Peter Cameron

This paper introduces Protein2PAM, a deep learning model that predicts CRISPR-Cas PAM specificity from protein sequences, enabling the design of Cas variants with tailored PAM recognition.

Language models trained on over one million mined CRISPR operons generated Cas9-like effectors and matching guide RNAs, and an AI-designed editor is reported to edit the human genome precisely.

The paper demonstrates that NmeCas9, a Cas9 ortholog, exhibits high-fidelity genome editing in human cells with minimal off-target effects and multiple PAM compatibility.