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<p>Molecular simulations have become indispensable in biological research. Their accuracy continues to improve, but directly modelling biochemical reactions – central to all life processes – remains computationally challenging. Here, we present a biomolecular reaction emulator that models reactions across conformational ensembles using kinetic Monte Carlo. Our method, KIMMDY, is capable of handling dynamic, large-scale systems with successive, competing reactions, even on the second timescale or slower. It leverages graph neural networks for large-scale prediction of reaction rates, while also being capable of using simpler physics-based or heuristic models. We validate our approach against experimental data and showcase its power and versatility through a series of applications, including radical reactions, nucleophilic substitutions, and photodimerization. Example systems span proteins and DNA. KIMMDY aids the understanding of biochemical reaction cascades in complex systems, helps to re-interpret experimental data, and can inspire future wet-lab experiments.</p>

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KIMMDY: a biomolecular reaction emulator

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月14日

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  • Eric Hartmann,
  • Jannik Buhr,
  • Kai Riedmiller,
  • Evgeni Ulanov,
  • Boris N. Schüpp,
  • Denis Kiesewetter,
  • Daniel Sucerquia,
  • Camilo Aponte-Santamaría,
  • Frauke Gräter

摘要

Molecular simulations have become indispensable in biological research. Their accuracy continues to improve, but directly modelling biochemical reactions – central to all life processes – remains computationally challenging. Here, we present a biomolecular reaction emulator that models reactions across conformational ensembles using kinetic Monte Carlo. Our method, KIMMDY, is capable of handling dynamic, large-scale systems with successive, competing reactions, even on the second timescale or slower. It leverages graph neural networks for large-scale prediction of reaction rates, while also being capable of using simpler physics-based or heuristic models. We validate our approach against experimental data and showcase its power and versatility through a series of applications, including radical reactions, nucleophilic substitutions, and photodimerization. Example systems span proteins and DNA. KIMMDY aids the understanding of biochemical reaction cascades in complex systems, helps to re-interpret experimental data, and can inspire future wet-lab experiments.