In Indian journal of microbiology
The large-scale usage of petro-chemical-based plastics has proved to be a significant source of environmental pollution due to their non-biodegradable nature. Microbes-based enzymes such as esterases, cutinases, and lipases have shown the ability to degrade synthetic plastic. However, the degradation of plastics by enzymes is primarily limited by the unavailability of a robust enzymatic system, i.e., low activity and stability towards plastic degradation. Recently, the machine learning strategy involved structure-based and deep neural networks show desirable potential to generate functional, active stable, and tolerant polyethylene terephthalate (PET) degrading enzyme (FAST-PETase). FAST-PETase showed the highest PET hydrolytic activity among known enzymes or their variants and degraded broad ranges of plastics. The development of a closed-loop circular economy-based system of plastic degradation to monomers by FAST-PETase followed by the re-polymerization of monomers into clean plastics can be a more sustainable approach. As an alternative to synthetic plastics, diverse microbes can produce polyhydroxyalkanoates, and their degradation by microbes has been well-established. This article discusses recent updates in the enzymatic degradation of plastics for sustainable development.
Patel Sanjay K S, Lee Jung-Kul
2022-Dec
Bio-degradation process, Machine learning strategy, Plastic degrading enzyme, Polyhydroxyalkanoates, Synthetic plastic
