Network Dynamics as Fingerprints of Thermostability in an In Silico-Engineered DyP-Type Peroxidase

Area of Science:

• Biotechnology
• Protein Engineering
• Biochemistry

Background:

• Enzyme stabilization is key for sustainable industrial bioprocesses.
• The structural basis for enzyme thermostability is not fully understood.
• Dye-decolorizing peroxidase (DyP) is an industrially relevant enzyme.

Purpose of the Study:

• To engineer thermostable variants of tetrameric DyP.
• To understand the structural and dynamic basis of enhanced thermostability.
• To explore novel indicators for protein stabilization.

Main Methods:

• Utilized open-source AI design algorithms for enzyme engineering.
• Employed recombination strategies to minimize mutational burden.
• Conducted structural and dynamic analyses, including protein correlation network analysis.

Main Results:

• Engineered DyP variants exhibited significantly improved thermal performance and stability.
• Stabilized variants showed increased compactness, rigidity, and enhanced non-covalent interactions.
• Identified highly connected dynamic interaction networks as a key feature of thermostability.

Conclusions:

• Convergent structural and dynamic features contribute to DyP thermostability.
• Dynamic interaction networks offer a new framework for rational enzyme design.
• Findings provide novel indicators for predicting and enhancing protein stability.