AlphaFold used to redesign CRISPR proteins, cutting off-target edits from 28% to 5%

Gene-editing therapies have faced a fundamental safety challenge since CRISPR systems were first adapted for human use. Although guide RNAs are designed to match only the intended target sequence, the sheer size of the human genome (about 3 billion bases) means that even rare sequences can appear multiple times by chance. More problematically, the Cas9 protein can tolerate small numbers of mismatched base pairs without losing its ability to bind DNA, making it difficult to predict which off-target sequences will be cut. Researchers have pursued various strategies to address this—optimizing guide RNA selection, improving the Cas proteins themselves, and modifying the effector proteins that make the actual DNA change. This new work takes a computational approach, leveraging AlphaFold's ability to model protein-nucleic acid interactions to identify the exact structural features of Cas9 that enable off-target binding.

What makes this approach particularly valuable is its specificity and generality. By analyzing how Cas9's structure changes when binding mismatch-containing sequences, the researchers found that amino acids shift their contact patterns in predictable ways. This allowed them to design targeted modifications—swapping amino acids at identified positions—that reduce off-target activity dramatically without losing on-target performance. The fact that the method worked for both Cas9 and Cas12 suggests it could be applied to other gene-editing systems. While other research teams have achieved similar or slightly better results using directed evolution, this computational method offers the potential to design systems tailored to specific guide RNAs and known mismatch patterns, opening a path toward personalized safety optimization in gene therapy development.