Automation to Enable High-Throughput Chemical Proteomics.

Journal: Journal of proteome research
Published Date:

Abstract

Chemical proteomics utilizes small-molecule probes to covalently engage with their interacting proteins. Since chemical probes are tagged to the active or binding sites of functional proteins, chemical proteomics can be used to profile protein targets, reveal precise binding sites/mechanisms, and screen inhibitors competing with probes in a biological context. These capabilities of chemical proteomics have great potential to enable discoveries of both drug targets and lead compounds. However, chemical proteomics is limited by the time-consuming bottleneck of sample preparations, which are processed manually. With the advancement of robotics and artificial intelligence, it is now possible to automate workflows to make chemical proteomics sample preparation a high-throughput process. An automated robotic system represents a major technological opportunity to speed up advances in proteomics, open new frontiers in drug target discovery, and broaden the future of chemical biology.

Authors

  • Zongtao Lin
    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Joanna Gongora
    Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Xingyu Liu
    First People's Hospital of Zunyi City, Zunyi, China.
  • Yixuan Xie
    College of Information Engineering, Capital Normal University, Beijing, China.
  • Chenfeng Zhao
    McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri 63110, United States.
  • Dongwen Lv
    Department of Biochemistry and Structural Biology and Center for Innovative Drug Discovery, School of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, United States.
  • Benjamin A Garcia
    From the ‡Genomics and Computational Biology, Biomedical Graduate Studies, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; bgarci@pennmedicine.upenn.edu.