Detergent enzymes have been extensively developed as eco-friendly alternatives to harmful chemicals, with alkaline protease representing a significant portion of detergent enzyme sales. However, the self-cleavage function of alkaline protease impacts its activity and overall application. Therefore, a new rational combinatorial strategy is proposed based on self-molecular docking (Self-ZDOCK) and molecular dynamics (MD) simulations. Self-ZDOCK is a computational method for predicting the binding mode of proteins to themselves, which is crucial for understanding the self-cleavage mechanism of proteases. On the other hand, MD simulation is a powerful tool to gain insight into the dynamic behaviour of proteins over time, and thus to analyse the structural stability and flexibility of BpAP under various conditions. Experiments verified this strategy is an effective way to improve the anti-autolytic ability of BpAP. Among the 28 mutants of BpAP, 5 mutants showed increases in thermal stability, pH stability, and storage stability in detergent, indicating a significant enhancement in their anti-autolytic capacity. Structural analysis and MD simulations confirmed that the enhanced stability characteristic of BpAP is attributed to improved anti-autolytic ability rather than increased structural stability. The three points combined mutant (MT5) showed the best increases in autolytic ability, as well as advanced catalytic efficiency. The low rate of inactive mutants and the high rate of positive mutants indicated that newly introduced screening factors (distance from catalytic residues, Gibbs free energy term, molecular simulation, and visual inspections) greatly enhance the design of anti-autolytic alkaline protease. Additionally, these findings enhance the industrial use of alkaline protease in detergents and similar applications.
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