An artificial intelligence accelerated virtual screening platform for drug discovery.

Journal: Nature communications
PMID: 39237523

Abstract

Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel Na1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to Na1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.

Authors

  • Guangfeng Zhou
    Department of Biochemistry, University of Washington, Seattle, WA, USA.
  • Domnita-Valeria Rusnac
    Howard Hughes Medical Institute, Department of Pharmacology, University of Washington, Seattle, WA, USA.
  • Hahnbeom Park
    Department of Biochemistry and Institute for Protein Design, University of Washington, Washington, WA, USA.
  • Daniele Canzani
    Department of Chemistry, University of Washington, Seattle, WA, USA.
  • Hai Minh Nguyen
    Department of Pharmacology, University of California Davis, Davis, CA, USA.
  • Lance Stewart
    Department of Biochemistry, University of Washington, Seattle, WA, USA.
  • Matthew F Bush
    Department of Chemistry, University of Washington, Seattle, WA, USA.
  • Phuong Tran Nguyen
    Department of Physiology and Membrane Biology, University of California Davis, Davis, CA, USA.
  • Heike Wulff
    Department of Pharmacology, University of California, Davis, California 95616, United States.
  • Vladimir Yarov-Yarovoy
    Departments of Biochemistry and Molecular Medicine, Chemistry, Statistics, Molecular and Cellular Biology, and Physiology and Membrane Biology, the Center for Neuroscience, and Graduate Programs in Molecular, Cellular, and Integrative Physiology, Biochemistry, Molecular, Cellular and Developmental Biology and Neuroscience, University of California, Davis, Davis, CA 95616, USA.
  • Ning Zheng
    School of Intelligent Engineering, Zhengzhou University of Aeronautics, Zhengzhou, Henan 450046, China.
  • Frank DiMaio
    Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.

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