Modifying recombinant purple acid phosphatase using computational design.

Area of Science:

• Biochemistry
• Protein Engineering
• Computational Biology

Background:

• Enhancing protein stability while maintaining activity is a significant challenge in protein engineering.
• Purple acid phosphatase (PAP) is a metalloprotein with a complex redox-active site and iron ions crucial for its function, making it a difficult model for engineering.
• Existing protein engineering methods often face trade-offs between stability and activity.

Purpose of the Study:

• To improve the thermal stability of purple acid phosphatase (PAP) using a computational design strategy.
• To validate computationally designed mutations through experimental methods.
• To assess the impact of mutations on PAP's enzymatic activity, spectral properties, and aggregation.

Main Methods:

• Utilized the CamSol Combination computational design strategy to identify mutations.
• Introduced five specific mutations (H22R, A24P, F54P, H197P, T208R) predicted to enhance thermal stability.
• Performed experimental validation including thermal stability assays, enzymatic activity measurements, spectral analysis, and dynamic light scattering.

Main Results:

• Achieved a 5°C increase in thermal stability for the engineered PAP.
• Maintained enzymatic activity across a slightly expanded pH range.
• Observed subtle spectral and redox behavior shifts, indicating a lower energy of the oxidized state and minimal aggregation.

Conclusions:

• The CamSol Combination strategy successfully enhanced PAP's thermal stability without compromising its activity.
• Computational design offers an efficient approach for multi-trait optimization in protein engineering.
• The engineered PAP demonstrates potential for applications requiring enhanced stability and specific functional properties.