Detection and degradation of phenolic pollutants using a highly effective and stable biomimetic laccase-mimicking Cys-Cu/NH₂-ZIF-8 nanozyme: Toxicity assessment and artificial neural network modeling

Laccases, oxidase enzymes containing multiple copper atoms, are important in biotechnology and environmental remediation. Owing to the inherent limitations of natural laccases, we prepared a highly effective laccase-like nanozyme by combining the supramolecular assembly of cysteine-copper with NH2-ZIF-8 (Cys-Cu/NH2-ZIF-8). Compared to natural laccase, the produced nanozyme exhibited lower Km (0.13mM) and Vmax (1.91× 10-5 mM.s-1) values, along with improved stability under various conditions, including extreme pH, high temperatures, and long-Term storage, conditions that typically reduce the efficacy of laccases. The prepared nanozyme was utilized to degrade and quantify various phenolic substances, including phenol, 1-naphthol, 2-Aminophenol, 2-nitrophenol, and 2,4-dichlorophenol. The bacterial toxicity assay of the degradation products was performed, and the findings indicated the formation of less toxic intermediates after the degradation of desired phenols. An artificial neural network (ANN) with a 4:7:1 topology was utilized to model the efficiency of degrading phenolic compounds. The results demonstrated that the developed ANN could successfully predict 2,4-dichlorophenol (as a phenolic pollutant model) removal. Furthermore, the synthesized laccase-like Cys-Cu/NH2-ZIF-8 was used to fabricate a smartphone-based digital image colorimetric sensor for dopamine detection, with a detection limit of 6.27μM and linearity in the range of 10-140μM. Cys-Cu/NH2-ZIF-8 could be a promising substitute for natural laccases in biotechnological applications, environmental protection, and biosensing.