MGDTI: Graph Transformer with Meta-Learning for Drug-Target Interaction Prediction

Zhenjiang Zhao, Chengxin He, Yuening Qu, Huiru Zheng, Lei Duan, Jie Zuo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Abstract

Drug-target interaction (DTI) prediction is of great importance for drug discovery and development. With the rapid development of biological and chemical technologies, computational methods for DTI prediction are becoming a promising strategy. However, there are few methods which explore solving the cold-start problem in DTI prediction scenarios due to most of existing methods require modeling under the existing interaction that can’t effectively capture information from new drugs and new targets which have few interactions in existing literature. In this paper, we propose a graph transformer method based on meta-learning named MGDTI to fill the gap. In particular, we employ drug-drug similarity and target-target similarity as additional information for network to mitigate the scarcity of interactions. Besides, we trained our model via meta-learning to be adaptive to cold-start tasks. Moreover, we introduced graph transformer to prevent over-smoothing by capturing long-range dependencies. Comparison results on the benchmark dataset demonstrate that our proposed MGDTI is effective in the DTI prediction.
Original languageEnglish
Title of host publication2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
EditorsXingpeng Jiang, Haiying Wang, Reda Alhajj, Xiaohua Hu, Felix Engel, Mufti Mahmud, Nadia Pisanti, Xuefeng Cui, Hong Song
PublisherIEEE
Pages801-806
Number of pages6
ISBN (Electronic)979-8-3503-3748-8
ISBN (Print)979-8-3503-3749-5
DOIs
Publication statusPublished online - 18 Jan 2024
Event2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) - Istanbul, Turkey
Duration: 5 Dec 20238 Dec 2023

Publication series

Name2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
PublisherIEEE Control Society

Conference

Conference2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Country/TerritoryTurkey
CityIstanbul
Period5/12/238/12/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • drug-target interaction prediction
  • meta-learning
  • graph transformer

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