Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis.

Area of Science:

• Biocatalysis
• Enzyme Engineering
• Synthetic Biology

Background:

• Halide methyltransferases (HMTs) regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine.
• Methyl toluene sulfonate (MeOTs) is a cost-effective substrate for SAM regeneration but exhibits low reactivity with wild-type HMTs.

Purpose of the Study:

• To engineer HMTs for enhanced catalytic efficiency with MeOTs.
• To identify key residues influencing HMT activity using dynamic cross-correlation network analysis (DCCNA).

Main Methods:

• Developed a DCCNA strategy to identify enzyme "hot spots" for targeted mutagenesis.
• Applied DCCNA to evolve HMT from Paraburkholderia xenovorans.
• Utilized molecular dynamics simulations to elucidate the structural basis of enhanced activity.

Main Results:

• Engineered HMT mutant M4 (V55T/C125S/L127T/L129P) achieved a specific activity of 4.08 U/mg towards MeOTs.
• The M4 mutant demonstrated an 82-fold increase in specific activity compared to the wild-type enzyme.
• M4 also showed improved catalytic performance with other methyl donors.

Conclusions:

• The engineered M4 mutant is a highly efficient biocatalyst for SAM regeneration using MeOTs.
• The study presents a novel DCCNA strategy for rapid enzyme engineering.
• This work provides a promising biocatalyst and an efficient enzyme engineering approach.