Sequence-based drug-target affinity prediction using weighted graph neural networks.

Journal: BMC genomics
Published Date: Jun 17, 2022

Abstract

BACKGROUND: Affinity prediction between molecule and protein is an important step of virtual screening, which is usually called drug-target affinity (DTA) prediction. Its accuracy directly influences the progress of drug development. Sequence-based drug-target affinity prediction can predict the affinity according to protein sequence, which is fast and can be applied to large datasets. However, due to the lack of protein structure information, the accuracy needs to be improved.

Authors

  • Mingjian Jiang
    College of Information Science and Engineering, Ocean University of China, Qingdao, China. jmj@stu.ouc.edu.cn.
  • Shuang Wang
    Engineering Technology Research Center of Shanxi Province for Opto-Electric Information and Instrument, Taiyuan 030051, China. S1507038@st.nuc.edu.cn.
  • Shugang Zhang
    College of Information Science and Engineering, Ocean University of China, Qingdao, China. zhangshugang@hotmail.com.
  • Wei Zhou
    Department of Eye Function Laboratory, Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
  • Yuanyuan Zhang
    National Clinical Research Center for Kidney Disease, State Key Laboratory for Organ Failure Research, Division of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China.
  • Zhen Li
    PepsiCo R&D, Valhalla, NY, United States.

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