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.
Requirements
SyGMa requires RDKit with INCHI support
Installation
Install with Anaconda: conda install -c 3d-e-Chem -c rdkit sygma
OR
Install RDKit following the instructions in http://www.rdkit.org/docs/Install.html
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
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