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Quantum computing (QC) provides a promising avenue for enabling quantum chemistry calculations, which are classically impossible due to computational complexity that increases exponentially with system size. As fully fault-tolerant algorithms and hardware, for which an exponential speedup is predicted, are currently out of reach, recent research efforts have been dedicated to developing and scaling algorithms for Noisy Intermediate-Scale Quantum (NISQ) devices to showcase the practical usefulness of such machines. To demonstrate the usefulness of NISQ devices in the field of chemistry, we apply our recently developed FAST-VQE algorithm and a state-of-the-art quantum gate reduction strategy based on propositional satisfiability together with standard optimization tools for the simulation of the rate-determining proton transfer step for CO 2 hydration catalyzed by carbonic anhydrase resulting in the first application of a quantum computing device for the simulation of an enzymatic reaction. To this end, we have combined classical force field simulations with quantum mechanical methods on classical and quantum computers in a hybrid calculation approach. The presented technique significantly enhances the accuracy and capabilities of QC-based molecular modeling and finally pushes it into compelling and realistic applications. The framework is general and can be applied beyond the case of computational enzymology.
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Ettenhuber et al. (2025) studied this question.
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