The Gated Quantum Resonator: An Evolved Bayesian Engine for Chemo-Mechanical Catalysis

The extraordinary catalytic power of enzymes presents a fundamental challenge to the classical, equilibrium-based theories of Michaelis-Menten, Marcus, Warshel, and Koshland. While these frame- works provide an indispensable description of macroscopic, statistical behavior, they struggle to ac- count for the speed and precision of a single catalytic event, which occurs on a non-equilibrium, femtosecond timescale. To reconcile these scales, this paper introduces the Gated Quantum Res- onator (GQR) model, a new framework describing enzymes not as passive scaffolds, but as active, far-from-equilibrium quantum engines that function as evolved Bayesian computers. We posit that the enzyme is a non-equilibrium information processor that leverages allosteric gating to create a low-noise resonant cavity, where energy, in the form of a Davydov soliton, is trapped and discharged in a Quantum Lightning event. This microscopic, non-equilibrium model aims to provide a physical basis for the emergent parameters of the classical frameworks. We first present the complete multi- scale theory, then provide detailed case studies of FAD and the Oxygen-Evolving Complex (OEC), propose a clear roadmap for the model’s validation, and show how this view can be scaled up through the formal analogy between molecular kinetics and analog electronic circuits.