In [1]:

    

from rdkit import Chem
from rdkit.Chem.Draw import IPythonConsole
from rdkit.Chem import Draw
from rdkit.Chem import MACCSkeys
import numpy as np


    

    




/usr/lib/python2.7/site-packages/IPython/html.py:14: ShimWarning: The `IPython.html` package has been deprecated. You should import from `notebook` instead. `IPython.html.widgets` has moved to `ipywidgets`.
  "`IPython.html.widgets` has moved to `ipywidgets`.", ShimWarning)

In [2]:

    

mol1 = Chem.MolFromSmiles('COc1cc2c(cc1OCCCN3CCOCC3)c(ncn2)Nc4ccc(c(c4)Cl)F')


    

In [3]:

    

mol2 = Chem.MolFromSmiles('COCCOc1cc2c(cc1OCCOC)ncnc2Nc3cccc(c3)C#C')


    

In [4]:

    

mol1


    

    
Out[4]:

In [5]:

    

Draw.MolsToGridImage([mol1,mol2])


    

    
Out[5]:

In [6]:

    

fp1 = MACCSkeys.GenMACCSKeys(mol1)
fp2 = MACCSkeys.GenMACCSKeys(mol2)


    

In [7]:

    

fp1.ToBitString()


    

    
Out[7]:





'00000000000000000000000000000000000000100010000000000000010000000100000010010100100001110000010101101101010101010100001011100111110011110110001111111011110111111111110'

In [8]:

    

fp2.ToBitString()


    

    
Out[8]:





'00000000000000000100000000000000000000100000000000000000000000000100000010000100100000100000010001100100010001000101101011000111000011010110101111110111110111111111110'

In [9]:

    

fp_a1 = np.array(map(int, fp1.ToBitString()))
fp_a2 = np.array(map(int, fp2.ToBitString()))


    

In [10]:

    

from scipy.spatial.distance import dice


    

In [11]:

    

dice(fp_a1, fp_a2)


    

    
Out[11]:





0.18181818181818182

In [12]:

    

1 - dice(fp_a1, fp_a2)


    

    
Out[12]:





0.8181818181818181

In [13]:

    

from rdkit.Chem.Draw import SimilarityMaps


    

In [14]:

    

%matplotlib inline


    

In [15]:

    

fig, maxweight = SimilarityMaps.GetSimilarityMapForFingerprint(mol1, mol2, SimilarityMaps.GetMorganFingerprint)


    

In [ ]:

    




    

In [16]:

    

from rdkit.Chem import PandasTools


    

In [17]:

    

import pandas as pd


    

In [18]:

    

df = PandasTools.LoadSDF('../data/test.sdf')


    

In [19]:

    

df.head(1)


    

    
Out[19]:





  

    

      

      
ID
      
ROMol
      
logp
      
mw
    
  
  

    

      
0
      
DB01322
      

      
2.6648
      
232.278994301
    
  

In [20]:

    

from rdkit.Chem import Descriptors


    

In [21]:

    

df['HAC'] = df['ROMol'].map(Descriptors.HeavyAtomCount)
df['HBD'] = df['ROMol'].map(Descriptors.NumHDonors)


    

In [22]:

    

df.head(1)


    

    
Out[22]:





  

    

      

      
ID
      
ROMol
      
logp
      
mw
      
HAC
      
HBD
    
  
  

    

      
0
      
DB01322
      

      
2.6648
      
232.278994301
      
17
      
0
    
  

In [23]:

    

df['HAC'].head(5) > 15


    

    
Out[23]:





0     True
1     True
2    False
3     True
4    False
Name: HAC, dtype: bool

In [24]:

    

df[(df['HAC'] > 22) & df['HBD'] == 1]


    

    
Out[24]:





  

    

      

      
ID
      
ROMol
      
logp
      
mw
      
HAC
      
HBD
    
  
  

    

      
11
      
DB01466
      

      
1.8912
      
313.396992668
      
23
      
1
    
    

      
23
      
DB01505
      

      
1.5922
      
321.416992584
      
23
      
1
    
    

      
48
      
DB01568
      

      
1.5137
      
315.368992584
      
23
      
1
    
    

      
53
      
DB04829
      

      
2.906
      
323.439993095
      
24
      
1
    
    

      
72
      
DB01333
      

      
0.3486
      
349.411994507
      
24
      
3
    
  

In [ ]:

    




    

In [25]:

    

from ipywidgets import interact, fixed
from IPython.display import display


    

In [26]:

    

def show_frame(df, sort_by, ascending=True, num=2):
    display(df.sort_values(sort_by, ascending=ascending).head(num))


    

In [27]:

    

show_frame(df, 'logp')


    

    






  

    

      

      
ID
      
ROMol
      
logp
      
mw
      
HAC
      
HBD
    
  
  

    

      
29
      
DB01525
      

      
-0.0854
      
185.222995872
      
13
      
2
    
    

      
56
      
DB00529
      

      
-0.1579
      
126.003998589
      
7
      
3
    
  

In [28]:

    

interact(show_frame, df=fixed(df), sort_by={'HAC':'HAC', 'HBD':'HBD'}, num=[1,3])


    

    






  

    

      

      
ID
      
ROMol
      
logp
      
mw
      
HAC
      
HBD
    
  
  

    

      
0
      
DB01322
      

      
2.6648
      
232.278994301
      
17
      
0
    
    

      
52
      
DB01579
      

      
2.0782
      
191.27399572
      
14
      
0
    
  







    
Out[28]:





<function __main__.show_frame>

In [ ]: