Modeling Boltzmann-weighted structural ensembles of proteins using artificial intelligence-based methods.

Journal: Current opinion in structural biology
PMID: 39923288

Abstract

This review highlights recent advances in AI-driven methods for generating Boltzmann-weighted structural ensembles, which are crucial for understanding biomolecular dynamics and drug discovery. With the rise of deep learning models such as AlphaFold2, there has been a shift toward more accurate and efficient sampling of structural ensembles. The review discusses the integration of AI with traditional molecular dynamics techniques as well as experiments, the challenges of conformational sampling, and future directions for AI-driven research in structural biology, particularly in drug discovery and protein dynamics.

Authors

  • Akashnathan Aranganathan
    Biophysics Program, University of Maryland, College Park, 20742, MD, USA; Institute of Physical Science and Technology, University of Maryland, College Park, 20742, MD, USA.
  • Xinyu Gu
    Institute of Physical Science and Technology, University of Maryland, College Park, 20742, MD, USA; University of Maryland Institute for Health Computing, Bethesda, 20852, MD, USA. Electronic address: xgu1997@gmail.com.
  • Dedi Wang
    Biophysics Program and Institute for Physical Science and Technology, University of Maryland, College Park, Maryland 20742, United States.
  • Bodhi P Vani
    Genentech, 1 DNA Way, South San Francisco, 94080, CA, USA.
  • Pratyush Tiwary
    University of Maryland at College Park: University of Maryland, Chemistry and Biochemistry, UNITED STATES OF AMERICA.

Keywords

External Resources

Popular Topics
Recent Journals