Source Code for Module Chem.Pharm2D.Generate

  1  # $Id: Generate.py 2 2006-05-06 22:54:39Z glandrum $ 
  2  # 
  3  # Copyright (C) 2002-2006 greg Landrum and Rational Discovery LLC 
  4  # 
  5  #   @@ All Rights Reserved  @@ 
  6  # 
  7  """ generation of 2D pharmacophores 
  8   
  9  **Notes** 
 10   
 11    - The terminology for this gets a bit rocky, so here's a glossary of what 
 12      terms used here mean: 
 13   
 14        1) *N-point pharmacophore* a combination of N features along with 
 15           distances betwen them. 
 16   
 17        2) *N-point proto-pharmacophore*: a combination of N feature 
 18           definitions without distances.  Each N-point 
 19           proto-pharmacophore defines a manifold of potential N-point 
 20           pharmacophores. 
 21   
 22        3) *N-point scaffold*: a collection of the distances defining 
 23           an N-point pharmacophore without feature identities. 
 24   
 25   
 26    See Docs/Chem/Pharm2D.triangles.jpg for an illustration of the way 
 27    pharmacophores are broken into triangles and labelled. 
 28   
 29    See Docs/Chem/Pharm2D.signatures.jpg for an illustration of bit 
 30    numbering 
 31   
 32  """ 
 33  from Chem.Pharm2D import Utils,Signature,SigFactory 
 34   
 35  _verbose = 0 
 36   
 37 -def _ShortestPathsMatch(match,featureSet,sig,dMat): 
 38    """  Internal use only 
 39   
 40    """ 
 41    if _verbose: 
 42      print 'match:',match 
 43    nPts = len(match) 
 44    distsToCheck =  Utils.nPointDistDict[nPts] 
 45    nDists = len(distsToCheck) 
 46    dist = [0]*nDists 
 47    #minD,maxD = sig.GetMinDist(),sig.GetMaxDist() 
 48    minD,maxD = sig.bins[0][0],sig.bins[-1][1] 
 49     
 50    for i in range(nDists): 
 51      pt0,pt1 = distsToCheck[i] 
 52      idx1,idx2 = match[pt0][0],match[pt1][0] 
 53      # FIX: treats all matches as single-atom 
 54      # FIX: is it ok that this is an int? 
 55      d = int(dMat[idx1,idx2]) 
 56      # do a quick distance filter 
 57      if d == 0 or d <= minD or d > maxD: 
 58        return 
 59      dist[i] = d 
 60    if _verbose: 
 61      print '\t',dist,sig.GetMinDist(),sig.GetMaxDist() 
 62    sig.SetBit(featureSet,dist,checkPatts=0) 
 63   
 64     
 65   
 66 -def Gen2DFingerprint(mol,sig,perms=None,dMat=None): 
 67    """ generates a 2D fingerprint for a molecule using the 
 68     parameters in _sig_ 
 69   
 70     **Arguments** 
 71   
 72       - mol: the molecule for which the signature should be generated 
 73   
 74       - sig: the signature object which will be filled. 
 75   
 76       - perms: (optional) a sequence of permutation indices limiting which 
 77         pharmacophore combinations are allowed 
 78   
 79       - dMat: (optional) the distance matrix to be used 
 80   
 81     **Notes**   
 82   
 83       - no preprocessing is carried out for _sig_. It *must* be pre-initialized. 
 84         Any bits which are already set will not be changed by this operation. 
 85   
 86      
 87    """ 
 88    if isinstance(sig,SigFactory.SigFactory): 
 89      sig = sig.GetSignature() 
 90    nPatts = sig.GetNumPatterns() 
 91    minCount = sig.GetMinCount() 
 92    maxCount = sig.GetMaxCount() 
 93   
 94    # generate the molecule's distance matrix, if required 
 95    if dMat is None: 
 96      import Chem 
 97      useBO = sig.GetIncludeBondOrder() 
 98      dMat = Chem.GetDistanceMatrix(mol,useBO) 
 99   
100    # generate the permutations, if required 
101    if perms is None: 
102      perms = [] 
103      for count in range(minCount,maxCount+1): 
104        perms += Utils.GetIndexCombinations(nPatts,count) 
105   
106    # generate the matches: 
107    pattMatches = [None]*nPatts 
108    for i in range(nPatts): 
109      patt = sig.GetPattern(i) 
110      pattMatches[i] = mol.GetSubstructMatches(patt) 
111   
112    for perm in perms: 
113      # the permutation is a combination of feature indices 
114      #   defining the feature set for a proto-pharmacophore 
115   
116      # Get a set of matches at each index of 
117      #  the proto-pharmacophore. 
118      matchPerms = [pattMatches[x] for x in perm] 
119      if _verbose: 
120        print '\n->Perm: %s'%(str(perm)) 
121        print '    matchPerms: %s'%(str(matchPerms)) 
122       
123      # Get all unique combinations of those possible matches: 
124      matchesToMap = Utils.UniquifyCombinations(Utils.GetAllCombinations(matchPerms)) 
125       
126      for match in matchesToMap: 
127        if sig.GetShortestPathsOnly(): 
128          _ShortestPathsMatch(match,perm,sig,dMat) 
129   
130    return sig 
131  if __name__ == '__main__': 
132    import Chem 
133 -  def test1(): 
134      sig = Signature.Pharm2DSig() 
135      sig.SetPatternsFromSmarts(['O','N']) 
136      sig.SetBins([(1,2),(2,4),(4,6)]) 
137      sig.SetMinCount(2) 
138      sig.SetMaxCount(3) 
139      sig.Init() 
140   
141      mol = Chem.MolFromSmiles('C1OCOCC1O') 
142      Gen2DFingerprint(mol,sig) 
143   
144      print list(sig.GetOnBits()) 
145      print sig._size 
146   
147 -  def test2(): 
148      sig = Signature.Pharm2DSig() 
149      sig.SetPatternsFromSmarts(['[OD1]','[OD2]','[CD3]',]) 
150      sig.SetBins([(1,3),(3,8)]) 
151      sig.SetMinCount(3) 
152      sig.SetMaxCount(3) 
153      sig.Init() 
154      mol = Chem.MolFromSmiles('OCCC1COCCO1') 
155      dMat= Chem.GetDistanceMatrix(mol) 
156   
157      #Signature._verbose = 1 
158      Gen2DFingerprint(mol,sig) 
159   
160      #print sig._binCombos 
161      print list(sig.GetOnBits()) 
162      print sig._size 
163    Signature._verbose=1 
164    _verbose = 1 
165    test1() 
166