Predicting GPR40 Agonists with A Deep Learning-Based Ensemble Model.

Journal: ChemistryOpen
Published Date: Nov 1, 2023

Abstract

Recent studies have identified G protein-coupled receptor 40 (GPR40) as a promising target for treating type 2 diabetes mellitus, and GPR40 agonists have several superior effects over other hypoglycemic drugs, including cardiovascular protection and suppression of glucagon levels. In this study, we constructed an up-to-date GPR40 ligand dataset for training models and performed a systematic optimization of the ensemble model, resulting in a powerful ensemble model (ROC AUC: 0.9496) for distinguishing GPR40 agonists and non-agonists. The ensemble model is divided into three layers, and the optimization process is carried out in each layer. We believe that these results will prove helpful for both the development of GPR40 agonists and ensemble models. All the data and models are available on GitHub. (https://github.com/Jiamin-Yang/ensemble_model).

Authors

  • Jiamin Yang
    School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, P. R. China, 310053.
  • Chen Jiang
    Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Jing Chen
    Department of Vascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.
  • Lu-Ping Qin
    School of Pharmaceutical Sciences, Zhejiang Chinese Medical University Hangzhou, 310053, People's Republic of China. Electronic address: lpqin@zcmu.edu.cn.
  • Gang Cheng
    National Laboratory of Solid State Microstructures, College of Engineering and Applied Sciences, Nanjing University, 22 Hankou Road, Nanjing 210093, P. R. China.

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