Skip to content

3D-e-Chem/sygma

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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.

https://travis-ci.org/3D-e-Chem/sygma.svg?branch=master https://api.codacy.com/project/badge/Grade/7f18ab1d1a80437f8e28ac1676c70519 https://api.codacy.com/project/badge/Coverage/7f18ab1d1a80437f8e28ac1676c70519

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

About

A python library for prediction of drug metabolites

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages