The Graph Grammar Library - a generic framework for chemical graph rewrite systems

TL;DR

The Graph Grammar Library (GGL) provides a modular, high-performance framework for modeling chemical reactions using graph rewrite systems, enabling detailed cheminformatics studies at a molecular level.

Contribution

It introduces a generic, efficient graph rewrite system framework tailored for chemical modeling, with extensive cheminformatics features and enzyme reaction rules.

Findings

Supports detailed chemical reaction modeling

Includes rewrite rules for KEGG enzymes

Offers advanced cheminformatics algorithms

Abstract

Graph rewrite systems are powerful tools to model and study complex problems in various fields of research. Their successful application to chemical reaction modelling on a molecular level was shown but no appropriate and simple system is available at the moment. The presented Graph Grammar Library (GGL) implements a generic Double Push Out approach for general graph rewrite systems. The framework focuses on a high level of modularity as well as high performance, using state-of-the-art algorithms and data structures, and comes with extensive documentation. The large GGL chemistry module enables extensive and detailed studies of chemical systems. It well meets the requirements and abilities envisioned by Yadav et al. (2004) for such chemical rewrite systems. Here, molecules are represented as undirected labeled graphs while chemical reactions are described by according graph grammar rules. Beside the graph transformation, the GGL offers advanced cheminformatics algorithms for instance to estimate energies ofmolecules or aromaticity perception. These features are illustrated using a set of reactions from polyketide chemistry a huge class of natural compounds of medical relevance. The graph grammar based simulation of chemical reactions offered by the GGL is a powerful tool for extensive cheminformatics studies on a molecular level. The GGL already provides rewrite rules for all enzymes listed in the KEGG LIGAND database is freely available at http://www.tbi.univie.ac.at/software/GGL/.