Computational Study of a Versatile Lipase for the Degradation of Polylactic Acid

Biocatalysis is an emerging and sustainable approach
to depolymerize
highly hydrophobic plastic polyesters such as poly­(lactic acid) (PLA),
a bioplastic widely used in packaging and disposable items. Some enzymes,
including lipases, cutinases, and proteases, have been described to
hydrolyze PLA, but the activity strongly depends on stereochemistry
and crystallinity. In this study, we explored the activity of the
versatile lipase fromOphiostoma piceae (OPE) and three engineered variants (N81A, N94A, and N81/94A) on
polylactic acid (PLA), comparing the experimental data with predictions
from two computational methodologies, Thermal Titration Molecular
Dynamics (a classical method) and the machine learning-guided XLPFE
scoring function. Experimentally, mutant N81A showed the highest PLA
hydrolytic activity, followed by WT OPE, with N94A and N81/94A being
substantially less effective. This combined approach served to validate
the reliability of these computational strategies for predicting enzyme
interactions and highlights the importance of using long enough model
substrates to guide future enzyme optimization.