Structure-guided consensus approach to create a more thermostable penicillin G acylase

Area of Science:

• Protein Engineering
• Biotechnology
• Enzyme Stabilization

Background:

• Thermostabilization of large enzymes like penicillin G acylase (PGA) is challenging due to their complex structure and maturation.
• Traditional methods, such as the consensus approach, often require extensive homologous sequences.

Purpose of the Study:

• To develop an efficient, data-driven protein design method for enhancing PGA thermostability.
• To identify single-point mutations that increase enzyme stability without compromising activity.

Main Methods:

• A data-driven protein design strategy integrating structural information was employed.
• Fewer homologous sequences were required compared to traditional consensus methods.
• 21 single-point mutants of PGA were generated and experimentally tested.

Main Results:

• Approximately 50% of the designed single-point mutants exhibited enhanced thermostability compared to wild-type PGA.
• Two mutants demonstrated a threefold increase in half-life at 50°C with negligible impact on enzyme activity.
• Predictive software showed poor agreement with experimental data, highlighting the difficulty in predicting stabilizing mutations.

Conclusions:

• The developed data-driven method is effective for designing thermostable enzymes.
• This approach offers a valuable tool for protein engineering, particularly for enzymes with complex characteristics like PGA.
• Experimental validation is crucial as computational predictions for thermostability remain unreliable.