Chinese Structural Biologist Nieng Yan Talks Cooperation with AI Team

Nieng Yan, a well-known Chinese structural biologist, responded on Twitter-like Weibo on November 11 to topics such as her resignation from Princeton University, her return to China to establish the Shenzhen Medical Academy of Research and Translation (SMART), and her core research direction being replaced by AI.

Earlier, at the 2022 Shenzhen Global Innovative Forum of Talents, Yan announced these decisions. As early as 2017, Yan endured controversy because she chose to leave Tsinghua University, where she had been teaching for 10 years, to work at Princeton University.

Yan’s announcement of returning to China without warning once again triggered debate on the Internet. People speculated that Yan chose to return home because of insufficient research funds at Princeton and, furthermore, her main research direction had been replaced by AI.

Yan later posted on Weibo, “In the past two days, my teachers and friends who love me urged me to dispel rumors, but I am really busy and have no time to read articles full of mistakes and omissions written by those who didn’t spend much time reading my papers.”

Structural biology is an important branch of biophysics. This discipline mainly applies the ideas and research methods of physics, and uses X-ray crystal diffraction, nuclear magnetic resonance, cryogenic electron microscopy and other technologies to accurately analyze the three-dimensional structure of biological macromolecules such as proteins and nucleic acids and the interaction mechanism between them.

In recent years, with the release of AlphaFold2 by DeepMind, a British artificial intelligence company, two-thirds of a protein structure has been predicted with atomic level accuracy, which has led to widespread belief that AI technology can replace the work of structural biology researchers.

Yan said that she focused on several key issues of electromechanical coupling, ion selection, MOA of drugs and toxins. AlphaFold’s forecast last year reached the level of her team in 2017, and this year, it still stays at the level of her team in 2017 (only for Nav/Cav here). Yan is cooperating with AI teams specializing in structural prediction to test the interaction between new small molecules and proteins. So far, none of the predictions have worked out.

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As for the core scientific research direction being replaced by AI, Yan has said that AI predicts the structure of the human protein based on her previous research and analysis data, adding that she expected AI to become much more powerful to help biological researchers seriously study the origin of life from a chemical point of view.

Yan later added that sufficient start-up funds are the basis for researchers to explore freely in science. She believed that the first tragedy for researchers is that they want to do experiments but have no funds, while the second tragedy is that a lot of start-up funds later retreated from the field.