Catalytic insights into laccase for sustainable remediation of multifaceted pharmaceutically active micropollutants from water matrices: A state-of-art review

Novel pharmaceuticals are continuously being brought into the market for the treatment of human ailments like inflammation, fever, bacterial infection, cardiovascular, cancers, and multidrug-resistant infectious diseases, etc. The overproduction and application of pharmaceuticals, along with their untreated or unmetabolized release into the environment, lead to the contamination of aquatic ecosystems, thereby posing a risk to both the sustainability of the environment and human health. Pharmaceutically active micropollutants (PhAMPs) and their metabolites are widely present in aquatic environments at concentrations ranging from ng/L to mu g/L. The impacts of PhAMPs in the aquatic environment are not limited to antibiotic resistance; they also have a substantial negative impact on aquatic species at low concentrations. The considerable removal and elimination of PhAMPs from wastewater is a challenging pursuit by conventional physicochemical processes, nevertheless can be accomplished efficiently in an eco-friendly way by employing a laccase-assisted biocatalytic system. Laccase has been used to cope with this challenging situation by way of cost-effective and environmentally friendly beneficial approaches for the degradation of multiple PhAMPs. This review highlights the crucial function of laccase-based biocatalytic systems in the eco-friendly remediation of multiple PhAMPs, including but not limited to analgesics/NSAIDs, anticancer drugs, antiepileptic drugs, beta-blockers, and antibiotics, etc. Additionally, an atomic-level computational investigation of Enzymes-PhAMPs have been delineated to comprehend laccase activity to facilitate mechanisms aimed to clean water. Furthermore, laccase may be implemented to fulfill the United Nations Sustainable Development Goal (UN-SDG) by ensuring universal and equitable access to safe and affordable drinking water for all.