Quantum computers may enable simulations of complex molecules that are otherwise unfeasible to simulate classically, meaning that chemical simulations may be one of the most promising applications for demonstrating a quantum advantage. At present, identifying chemical problems where one can reasonably expect a quantum advantage is difficult because both classical and quantum algorithms are continuously evolving. For example, current challenges in pinpointing such an application include identifying a problem that is currently impossible classically, and ideally will remain so in the future, as well as the fact that current estimates of the required quantum resources will continue to evolve.
With the goal of better understanding quantum advantage in chemical simulations, a recent study by Nicholas C. Rubin, Ryan Babbush and colleagues studied this problem in the context of cytochrome P450 enzymes (CYPs), which are biologically important for metabolic processes. Simulating CYPs classically is cost prohibitive, and optimizing the active species is particularly challenging because it is widely considered to be a ‘chameleon species’, meaning that it can easily change spin states depending on subtle structural changes in the protein. Further, the oxidation by CYPs involves a complex multistep catalytic cycle with at least eight intermediates, which is difficult to compute correctly, as a single intermediate can imply qualitative changes in the chemical behavior. The computationally expensive and finicky nature of CYPs makes them a promising application for taking advantage of quantum resources.
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