Computation and Structure-Guided Arginine Scanning Engineers a Hyperactive AP Endonuclease for Multiplex Viral RNA...

Area of Science:

• Biotechnology
• Bioinformatics
• Molecular Biology

Background:

• DNA-binding proteins like AP endonucleases are crucial for biotechnology.
• Rewiring DNA-contact surfaces of these proteins is challenging.

Purpose of the Study:

• To develop a general method for engineering DNA-binding protein interfaces.
• To enhance AP endonuclease activity for advanced nucleic acid technologies.

Main Methods:

• Introduced ARGENT (AI-guided Arginine scanning Engine for Nucleic-acid Tuning), an interpretable framework.
• Utilized protein-DNA structures and homologous sequences to identify beneficial arginine substitutions.
• Combined structural and evolutionary data to create a residue-wise hotspot score.

Main Results:

• ARGENT identified key sites on APE1, leading to six single mutants with increased AP-site cleavage.
• A triple mutant, APE1-Evo, showed a ~4-fold increase in rate constant while maintaining fidelity.
• The engineered APE1-Evo, integrated into NAPTUNE-V2.0, enabled multiplex viral RNA detection with high accuracy.

Conclusions:

• AI-guided arginine scanning is a practical method for engineering hyperactive, high-fidelity AP endonucleases.
• ARGENT can be applied to other DNA-binding proteins, including Cas9d, for genome editing.
• This approach enables next-generation nucleic acid technologies and viral RNA sensing.