Abstract
The clustered regularly interspaced short palindromic repeats (CRISPR) technology is an RNA-guided targeted genome-editing tool that uses the Cas family proteins. Two magnesium-dependent nuclease domains of this enzyme termed HNH and RuvC are responsible for the cleavage of the target DNA (t-DNA) and non-target DNA strand (nt-DNA), respectively. It is believed that the HNH domain determines the DNA cleavage activity of both endonuclease domains and is sensitive to RNA-DNA base pairing complementary. However, the underlying molecular mechanisms of CRISPR-Cas9, by which it rebukes or accepts mismatches, are poorly understood. Thus, investigation of the structure and dynamics of the catalytic state of Cas9 with either matched or mismatched t-DNA can provide insights for improving its specificity in off-target cleavage. Here we focus on a recently discovered catalytic-active form of the Streptococcus pyogenes Cas9 (SpCas9) and employ classical molecular dynamics (MD) and hybrid QM/MM to study two possible reaction mechanisms of t-DNA cleavage reaction catalyzed by the HNH domain. Moreover, by designing a mismatched t-DNA structure called MM5 (C to G in the fifth position of the PAM region), the impact of single-guide RNA (sgRNA) and t-DNA complementarity on the catalysis process was investigated. Our calculated binding affinities, minimum energy paths, and analysis of catalytically important residues based on these simulations provide atomic-level details of the differences between matched and mismatched cleavage reactions. In addition, several residues exhibit significant differences in their catalytic role for the two considered systems, including K896, R820, K253, K263, K268, and R400, which will be used for further experimental investigations.
Supplementary materials
Title
Supporting Information for: Leveraging QM/MM and Molecular Dynamics Simulations to Decipher the Reaction Mechanism of the Cas9 HNH Domain to Investigate off-Target Effects
Description
Additional details of molecular dynamics, binding enthalpies, k-means clustering, QM/MM path optimization, ESP charges, and energy decomposition analysis
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