An AI tool has made a step forward in translating the language proteins use to dictate whether they form sticky clumps similar to those linked to Alzheimer’s disease and around fifty other types of human disease. In a departure from typical “black-box” AI models, the new tool, CANYA, was designed to be able to explain its decisions, revealing the specific chemical patterns that drive or prevent harmful protein folding.

The discovery, published in the journal Science Advances, was possible thanks to the largest-ever dataset on protein aggregation created to date. The study gives new insights about the molecular mechanisms underpinning sticky proteins, which are linked to diseases affecting half a billion people worldwide.

Protein clumping, or amyloid aggregation, is a health hazard that disrupts normal cell function. When certain patches in proteins stick to each other, proteins grow into dense fibrous masses that have pathological consequences.