Evolution of metabolic networks: a computational frame-work

Flamm, Christoph; Ullrich, Alexander; Ekker, Heinz; Mann, Martin; Högerl, Daniel; Rohrschneider, Markus; Sauer, Sebastian; Scheuermann, Gerik; Klemm, Konstantin; Hofacker, Ivo L.; Stadler, Peter F.

doi:10.1186/1759-2208-1-4

Cited by 17 publications

(19 citation statements)

References 78 publications

(79 reference statements)

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“…Such graph grammar rules have been successfully applied to model chemical reactions with molecular detail [6,19,35]. Therein, a graph grammar rule encodes the molecule graph transformations resulting from a chemical reaction as exemplified in Fig.…”

Section: Graph Grammars and Their Applications In Chemistrymentioning

confidence: 99%

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The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

Mann

Ekker

Flamm

2013

Theory and Practice of Model Transformations

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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/. BackgroundGraphs are powerful tools to represent and study all kind of data in any field of research. In order to generate graph structures of interest or to alter them according to some directive, graph transformations can be applied. A common approach is to formulate such transformations in terms of graph grammars or graph rewrite systems [5,7,37]. This enables a compact but very expressive representation of allowed alterations and allows for sound mathematical analyses of the problems [2,19].Here, we present our Graph Grammar Library (GGL), a fast and generic C++ framework to formulate and apply graph grammars. Beside the general graph rewrite system, we provide a specialized module to enable efficient graph grammar applications in chemical context. The power of such systems for chemical studies was highlighted by Yadav et al. [49] who emphasized the lack and need for an efficient implementation. The requirements and abilities sketched by Yadav et al. are well met by the capabilites of the GGL framework as presented within this manuscript.To represent molecules in graph notation is well known in chemistry and found in any text book. Therein, atoms are represented by labeled nodes in the graph and the connecting chemical bonds are depicted by according edges (see Fig. 1 a) and b)). Such molecule graphs can be used to model chemical reactions by the application of graph grammar rules as shown in Fig. 1 c) and d). This small example shows already the power of graph rewrite systems, since a single graph grammar rule encodes...

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Section: Graph Grammars and Their Applications In Chemistrymentioning

confidence: 99%

“…A common approach is to formulate such transformations in terms of graph grammars or graph rewrite systems [5,7,37]. This enables a compact but very expressive representation of allowed alterations and allows for sound mathematical analyses of the problems [2,19].…”

Section: Introductionmentioning

confidence: 99%

The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

Mann

Ekker

Flamm

2013

Theory and Practice of Model Transformations

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“…The implementation of the algorithm naturally depends heavily on the representation of transformation rules, which in our implementation is the representation from the Graph Grammar Library (GGL) [15]. The representation is a single graph, with attached vertex and edge properties defining membership of L, K and R, as well as the needed labels.…”

Section: Composing the Rulesmentioning

confidence: 99%

Inferring chemical reaction patterns using rule composition in graph grammars

et al. 2013

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Background: Modeling molecules as undirected graphs and chemical reactions as graph rewriting operations is a natural and convenient approach to modeling chemistry. Graph grammar rules are most naturally employed to model elementary reactions like merging, splitting, and isomerisation of molecules. It is often convenient, in particular in the analysis of larger systems, to summarize several subsequent reactions into a single composite chemical reaction.Results: We introduce a generic approach for composing graph grammar rules to define a chemically useful rule compositions. We iteratively apply these rule compositions to elementary transformations in order to automatically infer complex transformation patterns. As an application we automatically derive the overall reaction pattern of the Formose cycle, namely two carbonyl groups that can react with a bound glycolaldehyde to a second glycolaldehyde. Rule composition also can be used to study polymerization reactions as well as more complicated iterative reaction schemes. Terpenes and the polyketides, for instance, form two naturally occurring classes of compounds of utmost pharmaceutical interest that can be understood as "generalized polymers" consisting of five-carbon (isoprene) and two-carbon units, respectively. Conclusion: The framework of graph transformations provides a valuable set of tools to generate and investigate large networks of chemical networks. Within this formalism, rule composition is a canonical technique to obtain coarse-grained representations that reflect, in a natural way, "effective" reactions that are obtained by lumping together specific combinations of elementary reactions.

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“…Finally, genetic variation operators are applied to the genome (Step E in Figure 2). For a detailed discussion of the various steps of the computational model we refer the reader to Flamm et al (2010).…”

Section: Modelmentioning

confidence: 99%

“…Simulation approaches have shown to be useful in finding and challenging explanations for the evolution of biological networks (Pfeiffer et al, 2005). We have recently proposed a computational framework for the evolution of metabolism (Flamm et al, 2010), modeling all its significant components in a realistic way. In this report we discuss first results from several simulation runs.…”

Section: Introductionmentioning

confidence: 99%

In Silico Evolution of Early Metabolism

et al. 2011

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We developed a simulation tool for investigating the evolution of early metabolism, allowing us to speculate on the formation of metabolic pathways from catalyzed chemical reactions and development of characteristic properties. Our model consists of a protocellular entity with a simple RNA-based genetic system and an evolving metabolism of ribozymecatalyzed enzymes that manipulate a rich underlying chemistry.Ensuring an almost open-ended and fairly realistic simulation is crucial for understanding the first steps in metabolic evolution. We show here, how our simulation tool can be helpful in arguing for or against hypotheses on the evolution of metabolic pathways. We demonstrate that seemingly mutually exclusive hypotheses may well be compatible when we take into account that different processes dominate different phases in the evolution of a metabolic system. Our results suggest that forward evolution shapes metabolic network in the very early steps of evolution. In later and more complex stages, enzyme recruitment supersedes forward evolution, keeping a core set of pathways from the early phase.

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Evolution of metabolic networks: a computational frame-work

Cited by 17 publications

References 78 publications

The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

The Graph Grammar Library - A Generic Framework for Chemical Graph Rewrite Systems

Inferring chemical reaction patterns using rule composition in graph grammars

In Silico Evolution of Early Metabolism

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