Welcome to SyGMa’s documentation!¶
Contents:
Introduction¶
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¶
import sygma
from rdkit import Chem
def test_predict_phenol_metabolites():
"""Test prediction of phenol metabolites by sygma module"""
# 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()
metabolite_list = metabolic_tree.to_list()
assert len(metabolite_list) == 12
assert metabolite_list[0]['SyGMa_score'] == 1
assert metabolite_list[1]['SyGMa_pathway'] == 'O-glucuronidation_(aromatic_hydroxyl); \n'
Rulesets¶
SyGMa comes currently with two rulesets:
- phase1
- Phase 1 metabolism rules include mainly different types of oxidation, hydrolysis, reduction and condensation reactions
- phase2
- Phase 2 metabolism rules include severaly conjugation reaction, i.e. with glucuronyl, sulfate, methyl and acetyl