Source code for geary
# -*- coding: utf-8 -*-
# Copyright (c) 2016-2017, Zhijiang Yao, Jie Dong and Dongsheng Cao
# All rights reserved.
# This file is part of the PyBioMed.
# The contents are covered by the terms of the BSD license
# which is included in the file license.txt, found at the root
# of the PyBioMed source tree.
"""
##############################################################################
The calculation of Geary autocorrelation indices based on its topological
structure. You can get 32 molecular autocorrelation descriptors. You can
freely use and distribute it. If you hava any problem, you could contact
with us timely!
Authors: Zhijiang Yao and Dongsheng Cao.
Date: 2016.06.04
Email: gadsby@163.com and oriental-cds@163.com
##############################################################################
"""
from rdkit import Chem
from AtomProperty import GetRelativeAtomicProperty
import numpy
Version=1.0
################################################################
def _CalculateGearyAutocorrelation(mol,lag=1,propertylabel='m'):
"""
#################################################################
**Internal used only**
Calculation of Geary autocorrelation descriptors based on
different property weights.
Usage:
res=_CalculateGearyAutocorrelation(mol,lag=1,propertylabel='m')
Input: mol is a molecule object.
lag is the topological distance between atom i and atom j.
propertylabel is the weighted property.
Output: res is a numeric value.
#################################################################
"""
Natom=mol.GetNumAtoms()
prolist=[]
for i in mol.GetAtoms():
temp=GetRelativeAtomicProperty(i.GetSymbol(),propertyname=propertylabel)
prolist.append(temp)
aveweight=sum(prolist)/Natom
tempp=[numpy.square(x-aveweight) for x in prolist]
GetDistanceMatrix=Chem.GetDistanceMatrix(mol)
res=0.0
index=0
for i in range(Natom):
for j in range(Natom):
if GetDistanceMatrix[i,j]==lag:
atom1=mol.GetAtomWithIdx(i)
atom2=mol.GetAtomWithIdx(j)
temp1=GetRelativeAtomicProperty(element=atom1.GetSymbol(),propertyname=propertylabel)
temp2=GetRelativeAtomicProperty(element=atom2.GetSymbol(),propertyname=propertylabel)
res=res+numpy.square(temp1-temp2)
index=index+1
else:
res=res+0.0
if sum(tempp)==0 or index==0:
result=0
else:
result=(res/index/2)/(sum(tempp)/(Natom-1))
return round(result,3)
[docs]def CalculateGearyAutoMass(mol):
"""
#################################################################
Calculation of Geary autocorrelation descriptors based on
carbon-scaled atomic mass.
Usage:
res=CalculateMoranAutoMass(mol)
Input: mol is a molecule object.
Output: res is a dict form containing eight geary autocorrealtion
descriptors.
#################################################################
"""
res={}
for i in range(8):
res['GATSm'+str(i+1)]=_CalculateGearyAutocorrelation(mol,lag=i+1,propertylabel='m')
return res
[docs]def CalculateGearyAutoVolume(mol):
"""
#################################################################
Calculation of Geary autocorrelation descriptors based on
carbon-scaled atomic van der Waals volume.
Usage:
res=CalculateGearyAutoVolume(mol)
Input: mol is a molecule object.
Output: res is a dict form containing eight geary autocorrealtion
descriptors.
#################################################################
"""
res={}
for i in range(8):
res['GATSv'+str(i+1)]=_CalculateGearyAutocorrelation(mol,lag=i+1,propertylabel='V')
return res
[docs]def CalculateGearyAutoElectronegativity(mol):
"""
#################################################################
Calculation of Geary autocorrelation descriptors based on
carbon-scaled atomic Sanderson electronegativity.
Usage:
res=CalculateGearyAutoElectronegativity(mol)
Input: mol is a molecule object.
Output: res is a dict form containing eight geary autocorrealtion
descriptors.
#################################################################
"""
res={}
for i in range(8):
res['GATSe'+str(i+1)]=_CalculateGearyAutocorrelation(mol,lag=i+1,propertylabel='En')
return res
[docs]def CalculateGearyAutoPolarizability(mol):
"""
#################################################################
Calculation of Geary autocorrelation descriptors based on
carbon-scaled atomic polarizability.
Usage:
res=CalculateGearyAutoPolarizability(mol)
Input: mol is a molecule object.
Output: res is a dict form containing eight geary autocorrealtion
descriptors.
#################################################################
"""
res={}
for i in range(8):
res['GATSp'+str(i+1)]=_CalculateGearyAutocorrelation(mol,lag=i+1,propertylabel='alapha')
return res
[docs]def GetGearyAuto(mol):
"""
#################################################################
Calcualate all Geary autocorrelation descriptors.
(carbon-scaled atomic mass, carbon-scaled atomic van der Waals volume,
carbon-scaled atomic Sanderson electronegativity,
carbon-scaled atomic polarizability)
Usage:
res=GetGearyAuto(mol)
Input: mol is a molecule object.
Output: res is a dict form containing all geary autocorrealtion
descriptors.
#################################################################
"""
res={}
res.update(CalculateGearyAutoMass(mol))
res.update(CalculateGearyAutoVolume(mol))
res.update(CalculateGearyAutoElectronegativity(mol))
res.update(CalculateGearyAutoPolarizability(mol))
return res
###########################################################################
if __name__=='__main__':
smi5=['COCCCC','CCC(C)CC','CC(C)CCC','CC(C)C(C)C','CCOCCN','c1ccccc1N']
smis = ['CCCC','CCCCC','CCCCCC','CC(N)C(=O)O','CC(N)C(=O)[O-].[Na+]']
for index, smi in enumerate(smis):
m = Chem.MolFromSmiles(smi)
print index+1
print smi
## print '\t',CalculateEstateFingerprint(m)
## print '\t',CalculateEstateValue(m)
## print '\t',CalculateMaxAtomTypeEState(m)
## print '\t', CalculateMinAtomTypeEState(m)
print GetGearyAuto(m)
