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Mutant-Initiated Structure-Guided Refinement Enables Second-Generation Compact IscB Genome Editors.

Taixin Sha1,2, Dongdong Zhao2,3, Xiumei Zhao2

  • 1School of Biological Engineering, Dalian Polytechnic University, Dalian, China.

Chembiochem : a European Journal of Chemical Biology
|May 25, 2026
PubMed
Summary

Researchers enhanced compact genome editors like IscB for mammalian cells. A structure-guided strategy identified a key mutation (V367Y) significantly boosting editing efficiency for both nuclease and base editing applications.

Keywords:
CRISPRbase editinggenome editingiscBprotein engineering

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Published on: September 25, 2019

Area of Science:

  • Molecular Biology
  • Biotechnology
  • Structural Biology

Background:

  • Compact RNA-guided nucleases (e.g., IscB) show promise for genome editing.
  • Current IscB editor activity in mammalian cells is limited.
  • Novel strategies are needed to improve IscB editor performance.

Purpose of the Study:

  • To develop a structure-guided optimization strategy for enhancing IscB editor activity.
  • To generate second-generation IscB editors with improved efficiency in mammalian cells.
  • To assess the impact of identified mutations on both nuclease and base editing functions.

Main Methods:

  • Employed a mutant-initiated, structure-guided approach for enzyme optimization.
  • Utilized AlphaFold3 for modeling the IscB-nucleic acid complex.
  • Performed focused mutational scanning and saturation mutagenesis at identified hotspots.
  • Evaluated editing efficiency and off-target effects in mammalian cells.

Main Results:

  • Identified V367 as a critical residue for enhancing IscB activity.
  • Developed the V367Y substitution (IscB*-Act), increasing mean editing efficiency by 34% (up to 2.1-fold).
  • Demonstrated V367Y's transferability to adenine base editors, improving A-to-G conversion by 68% (up to 4.46-fold).
  • Showed no substantial increase in off-target indels or base editing.

Conclusions:

  • Established a practical framework for second-generation refinement of compact genome editors.
  • Integrated deep-learning structural prediction with protein engineering for enzyme improvement.
  • Expanded the utility of miniature IscB systems for advanced genome and base editing in mammalian systems.