Artificial intelligence (AI) is reshaping the fight against viral infections in crops through precision CRISPR genome editing, strengthening global food security amid rising agricultural challenges. A new study published in the journal Genes explores how AI algorithms, ranging from machine learning to generative neural networks, are transforming the design and optimization of CRISPR tools for developing virus-resistant plants.
[The] research highlights the synergy between computational prediction and biological experimentation in combating crop diseases that devastate yields across tropical and subtropical regions.
Plant viral infections continue to cause catastrophic losses, often exceeding 30 percent of yield annually, in crops such as tomato, rice, cotton, and maize. … CRISPR/Cas systems, originally derived from bacterial immune responses, have emerged as the most promising tool for precise genome manipulation, allowing scientists to edit viral genomes or host susceptibility genes directly.
The study primarily focuses on the AI-assisted engineering of Cas proteins, the molecular “scissors” that perform targeted cutting of DNA or RNA. Deep learning models can now simulate protein–nucleic acid interactions, enabling scientists to design enzymes with enhanced specificity and stability inside plant cells.
