ArticlebioRxiv : the preprint server for biology2026
Model-based inference of enzyme inhibitions from perturbation-induced metabolic dynamics.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
In microbes, metabolism plays a key role in the first rapid adaptation to sudden challenges such as nutrient limitations or toxic compounds. While metabolomics enables the profiling of stimuli-induced metabolic changes, computational approaches that can interpret these data to mechanistically explain how perturbations propagate through metabolism to produce the observed changes are lagging behind. Here, we developed a computational framework, called Inference from Metabolic Fingerprints (IMF), to model the immediate dynamic response to a metabolic perturbation and systematically infer its entry point (i.e. enzymatic target). IMF assumes small perturbations and linearizes the nonlinear dynamics around a reference steady state. This allows IMF to scale with large metabolic networks and bypass missing kinetic parameters by allowing for fast and efficient ensemble sampling. We apply IMF to a model of central metabolism in
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