Deciphering Cas9 specificity: Role of domain dynamics and RNA:DNA hybrid interactions revealed through machine

Gayatri Panda1, Arjun Ray1

  • 1Department of Computational Biology, Indraprastha Institute of Information Technology, New Delhi, India.

Insights

Francisella novicida Cas9 (FnCas9) exhibits higher specificity than SpCas9 due to domain rearrangements, not RNA:DNA shape. This discovery aids in designing more precise gene editing tools.

Area of Science:

  • Molecular Biology
  • Biochemistry
  • Genomics

Background:

  • CRISPR/Cas9 gene editing is crucial but limited by off-targeting concerns.
  • Existing Cas9 variants with improved specificity often show reduced on-target cleavage efficiency.

Purpose of the Study:

  • To compare the dynamics of Francisella novicida Cas9 (FnCas9) with standard SpCas9.
  • To elucidate the structural determinants of FnCas9's enhanced specificity using advanced simulations and machine learning.

Main Methods:

  • Long-scale atomistic Gaussian accelerated molecular dynamics simulations.
  • Machine learning techniques to analyze structural dynamics and specificity.
  • Comparative analysis of FnCas9 and SpCas9 in native and off-target states.

Main Results:

  • FnCas9 specificity is primarily governed by domain rearrangement, not RNA:DNA heteroduplex shape.
  • Off-target binding induces significant conformational changes in Cas9 domains, with minimal impact on the RNA:DNA hybrid, especially for FnCas9.
  • REC1-REC3 domain interactions with the RNA:DNA hybrid are key discriminators of off-target effects in FnCas9.
  • Allosteric signal transmission in FnCas9 involves REC3 and HNH domains, bypassing REC2, enhancing information transfer efficiency.

Conclusions:

  • FnCas9 possesses superior specificity due to distinct domain dynamics and allosteric signaling pathways.
  • Understanding these structural factors provides a quantitative framework for developing highly specific Cas9 variants.
  • This research facilitates the rational design of next-generation genome editing tools with improved precision.

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