Why Does the E1219V Mutation Expand T-Rich PAM Recognition in Cas9 from Streptococcus pyogenes ?
Shreya BhattacharyaPriyadarshi SatpatiPublished in: Journal of chemical information and modeling (2024)
Popular RNA-guided DNA endonuclease Cas9 from Streptococcus pyogenes ( SpCas9 ) recognizes the canonical 5'-NGG-3' protospacer adjacent motif (PAM) and triggers double-stranded DNA cleavage activity. Mutations in Sp Cas9 were demonstrated to expand the PAM readability and hold promise for therapeutic and genome editing applications. However, the energetics of the PAM recognition and its relation to the atomic structure remain unknown. Using the X-ray structure (precatalytic Sp Cas9:sgRNA:dsDNA) as a template, we calculated the change in the PAM binding affinity in response to Sp Cas9 mutations using computer simulations. The E1219V mutation in Sp Cas9 fine-tunes the water accessibility in the PAM binding pocket and promotes new interactions in the Sp Cas9:noncanonical T-rich PAM, thus weakening the PAM stringency. The nucleotide-specific interaction of two arginine residues (i.e., R1333 and R1335 of Sp Cas9) ensured stringent 5'-NGG-3' PAM recognition. R1335A substitution ( Sp Cas9 R1335A ) completely disrupts the direct interaction between Sp Cas9 and PAM sequences (canonical or noncanonical), accounting for the loss of editing activity. Interestingly, the double mutant ( Sp Cas9 R1335A,E1219V ) boosts DNA binding affinity by favoring protein:PAM electrostatic contact in a desolvated pocket. The underlying thermodynamics explain the varied DNA cleavage activity of Sp Cas9 variants. A direct link between the energetics, structures, and activity is highlighted, which can aid in the rational design of improved Sp Cas9-based genome editing tools.
Keyphrases
- genome editing
- crispr cas
- dna binding
- high resolution
- healthcare
- escherichia coli
- magnetic resonance imaging
- circulating tumor
- magnetic resonance
- pseudomonas aeruginosa
- mass spectrometry
- gene expression
- oxidative stress
- machine learning
- molecular dynamics
- candida albicans
- big data
- copy number
- deep learning
- molecularly imprinted