Abstract
Amino acids along the conformational motion pathway of the enzyme molecule correlated to its flexibility and rigidity. To enhance the enzyme activity and thermal stability, the motion pathway of Geobacillus stearothermophilus α-amylase has been identified and molecularly modified by using the neural relational inference model and deep learning tool. The significant differences in substrate specificity, enzymatic kinetics, optimal temperature, and thermal stability were observed among the mutants with modified amino acids along the pathway. Mutants especially the P44E demonstrated enhanced hydrolytic activity and catalytic efficiency (k(cat)/K(M)) than the wild-type enzyme to 95.0% and 93.8% respectively, with the optimum temperature increased to 90°C. This mutation from proline to glutamic acid has increased the number and the radius of the bottleneck of the channels, which might facilitate transporting large starch substrates into the enzyme. The mutation could also optimize the hydrogen bonding network of the catalytic center, and diminish the spatial hindering to the substrate entry and exit from the catalytic center.