BEIJING, CHINA: In a landmark scientific achievement, researchers from the Institute of Zoology at the Chinese Academy of Sciences have discovered a key mechanism explaining how different species evolve similar traits — a phenomenon known as convergent evolution — using a powerful AI protein language model.
The breakthrough sheds new light on how nature “rewrites” its genetic code to adapt to changing environments. The study, published in the Proceedings of the National Academy of Sciences (PNAS), introduces an AI-powered framework called ACEP, designed to analyze complex protein data and uncover high-level evolutionary patterns previously invisible to traditional methods.
According to the research team, the model identified hidden structural and functional signals within protein sequences, revealing that organisms with vastly different evolutionary backgrounds can develop similar adaptive features when exposed to comparable environmental pressures. Examples include bats and dolphins, both of which independently evolved echolocation to navigate their surroundings.
The scientists emphasized that this discovery not only enhances understanding of evolutionary biology but also opens new doors for biotechnology and genetic engineering, where similar AI tools could be used to predict or even design protein functions.
Experts describe this as a major step forward in merging artificial intelligence with life sciences, showcasing how machine learning can decode patterns that took nature millions of years to perfect. The study’s authors believe that the ACEP model could soon be applied to explore other evolutionary puzzles such as metabolism, vision, and cellular adaptation.
The research underscores China’s growing presence in AI-driven scientific discovery, positioning the country at the forefront of global efforts to understand the origins and mechanisms of life through technology.
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