Deep learning-based classification model for GPR151 activator activity prediction.

Journal: BMC bioinformatics
Published Date: Jun 9, 2023

Abstract

BACKGROUND: GPR151 is a kind of protein belonging to G protein-coupled receptor family that is closely associated with a variety of physiological and pathological processes.The potential use of GPR151 as a therapeutic target for the management of metabolic disorders has been demonstrated in several studies, highlighting the demand to explore its activators further. Activity prediction serves as a vital preliminary step in drug discovery, which is both costly and time-consuming. Thus, the development of reliable activity classification model has become an essential way in the process of drug discovery, aiming to enhance the efficiency of virtual screening.

Authors

  • Huangchao Xu
    Computer Network Information Center, Chinese Academy of Sciences, Dongsheng Sourth Street No.2, Haidian District, Beijing, 100190, China.
  • Baohua Zhang
    Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.

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