If you are looking for something quick and dirty, you could stay in numpy
to calculate Tanimoto.
*from rdkit import Chem*
*from rdkit.Chem import AllChem*
*import numpy as np*
*from __future__ import division*
*mol1 = Chem.MolFromSmiles('CCO')*
*mol2 = Chem.MolFromSmiles('CCC')*
*fp1 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol1, 8),
dtype='bool')*
*fp2 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol2, 8),
dtype='bool')*
*def tanimoto(v1, v2):*
* """*
* Calculates tanimoto similarity for two bit vectors*
* """*
* return(np.bitwise_and(v1, v2).sum() / np.bitwise_or(v1, v2).sum())*
*tanimoto(fp1, fp2)*
*Out[4]:0.42857142857142855*
On Thu, Mar 16, 2017 at 7:28 AM, Thomas Evangelidis <teva...@gmail.com>
wrote:
> Hello,
>
> I created a numpyarray from a molecule using the following function:
>
> AllChem.GetMorganFingerprintAsBitVect()
>
>
> Now I would like to convert back to bit vector the numpy array, in order
> to calculate the Tanimoto similarity of two compounds. Is this possible?
>
> thanks
> Thomas
>
>
>
> --
>
> ======================================================================
>
> Thomas Evangelidis
>
> Research Specialist
> CEITEC - Central European Institute of Technology
> Masaryk University
> Kamenice 5/A35/1S081,
> 62500 Brno, Czech Republic
>
> email: tev...@pharm.uoa.gr
>
> teva...@gmail.com
>
>
> website: https://sites.google.com/site/thomasevangelidishomepage/
>
>
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