Alcohol oxidases (AOxs) catalyze the aerobic oxidation of alcohols to the corresponding carbonyl products (aldehydes or ketones), producing only H₂O₂ as the byproduct. The majority of known AOxs, however, have a strong preference for small, primary alcohols, limiting their broad applicability, e.g., in the food industry. To broaden the product scope of AOxs, we performed structure-guided enzyme engineering of a methanol oxidase from Phanerochaete chrysosporium (PcAOx). The substrate preference was extended from methanol to a broad range of benzylic alcohols by modifying the substrate binding pocket. A mutant (PcAOx-EFMH) with four substitutions exhibited improved catalytic activity toward benzyl alcohols with increased conversion and k_cat toward the benzyl alcohol from 11.3 to 88.9% and from 0.5 to 2.6 s^-1, respectively. The molecular basis for the change of substrate selectivity was analyzed by molecular simulation.

Although near-term quantum computing devices are still limited by the quantity and quality of qubits in the so-called NISQ era, quantum computational advantage has been experimentally demonstrated. Moreover, hybrid architectures of quantum and classical computing have become the main paradigm for exhibiting NISQ applications, where low-depth quantum circuits are repeatedly applied. In order to further scale up the problem size solvable by the NISQ devices, it is also possible to reduce the number of physical qubits by "cutting"the quantum circuit into different pieces. In this work, we experimentally demonstrated a circuit-cutting method for simulating quantum circuits involving many logical qubits, using only a few physical superconducting qubits. By exploiting the symmetry of linear-cluster states, we can estimate the effectiveness of circuit-cutting for simulating up to 33-qubit linear-cluster states, using at most 4 physical qubits for each subcircuit. Specifically, for the 12-qubit linear-cluster state, we found that the experimental fidelity bound can reach as much as 0.734, which is about 19% higher than a direct implementation on the same 12-qubit superconducting processor. Our results indicate that circuit-cutting represents a feasible approach of simulating quantum circuits using much fewer qubits, while achieving a much higher circuit fidelity.