Zhao_2025_Int.J.Biol.Macromol__146620

Enzymes are nature's tiny workers, breaking down complex molecules with precision. Directed evolution a technique that mimics natural selection in the lab allows scientists to enhance enzymes for specific tasks. In this study, we applied directed evolution to improve four key enzymes PHB Depolymerase, Cutinase, Lipase, and Esterase so they could efficiently break down biomaterial-based spinal scaffolds after surgery. Using advanced computational tools like molecular docking and molecular dynamics (MD) simulations, along with high-throughput screening, we developed enzyme variants with superior performance. These engineered enzymes showed remarkable improvements: their catalytic efficiency increased by 1.5 to 3 times, they were structurally more stable (with 10-15 % lower RMSD and 20-30 % higher hydrogen bond formation), and they degraded polycaprolactone (PCL) and polylactic acid (PLA) scaffolds with 60-85 % efficiency over 72 h (p < 0.001). Among them, the mutant Esterase proved to be the most effective. Further structural analysis revealed that these optimized enzymes had reduced flexibility (RMSF: 0.4-0.7 A vs. 0.5-0.8 A in wild-type) and greater stability (Rg: 1.6-1.9 A vs. 1.8-2.3 A), making them more reliable for real-world applications. These findings pave the way for enzyme-driven solutions that ensure biodegradable spinal scaffolds break down at just the right pace fast enough to prevent complications but slow enough to support tissue healing. By harnessing the power of directed evolution, this study contributes to the development of smarter, more efficient enzymes for post-surgical scaffold degradation, advancing the field of regenerative medicine and improving patient recovery.