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Chinese study uses AI to find hidden protein link in unrelated species with similar traits

Scientists discover the key to how functions such as echolocation may evolve independently as different creatures adapt to their environment

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Convergent evolution, or the independent emergence of similar traits in unrelated species, has long been of interest to the scientific community. Photo: Shutterstock
Victoria Bela
Chinese researchers have harnessed artificial intelligence (AI) to uncover hidden shared protein features among species with similar functions that evolved independently.

From echolocation in bats and dolphins to the ability to fly, found in both birds and insects, convergent evolution – or the independent emergence of similar traits in unrelated species – has long been of interest to the scientific community.

The repeated emergence of the same functional trait provides the opportunity to investigate how genes and proteins relate to this process. Traditional investigation methods examine small sequence similarities rather than complex differences, such as 3D structure.

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With the help of an advanced AI protein language model, a team from the Chinese Academy of Sciences has been able to examine these complex high-order features in proteins that evolved separately but served a similar function.

“The findings emphasise an underrated sequence basis for functional trait convergence in evolution,” the team said in a paper published in the peer-reviewed journal Proceedings of the National Academy of Sciences on September 23.

A pod of spinner dolphins in the Red Sea off Egypt. Photo: Shutterstock
A pod of spinner dolphins in the Red Sea off Egypt. Photo: Shutterstock

Convergent evolution, also known as convergence, is the repeated, independent evolutionary emergence of the same trait in two or more species, thought to be driven by adaptation to similar environments or lifestyles.

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