A python library for prediction of drug metabolites
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README.rst

SyGMa

SyGMa is a python library for the Systematic Generation of potential Metabolites. It is a reimplementation of the metabolic rules outlined in Ridder, L., & Wagener, M. (2008) SyGMa: combining expert knowledge and empirical scoring in the prediction of metabolites. ChemMedChem, 3(5), 821-832.

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Requirements

SyGMa requires RDKit with INCHI support

Installation

  • Install with Anaconda: conda install -c 3d-e-Chem -c rdkit sygma

OR

AND

  • pip install sygma OR, after downloading sygma, python setup.py install

Example: generating metabolites of phenol

import sygma
from rdkit import Chem

# Each step in a scenario lists the ruleset and the number of reaction cycles to be applied
scenario = sygma.Scenario([
    [sygma.ruleset['phase1'], 1],
    [sygma.ruleset['phase2'], 1]])

# An rdkit molecule, optionally with 2D coordinates, is required as parent molecule
parent = Chem.MolFromSmiles("c1ccccc1O")

metabolic_tree = scenario.run(parent)
metabolic_tree.calc_scores()

print metabolic_tree.to_smiles()

Docker

SyGMa can be executed in a Docker (https://www.docker.com/) container as follows:

docker run 3dechem/sygma c1ccccc1O