A team of researchers from the Institute of Zoology at the Chinese Academy of Sciences has made a groundbreaking discovery using artificial intelligence (AI) to explain why different species often develop similar traits when adapting to comparable environments. The scientists utilized an advanced AI-driven protein language model to uncover the mechanisms underpinning this evolutionary phenomenon.
The process, known as convergent evolution, describes how distinct species independently evolve similar characteristics due to environmental pressures or functional needs. The study highlights the crucial influence of complex protein properties in driving adaptive convergence across vastly different species.
For example, though bats and toothed whales are separated by millions of years of evolution, both have independently developed the ability to use echolocation to navigate and detect prey. This shared ability, according to the researchers, exemplifies how nature repeatedly finds similar solutions to similar environmental challenges.
Under the leadership of Zou Zhengting, the research introduced a novel computational framework called “ACEP,” which employs a pre-trained protein language model to decode deep structural and functional patterns within amino acid sequences. Zou noted that this innovation enhances our understanding of life’s evolutionary processes while showcasing the transformative potential of AI in tackling complex biological questions. The team aims to further expand the application of AI technology in the study of evolutionary biology, exploring new frontiers in the scientific understanding of life’s development.
