Enzymes for Synthesis and Degradation of Bio‐Based Polyesters: Automatic In Silico Screening and Experimental Validation

This study intends to contribute to the rational eco-design of tailored new sustainable polymers with the aid of computational methods able to generate and screen new biocatalysts in silico for the synthesis or degradation of polyesters. Automatic computational workflows can be used for the rapid selection of enzymes that efficiently catalyze hydrolysis and/or synthesis of bio-based polyesters. Proteins and protein-ligand interactions were studied by integrating specific software for molecular dynamics simulations (Gromacs) and docking (AutoDock) into a workflow which also included some geometric evaluation of productive binding poses. Such a pipeline, based on successive calls to freely available and well-established software tools, was implemented in modeFRONTIER, a package equipped with a graphical user interface in which nodes, representing calls to external programs, are connected to form the sequential workflow. A series of bio-based monomers and enzymes was screened, and the computational results were correlated with experimental data obtained for the synthesis direction as well as with the data available for hydrolysis. The pipeline, by prioritizing and ranking molecules, enables the identification of optimal catalysts for both synthetic and hydrolytic reactions, emphasizing efficient prioritization and ranking strategies. The method was validated on a pool of 6 proteins and 20 substrates, and the predicted enzyme-substrate matches were subsequently compared with both the experimental synthesis and hydrolysis data, thereby confirming the reliability of the predictions. Overall, the results indicate that the hydrolytic and synthetic activity of enzymes toward polyesters can be rationally predicted by integrating different computational tools, providing a cost-effective alternative to time-consuming experimental screening.