Science

AlphaFold helps redesign gene-editing proteins to reduce off-target effects

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AlphaFold helps redesign gene-editing proteins to reduce off-target effects
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Researchers have used an artificial intelligence system, AlphaFold, to redesign gene-editing proteins, making them safer by reducing unintended edits to DNA. The work, published in Nature, addresses a persistent safety concern in gene therapy: off-target effects, where editing tools mistakenly alter the wrong genetic sequence.

These off-target errors affect patients undergoing gene-editing therapies. Because the human genome is vast, even rare DNA sequences can appear multiple times by chance. While the probability of a single off-target edit is low, therapies often require editing many cells, making errors nearly inevitable. This has been a major hurdle for developing safe treatments.

The significance lies in improving the safety profile of gene editing, which is crucial for advancing therapies from research to widespread clinical use. By reducing off-target effects, the modified proteins could lower the risk of unintended genetic changes, potentially making gene therapies more reliable and acceptable for treating diseases.

The team used AlphaFold, an AI program originally designed to predict protein structures, to identify key areas in gene-editing proteins responsible for off-target activity. They then modified those specific regions to minimize errors. The study was published in a recent issue of Nature, though the exact date was not specified in the source.

Gene editing was discovered about two decades ago, and the first therapies based on it are now emerging. However, safety challenges have persisted. Previous efforts have focused on minimizing off-target edits, but this approach using AI to redesign the proteins themselves represents a new strategy.

Next steps likely involve further testing of these redesigned proteins in preclinical models and eventually in humans. The source suggests that this method could lead to safer gene-editing tools, potentially accelerating the development of therapies for genetic disorders. However, no specific timeline or next experiments were detailed in the source.

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