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A Web Tool for Generating High Quality Machine-readable Biological Pathways
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KIMMDY: a biomolecular reaction emulator
Eric Hartmann1,2, Jannik Buhr1,2, Kai Riedmiller1,2
1Heidelberg Institute for Theoretical Studies, Am Schloss-Wolfsbrunnenweg 35, Heidelberg, Germany.
Nature Communications
|April 14, 2026
Summary
We developed KIMMDY, a biomolecular reaction emulator using kinetic Monte Carlo and graph neural networks. This tool models complex biochemical reactions in large systems, improving our understanding of biological processes.
Area of Science:
- Computational Biology
- Biochemistry
- Molecular Dynamics
Background:
- Molecular simulations are crucial in biology but struggle with modeling biochemical reactions.
- Directly simulating biochemical reactions in large, dynamic systems is computationally intensive.
Purpose of the Study:
- To present KIMMDY, a novel biomolecular reaction emulator.
- To enable accurate modeling of biochemical reactions across conformational ensembles.
Main Methods:
- Utilizing kinetic Monte Carlo simulations.
- Employing graph neural networks for reaction rate prediction.
- Integrating physics-based or heuristic models.
Main Results:
- KIMMDY successfully models dynamic, large-scale systems with competing reactions.
- Validated against experimental data for radical reactions, nucleophilic substitutions, and photodimerization.
- Demonstrated versatility across protein and DNA systems.
Conclusions:
- KIMMDY enhances understanding of biochemical reaction cascades.
- Provides a tool for re-interpreting experimental data.
- Inspires future experimental investigations in molecular biology.
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