KIMMDY: a biomolecular reaction emulator
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 acr...
Enregistré dans:
| Auteurs principaux: | , , , , , , , , |
|---|---|
| Format: | Article (Journal) |
| Langue: | anglais |
| Publié: |
2026
|
| In: |
Nature Communications
Year: 2026, Volume: 17, Pages: 1-10 |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-026-71955-2 |
| Accès en ligne: | Verlag, kostenfrei, Volltext: https://doi.org/10.1038/s41467-026-71955-2 Verlag, kostenfrei, Volltext: https://www.nature.com/articles/s41467-026-71955-2 
|
| Notes sur l'auteur: | Eric Hartmann, Jannik Buhr, Kai Riedmiller, Evgeni Ulanov, Boris N. Schüpp, Denis Kiesewetter, Daniel Sucerquia, Camilo Aponte-Santamaría & Frauke Gräter |
| Résumé: | 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. |
|---|---|
| Description: | Online veröffentlicht: 14. April 2026 Gesehen am 18.06.2026 |
| Description matérielle: | Online Resource |
| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-026-71955-2 |