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Systematic Generation of potential MetAbolites

Project Description

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.


SyGMa requires RDKit with INCHI support


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



  • pip install sygma OR, after downloading sygma, python 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 =

print metabolic_tree.to_smiles()


SyGMa can be executed in a Docker ( container as follows:

docker run 3dechem/sygma c1ccccc1O
Release History

Release History

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
SyGMa-1.1.0.tar.gz (13.8 kB) Copy SHA256 Checksum SHA256 Source Feb 7, 2017

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