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In silico bioprospecting of enzymatic PEF synthesis and degradation
Summary
This computational study searched protein databases for enzymes capable of synthesizing and breaking down PEF, a bio-based plastic alternative to PET, using Monte Carlo simulations to identify promising enzyme-substrate combinations. The research is relevant to microplastics because finding effective biodegradation pathways for plastics like PEF could reduce the long-term accumulation of plastic debris and microplastics in the environment.
Plastic waste accumulation is an urgent problem. Vast islands of accumulated plastic and microplastics spread endanger many ecosystems and are an imminent health threat to human populations [1]. Greener alternatives are being searched to fight against this environmental problem, including refining the recycling processes and searching for other options to fossil-based plastics. Poly(ethylene-2,5-furandi-carboxylate) (PEF) is a biopolymer structurally similar to poly(ethylene terephthalate) (PET), a widely used petroleum-derived polymeric plastic. Compared to PET, PEF has shown improved mechanical properties, reduced oxygen permeability, and a higher glass transition temperature, among other properties [2]. However, its extensive use has yet to be adopted because of the cost associated with PEF synthesis and a still unclear degradation strategy. The former could be solved by improving the synthesis of 2,5-Furandicarboxylic acid (FDCA), the monomeric building block, while the latter by finding or improving enzymes for an effective depolymerization reaction. We searched the available protein sequence and structural databases to find new enzymatic activities for the synthesis of FDCA and PEF degradation. We devised a vast computational bioprospecting strategy based on Monte Carlo simulations to uncover the interaction energy landscapes underlying the different enzyme and substrate combinations. This experiment revealed many uncharacterized enzymes showing good substrate affinity for reactive configurations and active site preorganization. Preliminary experimental results suggest that such a computational search can enormously narrow the experimental efforts when searching for enzymes able to act over novel chemical reactions.