Improving generalizability of drug-target binding prediction by pre-trained multi-view molecular representations.

Journal: Bioinformatics (Oxford, England)
PMID: 39776159

Abstract

MOTIVATION: Most drugs start on their journey inside the body by binding the right target proteins. This is the reason that numerous efforts have been devoted to predicting the drug-target binding during drug development. However, the inherent diversity among molecular properties, coupled with limited training data availability, poses challenges to the accuracy and generalizability of these methods beyond their training domain.

Authors

  • Xike Ouyang
    School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun, Jilin 130117, China.
  • Yannuo Feng
    School of Information Science and Technology, Institute of Computational Biology, Northeast Normal University, Changchun, Jilin 130117, China.
  • Chen Cui
    Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai, 201203, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
  • Yunhe Li
    School of Information Science and Engineering, Shandong University, supported by Shandong Provincial Key Laboratory of Wireless Communication Technologies, Jinan, 250100, China.
  • Li Zhang
    Department of Animal Nutrition and Feed Science, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
  • Han Wang
    Saw Swee Hock School of Public Health, National University Health System, National University of Singapore, Singapore.

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