Fewer Off-Target Gene Editors Using AI

Artificial intelligence (AI) is being applied to gene editing to create more precise and effective tools, similar to its impact on drug development. While CRISPR-Cas9 revolutionized the field, off-target effects and genomic rearrangements remain a concern, especially for in vivo therapies. Other gene editing technologies like ZFNs and TALENs also face challenges, highlighting the need for advancements that AI is now poised to address. An article in Genetic Engineering and Biotechnology News tackles some advances in gene editing involving AI.

Neoclease's custom AI model develops gene-specific editors, which may direct gene editing for humans in vivo, using the CRISPR nucleases, ZFNs, TALENs, and other gene editing nucleases. The developers describe it as “ChatGPT for proteins” that can be used to generate novel and effective protein designs.

DeepNEU simulates the CRISPR-Cas9 enzyme and functions like a text editor for genes to enable rapid prototyping and quality checks. Off-target effects are avoided so that when the virtual results are compared to those of CRISPR-Cas9 experiments, any differences can be identified, minimized or eliminated.

Gene editor called ZFDesign can identify the most precise options to reduce off-targeting. The current model has been modified to express all the ZFNs in the array continuously, rather than skipping bases between pairs, which reduces the modularity in the design.

Read more from Genetic Engineering and Biotechnology News.