Science cover: New AI technology is expected to solve the problem of RNA structure prediction

Determining the three-dimensional structure of biomolecules is one of the biggest challenges in modern biology

In the past two years, the application of artificial intelligence (AI) technology in the prediction of the structure of biological macromolecules has attracted more and more attention

Proteins are vital to life, and understanding their three-dimensional structure is the key to understanding their functions

In addition to AlphaFold, another system called RoseTTAFold developed by the research team at the University of Washington has also made important progress in predicting protein structure

While AI technology has solved major challenges in the field of protein structure analysis for decades, scientists from Stanford University have also applied AI technology to RNA structure prediction

RNA molecules are usually folded into complex three-dimensional shapes, which are critical to their function, but it is therefore difficult to determine the structure of RNA through experimental means

ARES network (Source: Science)

In this new study, Raphael JL Townshend et al.

ARES shows the highest level of blind RNA structure prediction (Source: Science)

ARES learns to identify key features of RNA structures that are not previously described (Source: Science)

Scientists believe that this machine learning method is expected to accelerate the deciphering of the RNA molecular structure, thereby helping to find drugs for the treatment of diseases that are currently incurable, such as the development of RNA targeted therapies

In addition, the scientists emphasized that most recent advances in deep learning require large amounts of data for training

Reference materials:

[1] Kathryn Tunyasuvunakool et al.

[5] Stanford machine learning algorithm predicts biological structures more accurately than ever before (Source: Stanford University)