Computational design of Fusarium solani cutinase variants for efficient polylactide and polyethylene terephtalate...

Poly(lactic acid) (PLA) is among the most widely produced bioplastics worldwide and, given its limited biodegradability, sustainable solutions for its recycling are needed. The efficiency of enzymatic depolymerization depends on enzyme stability and activity under industrial conditions. This study focuses on engineering the cutinase from Fusarium solani (FsC), a promising enzyme for polyester hydrolysis, to enhance its thermostability and catalytic performance. Two computational strategies were employed: SCANEER, leveraging co-evolutionary analysis to optimize catalytic efficiency, and FireProt, integrating evolutionary and structural data to predict thermostabilizing mutations. The designed variants, FsC-sc (A32P/I55V) and FsC-fp (S54M/N106Y/S129A/S135P/S181L), were produced in Komagataella phaffii, evaluating their thermostability and depolymerizing activity. Compared to both the wild type and variant FsC-sc, FsC-fp exhibited superior thermal stability, maintaining full activity for 24 h at 50 °C and showing substantial resistance to deactivation at 60 °C. Additionally, FsC-fp demonstrated increased catalytic activity against PLA (23 % higher) and PET. Computational simulations aligned with experimental results, predicting higher k_cat and binding affinity for the engineered variants. Structural analysis revealed that these mutations altered the geometry of the catalytic pocket, and increased surface hydrophobicity in FsC-fp, enhancing substrate interaction. This work highlights the efficacy of computational enzyme design in developing biocatalysts for industrial plastic recycling.