Inferring Chemical Reaction Patterns Using Rule Composition in Graph Grammars
Jakob L. Andersen, Christoph Flamm, Daniel Merkle, Peter F. Stadler

TL;DR
This paper introduces a method to automatically infer complex chemical reaction patterns by composing graph grammar rules, aiding the analysis of catalytic cycles, polymerization, and iterative reactions in chemistry.
Contribution
It presents a generic approach for composing graph grammar rules to automatically identify complex reaction patterns in chemical systems.
Findings
Successfully inferred the overall pattern of the Formose reaction cycle
Applied rule composition to study polymerization reactions
Demonstrated the method's utility in analyzing complex iterative schemes
Abstract
Modeling molecules as undirected graphs and chemical reactions as graph rewriting operations is a natural and convenient approach tom odeling 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. We use 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. This is useful for instance to understand the net effect of complex catalytic cycles such as the Formose reaction. The automatically inferred graph grammar rule is a generic representative that also…
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Taxonomy
TopicsModel-Driven Software Engineering Techniques · Semantic Web and Ontologies · Software Engineering Research
