Fully computational design of PAM-relaxed Staphylococcus aureus Cas9 with expanded targeting capability
Xiong, Y.; Tsai, L.-K.; Zhou, J.; Chen, S.; Xia, X.; Zhang, J.; Chen, Y. E.; Xu, J.; Huang, X.
Show abstract
CRISPR-Cas9 nucleases have transformed genome engineering, yet their application is often constrained by protospacer-adjacent motif (PAM) requirements. Staphylococcus aureus Cas9 (SaCas9) is particularly attractive for in vivo applications due to its compact size; however, its NNGRRT PAM limits targetable genomic sites. Here, we report KRH, a SaCas9 variant designed entirely from the wild-type enzyme through a fully computational point-mutation design workflow, UniDesign, without additional experimental optimization. As expected, KRH efficiently recognizes an expanded NNNRRT PAM and exhibits substantially enhanced editing efficiency at non-canonical PAM sites, with improvements of up to 116-fold over the wild type. Across multiple human cell types, KRH achieves genome- and base-editing efficiencies comparable to, or exceeding, those of the well-known evolution-derived KKH variant. Computational modeling by UniDesign provides a mechanistic explanation for the PAM relaxation observed in both KRH and KKH, with structural and energetic analyses revealing that KRH relaxes PAM specificity by fine-tuning the balance between sequence-specific interactions with PAM bases and nonspecific contacts with the DNA backbone. Beyond its practical utility, KRH demonstrates that computational design can identify a minimal set of mutations sufficient to remodel the PAM interface while preserving high nuclease activity. This approach recapitulates--and in some cases surpasses--the performance of evolution-derived variants, offering a scalable strategy for high-throughput Cas9 engineering. Overall, these results establish KRH as a blueprint for rationally engineered, PAM-relaxed nucleases and underscores the power of computational design to accelerate next-generation genome editing.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- DeepCLIP: Predicting the effect of mutations on protein-RNA binding with Deep Learning 95%
- The Effect of Pseudoknot Base Pairing on Cotranscriptional Structural Switching of the Fluoride Riboswitch 94%
- New design strategies for ultra-specific CRISPR-Cas13a-based RNA-diagnostic tools with single-nucleotide mismatch sensitivity 94%
Similar papers in this journal
- A generative algorithm for de novo design of proteins with diverse pocket structures 95%
- An interpretable molecular framework for predicting cancer driver missense mutations 94%
- Structural basis for the evolution of a domesticated group II intron-like reverse transcriptase to function in host cell DNA repair 94%
Similar papers in this journal
Similar papers in this journal
- Quantification of Cas9 binding and cleavage across diverse guide sequences maps landscapes of target engagement 94%
- Pronounced sequence specificity of the TET enzyme catalytic domain guides its cellular function 93%
- Fragment binding to the Nsp3 macrodomain of SARS-CoV-2 identified through crystallographic screening and computational docking 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.