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Pathfinder─Navigating and Analyzing Chemical Reaction Networks with an Efficient Graph-Based Approach
Paul L Türtscher1, Markus Reiher1
1Laboratory of Physical Chemistry, ETH Zurich, Vladimir-Prelog-Weg 2, 8093 Zurich, Switzerland.
Journal of Chemical Information and Modeling
|December 14, 2022
Summary
Pathfinder is a new algorithm for analyzing chemical reaction networks (CRNs). It uses graph theory and compound costs to rank compounds by formation probability, guiding exploration of complex chemical spaces.
Area of Science:
- Computational Chemistry
- Chemical Informatics
- Reaction Network Analysis
Background:
- First-principles exploration of chemical reaction space is expanding.
- Analysis of chemical reaction networks (CRNs) lags behind exploration.
- Kinetic modeling of compound transformations in CRNs is complex.
Purpose of the Study:
- To present Pathfinder, a graph-optimization-driven algorithm for CRN analysis.
- To enable efficient analysis of CRNs generated by computational methods.
- To provide a method for ranking compounds within a CRN based on formation probability.
Main Methods:
- Developed Pathfinder algorithm and software.
- Encoded CRNs as graphs with compound and reaction vertices.
- Introduced 'compound costs' to reflect reagent availability and compound formation probability.
- Utilized open-source Chemoton software for CRN generation.
Main Results:
- Pathfinder provides a graph-theoretical representation of CRNs.
- Compound costs effectively rank compounds by formation likelihood.
- Demonstrated Pathfinder on abstract and real chemical systems (iodine disproportionation/comproportionation).
Conclusions:
- Pathfinder facilitates efficient analysis of complex CRNs.
- Compound costs guide exploration towards more accessible compounds.
- Integrates CRN generation (Chemoton) and analysis (Pathfinder) for first-principles chemical exploration.
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