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sascorer.py
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sascorer.py
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#
# calculation of synthetic accessibility score as described in:
#
# Estimation of Synthetic Accessibility Score of Drug-like Molecules based on Molecular Complexity and Fragment Contributions
# Peter Ertl and Ansgar Schuffenhauer
# Journal of Cheminformatics 1:8 (2009)
# http://www.jcheminf.com/content/1/1/8
#
# several small modifications to the original paper are included
# particularly slightly different formula for marocyclic penalty
# and taking into account also molecule symmetry (fingerprint density)
#
# for a set of 10k diverse molecules the agreement between the original method
# as implemented in PipelinePilot and this implementation is r2 = 0.97
#
# peter ertl & greg landrum, september 2013
#
from __future__ import print_function
from rdkit import Chem
from rdkit.Chem import rdMolDescriptors
from rdkit.six.moves import cPickle
from rdkit.six import iteritems
import math
from collections import defaultdict
import os.path as op
_fscores = None
def readFragmentScores(name='fpscores'):
import gzip
global _fscores
# generate the full path filename:
if name == "fpscores":
name = op.join(op.dirname(__file__), name)
_fscores = cPickle.load(gzip.open('%s.pkl.gz'%name))
outDict = {}
for i in _fscores:
for j in range(1,len(i)):
outDict[i[j]] = float(i[0])
_fscores = outDict
def numBridgeheadsAndSpiro(mol,ri=None):
nSpiro = rdMolDescriptors.CalcNumSpiroAtoms(mol)
nBridgehead = rdMolDescriptors.CalcNumBridgeheadAtoms(mol)
return nBridgehead,nSpiro
def calculateScore(m):
if _fscores is None: readFragmentScores()
# fragment score
fp = rdMolDescriptors.GetMorganFingerprint(m,2) #<- 2 is the *radius* of the circular fingerprint
fps = fp.GetNonzeroElements()
score1 = 0.
nf = 0
for bitId,v in iteritems(fps):
nf += v
sfp = bitId
score1 += _fscores.get(sfp,-4)*v
score1 /= nf
# features score
nAtoms = m.GetNumAtoms()
nChiralCenters = len(Chem.FindMolChiralCenters(m,includeUnassigned=True))
ri = m.GetRingInfo()
nBridgeheads,nSpiro=numBridgeheadsAndSpiro(m,ri)
nMacrocycles=0
for x in ri.AtomRings():
if len(x)>8: nMacrocycles+=1
sizePenalty = nAtoms**1.005 - nAtoms
stereoPenalty = math.log10(nChiralCenters+1)
spiroPenalty = math.log10(nSpiro+1)
bridgePenalty = math.log10(nBridgeheads+1)
macrocyclePenalty = 0.
# ---------------------------------------
# This differs from the paper, which defines:
# macrocyclePenalty = math.log10(nMacrocycles+1)
# This form generates better results when 2 or more macrocycles are present
if nMacrocycles > 0: macrocyclePenalty = math.log10(2)
score2 = 0. -sizePenalty -stereoPenalty -spiroPenalty -bridgePenalty -macrocyclePenalty
# correction for the fingerprint density
# not in the original publication, added in version 1.1
# to make highly symmetrical molecules easier to synthetise
score3 = 0.
if nAtoms > len(fps):
score3 = math.log(float(nAtoms) / len(fps)) * .5
sascore = score1 + score2 + score3
# need to transform "raw" value into scale between 1 and 10
min = -4.0
max = 2.5
sascore = 11. - (sascore - min + 1) / (max - min) * 9.
# smooth the 10-end
if sascore > 8.: sascore = 8. + math.log(sascore+1.-9.)
if sascore > 10.: sascore = 10.0
elif sascore < 1.: sascore = 1.0
return sascore
def processMols(mols):
print('smiles\tName\tsa_score')
for i,m in enumerate(mols):
if m is None:
continue
s = calculateScore(m)
smiles = Chem.MolToSmiles(m)
print(smiles+"\t"+m.GetProp('_Name') + "\t%3f"%s)
if __name__=='__main__':
import sys,time
t1=time.time()
readFragmentScores("fpscores")
t2=time.time()
suppl = Chem.SmilesMolSupplier(sys.argv[1])
t3=time.time()
processMols(suppl)
t4=time.time()
print('Reading took %.2f seconds. Calculating took %.2f seconds'%((t2-t1),(t4-t3)), file=sys.stderr)
#
# Copyright (c) 2013, Novartis Institutes for BioMedical Research Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following
# disclaimer in the documentation and/or other materials provided
# with the distribution.
# * Neither the name of Novartis Institutes for BioMedical Research Inc.
# nor the names of its contributors may be used to endorse or promote
# products derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#