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Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
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A Computational Model for Nme1Cas9 HNH Activation Driven by Dynamic Interface Engineering at Residues S593 and W596
1Warshel Institute for Computational Biology, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China.
Biomolecules
|March 28, 2026
Summary
Nme1Cas9 genome editing shows low efficiency due to its HNH nuclease domain. Enhancing this domain
Area of Science:
- Molecular Biology
- Biochemistry
- Computational Biology
Background:
- Nme1Cas9 is a compact, high-fidelity genome editor, but its catalytic efficiency is lower than SpyCas9.
- The HNH nuclease domain's dynamic activation mechanism is crucial for improving Nme1Cas9 efficiency.
- Understanding the kinetic bottleneck requires detailed analysis of the HNH domain's activation pathway.
Purpose of the Study:
- To elucidate the atomic-level activation landscape of the Nme1Cas9 L1-HNH module.
- To identify key conformational changes and energetic barriers in HNH domain activation.
- To propose strategies for engineering hyperactive Nme1Cas9 variants.
Main Methods:
- Integration of Steered Molecular Dynamics (SMD) and the Traveling-Salesman-based automated Path Searching (TAPS) algorithm.
- Reconstruction of the L1-HNH module's activation pathway at the atomic level.
- Thermodynamic analysis using MM/PBSA for free energy decomposition.
- Unbiased Molecular Dynamics (MD) simulations to validate findings.
Main Results:
- A complex 'Lifting-Rearrangement-Sliding' pathway was identified, featuring a critical 'Backbone Sliding' conformation.
- The HNH/R-loop interface instability is the primary energetic barrier for wild-type Nme1Cas9.
- Hyperactive variants (S593Q/W596K and S593Q/W596R) enhance binding affinity via 'Geometry-Electrostatics Synergism'.
- Strengthened interfacial interactions promote drift towards the activated state.
Conclusions:
- The study reveals a novel activation mechanism for the Nme1Cas9 HNH nuclease domain.
- Hyperactive variants achieve higher efficiency by optimizing HNH/R-loop interactions.
- A 'Dynamic Interface Engineering' model is proposed for developing more efficient CRISPR-Cas effectors.
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