A Computational Approach to Optimising Laccase-mediated Polyethylene Oxidation Through Carbohydrate-binding Module Fusion

Plastic pollution is a major global concern to the health and wellbeing of all terrestrial and marine life. However, no sustainable method for waste management is currently viable. This study addresses the optimisation of microbial enzymatic polyethylene oxidation through rational engineering of laccases with carbohydrate-binding module (CBM) domains. An explorative bioinformatic approach was taken for high-throughput screening of candidate laccases and CBM domains, representing an exemplar workflow for future engineering research. Molecular docking simulated polyethylene binding whilst a deep-learning algorithm predicted catalytic activity. Protein properties were examined to interpret the mechanisms behind laccase-polyethylene binding. The incorporation of flexible GGGGS(x3) hinges were found to improve putative polyethylene binding of laccases. Whilst CBM1 family domains were predicted to bind polyethylene, they were suggested to detriment laccase-polyethylene associations. In contrast, CBM2 domains reported improved polyethylene binding and may thus optimise laccase oxidation. Interactions between CBM domains, linkers, and polyethylene hydrocarbons were heavily reliant on hydrophobicity. Preliminary polyethylene oxidation is considered a necessity for consequent microbial uptake and assimilation. However, slow oxidation and depolymerisation rates inhibit the large-scale industrial implementation of bioremediation within waste management systems. The optimised polyethylene oxidation of CBM2-engineered laccases represents a significant advancement towards a sustainable method of complete plastic breakdown. Results of this study offer a rapid, accessible workflow for further research into exoenzyme optimisation whilst elucidating mechanisms behind the laccase-polyethylene interaction.