A la carte bioprospecting of substrate‐selective laccases via high‐throughput computational enzyme–substrate interaction profiling

Laccases are versatile, multicopper oxidases with broad biotechnological applications due to their ability to oxidize a wide range of substrates. Here, we introduce a computational pipeline that combines sequence filtering, Monte Carlo simulations, and quantum mechanical spin density calculations to identify laccase candidates tailored to specific substrates from large databases. Using methyl syringate as a proof of concept, we selected 37 laccase sequences for heterologous expression in Aspergillus oryzae. Of these, 21 were produced in soluble form, and 7 showed significant activity. Further kinetic and biochemical analysis identified two candidates, KAI0175247.1 and EPT01171.1, that outperformed a commercial Myceliophthora thermophila laccase (Mtl) in catalytic activity, while also displaying comparable or higher optimal temperatures. At 30°C, KAI0175247.1 and EPT01171.1 exhibited approximately 2.7- and 1.8-fold higher k_cat than Mtl, despite EPT01171.1 operating at only 2.8% of its maximum activity at this temperature. Substrate profiling also revealed that EPT01171.1 has broad substrate promiscuity and is likely a high-redox-potential laccase, while KAI0175247.1 shows high specificity for the target substrate and related compounds. These results confirm our targeted bioprospecting strategy and highlight promising laccase candidates for future applications as robust and sustainable biocatalysts.