bioRxiv: Generative and reasoning models elucidate small-molecule structures from NMR spectra

[bioRxiv] A preprint posted to bioRxiv describes an AI system for automated de novo structure elucidation that pairs a molecular generative model with a scientific reasoning agent. The generative component, ChefNMR2, is an atomic flow-matching model that predicts small-molecule structures from molecular formulae and one-dimensional 1H and 13C NMR spectra; ChefNMR2-Agent adds large language models to reason over and refine candidate structures. According to the authors, ChefNMR2 substantially outperforms existing tools across diverse benchmarks, offers calibrated confidence estimates and runs two to three orders of magnitude faster than frontier LLMs. The team said it used ChefNMR2-Agent to elucidate the structures of four novel natural products, matching human-chemist accuracy in a fraction of the time. The preprint has not been peer-reviewed.