Predicting drug-target interactions from drug structure and protein sequence using novel convolutional neural networks.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Accurate identification of potential interactions between drugs and protein targets is a critical step to accelerate drug discovery. Despite many relative experimental researches have been done in the past decades, detecting drug-target interactions (DTIs) remains to be extremely resource-intensive and time-consuming. Therefore, many computational approaches have been developed for predicting drug-target associations on a large scale.

Authors

  • ShanShan Hu
  • Chenglin Zhang
    Institutes of Physical Science and Information Technology, Anhui University, Jiulong Road, Hefei, 230601, China.
  • Peng Chen
  • Pengying Gu
    Cadre's Ward (South District), The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, China. pyGu@ustc.edu.cn.
  • Jun Zhang
    First School of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, China.
  • Bing Wang
    Computer Science & Engineering Department at the University of Connecticut.