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
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Filename, size | File type | Python version | Upload date | Hashes |
---|---|---|---|---|
Filename, size SyGMa-1.1.0.tar.gz (13.8 kB) | File type Source | Python version None | Upload date | Hashes View |