Unraveling dynamic protein structures by two-dimensional infrared spectra with a pretrained machine learning model.

Journal: Proceedings of the National Academy of Sciences of the United States of America
PMID: 38917009

Abstract

Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for tracing rapid conformational evolutions in proteins. However, linking spectral characteristics to dynamic structures poses a formidable challenge. Here, we present a pretrained machine learning model based on 2DIR spectra analysis. This model has learned signal features from approximately 204,300 spectra to establish a "spectrum-structure" correlation, thereby tracing the dynamic conformations of proteins. It excels in accurately predicting the dynamic content changes of various secondary structures and demonstrates universal transferability on real folding trajectories spanning timescales from microseconds to milliseconds. Beyond exceptional predictive performance, the model offers attention-based spectral explanations of dynamic conformational changes. Our 2DIR-based pretrained model is anticipated to provide unique insights into the dynamic structural information of proteins in their native environments.

Authors

  • Fan Wu
    Department of Product Design, Dalian Polytechnic University, Dalian 116034, China.
  • Yan Huang
    Department of Neurology, University of Texas Health Science Center at Houston, Houston, TX.
  • Guokun Yang
    Key Laboratory of Precision and Intelligent Chemistry, Hefei National Research Center for Physical Sciences at the Microscale, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, Anhui, China.
  • Sheng Ye
    Hefei National Laboratory for Physical Science at the Microscale, Department of Chemical Physics, University of Science and Technology of China, Hefei, Anhui 230026, China.
  • Shaul Mukamel
    Departments of Chemistry, and Physics & Astronomy, University of California, Irvine, California 92697, United States.
  • Jun Jiang
    Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, China.

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