconf = mol.OBMol.NumConformers()
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203 numconf = 1
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204 #print "%i conformers generated"%numconf
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205 if numconf > 1:
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206 # Doing conf search
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207 #for i in range(numconf):
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208 # mol.OBMol.SetConformer(i)
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209 # confCoords = takeCoords(mol)
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210 # print 'coord:',confCoords[0,:]
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211 #
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212 # for imatch, molMatchIds in enumerate(molMatchAllIds):
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213 # molMatchIndx = npy.array(molMatchIds) - 1
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214 # confMatchCoords = npy.take(confCoords, molMatchIndx, axis=0)
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215 #
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216 # # Align: Get rotation matrix between the two sets of coords
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217 # # Apply rotation to the whole target molecule
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218 # rotMat, targetCentroid, refCentroid, rmsd = superpose3D(confMatchCoords, refMatchCoords, returnRotMat=True)
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219 # if rmsd < bestRMSPerMatch[imatch]:
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220 # newcoords = npy.dot((confCoords - targetCentroid), rotMat) + refCentroid
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221 # bestRMSPerMatch[imatch] = rmsd
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222 # bestCoordPerMatch[imatch] = newcoords
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223 # #if bestrms < 0.01: break
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224 pass
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225 else:
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226 molCoords = takeCoords(mol)
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227 for imatch, molMatchIds in enumerate(molMatchAllIds):
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228 # loop in each matching way for the input molecule
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229 molMatchIndx = npy.array(molMatchIds) - 1
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230 molMatchCoords = npy.take(molCoords, molMatchIndx, axis=0)
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231
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232 # Loop over the reference matches
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233 # Align: Get rotation matrix between the two sets of coords
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234 # Apply rotation to the whole target molecule
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235 for ir, refMatchCoord in enumerate(refMatchCoords):
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236 rotMat, targetCentroid, refCentroid, rmsd = superpose3D(molMatchCoords, refMatchCoord, returnRotMat=True)
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237 if rmsd < bestRMSPerMatch[ir][imatch]:
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238 newcoords = npy.dot((molCoords - targetCentroid), rotMat) + refCentroid
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239 bestRMSPerMatch[ir][imatch] = rmsd
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240 bestCoordPerMatch[ir][imatch] = newcoords
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241
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242 # Finally update molecule coordinates with the best matching coordinates found
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243 # change molecule coordinates, set TETHERED ATOMS property and save
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244 for imatch in range(numMatchs):
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245 for irefmatch in range(numRefMatchs):
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246 bestCoord = bestCoordPerMatch[irefmatch][imatch]
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247 bestRMS = bestRMSPerMatch[irefmatch][imatch]
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248 print "\tBest RMSD reached (match %d, refmatch %d): %s"%(imatch, irefmatch, bestRMS)
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249 molMatchID = molMatchAllIds[imatch]
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250 updateCoords(mol, bestCoord)
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251 newData = pybel.ob.OBPairData()
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252 newData.SetAttribute("TETHERED ATOMS")
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253 newData.SetValue(prepareAtomString(molMatchID))
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254
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255 mol.OBMol.DeleteData("TETHERED ATOMS") # Remove Previous DATA
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256 mol.OBMol.CloneData(newData) # Add new data
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257 out.write(mol)
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258
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259 out.close()
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260
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261 print "DONE"
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262 sys.stdout.close()
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263 sys.stderr.close()