Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling.

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353.