Evaluation of Docking Simulation Platforms for Predicting Incorporation Efficiency of Non-Canonical Amino Acids

This study evaluated the docking simulation platforms for the incorporation of amber-suppression tRNA synthetase and non-canonical amino acids (ncAAs).Recombinant Escherichia coli harboring mutant green fluorescence proteins and orthogonal amber-suppression tRNA synthetase/ tRNA pair was cultivated with different ncAAs, and the fluorescence and growth were measured.For molecular docking simulation of synthetase and each ncAA, three different platforms were used and the binding affinity predictions were examined.By comparing simulation results with experimental fluorescence protein expression, the reliability of each platform was assessed.AzF exhibited the highest expression levels and strong binding affinity in simulations, while pFF and pAcF showed lower expression and weaker affinity, demonstrating consistent trends between experimental and simulation results.In contrast, BpF displayed high affinity in simulations but low expression levels, which was attributed to ligand positioning outside the active site, as revealed by structural analysis.Among the tested docking platforms, DiffDock-L and DynamicBind showed better predictive accuracy than Autodock Vina.The results obtained in this study will serve as a valuable resource for the effective design for the biosynthesis of recombinant proteins incorporated with non-canonical amino acids.