Reengineering substrate specificity of E. coli glutamate dehydrogenase using a position-based prediction method

Area of Science:

• Biochemistry
• Protein Engineering
• Synthetic Biology

Background:

• Enzyme specificity is crucial for biological processes.
• Re-engineering enzyme active sites enables novel biocatalytic functions.
• Developing predictive methods for protein engineering is essential.

Purpose of the Study:

• To develop and apply a position-based prediction method (PBPM) for re-engineering protein active sites.
• To alter the substrate specificity of E. coli glutamate dehydrogenase for a de novo 1,3-propanediol biosynthetic pathway.

Main Methods:

• Utilized a position-based prediction method (PBPM) to identify key residues for substrate specificity.
• Selected E. coli glutamate dehydrogenase as the target enzyme.
• Performed site-directed mutagenesis on identified key residues (e.g., K92).

Main Results:

• Successfully re-engineered E. coli glutamate dehydrogenase to accept homoserine as a substrate, instead of glutamate.
• Identified key residues influencing substrate specificity.
• The K92V mutant showed a significant increase in specific activity (from 171 ± 35 to 1328 ± 71 μU mg⁻¹).

Conclusions:

• The position-based prediction method (PBPM) is highly efficient for re-engineering enzyme substrate specificity.
• This approach enables the creation of enzymes tailored for non-natural substrates and new biosynthetic pathways.