A computational approach to optimising laccase-mediated polyethylene oxidation through carbohydrate-binding module...

Area of Science:

• Biotechnology
• Environmental Science
• Biochemistry

Background:

• Plastic pollution poses a significant threat to ecosystems and requires sustainable waste management solutions.
• Current microbial methods for plastic degradation face limitations due to slow oxidation rates.

Purpose of the Study:

• To optimize microbial enzymatic polyethylene oxidation by engineering laccase enzymes.
• To investigate the role of carbohydrate-binding modules (CBMs) in enhancing laccase activity towards polyethylene.

Main Methods:

• Bioinformatic screening of laccases and CBM domains.
• Molecular docking to simulate polyethylene binding.
• Deep learning algorithms to predict catalytic activity.
• Analysis of protein properties and interactions.

Main Results:

• Flexible GGGGS(x3) hinges improved putative polyethylene binding of laccases.
• CBM1 domains showed potential binding but hindered laccase-polyethylene associations.
• CBM2 domains demonstrated improved polyethylene binding, optimizing laccase oxidation.
• Hydrophobicity significantly influenced interactions between CBM domains, linkers, and polyethylene.

Conclusions:

• Engineered laccases with CBM2 domains offer a promising strategy for enhanced polyethylene oxidation.
• This study presents a rapid workflow for exoenzyme optimization and elucidates laccase-polyethylene interaction mechanisms.
• Optimized polyethylene oxidation is a critical step towards sustainable plastic bioremediation and complete breakdown.