Harnessing deep learning for enhanced ligand docking.

Journal: Trends in pharmacological sciences
Published Date: Dec 30, 2023

Abstract

Ligand docking (LD), a technology for predicting protein-ligand (PL)-binding conformations and strengths, plays key roles in virtual screening (VS). However, the accuracy and speed of current LD methodologies remain suboptimal. Here, we discuss how deep learning (DL) could help to bridge this gap by examining recent advancements and projecting future trends.

Authors

  • Xujun Zhang
    Injury Prevention Research Institute, Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, Jiangsu Province, China.
  • Chao Shen
    Department of Epidemiology, School of Public Health, Soochow University, Suzhou 215123, China.
  • Chang-Yu Hsieh
    Tencent Quantum Laboratory, Tencent, Shenzhen 518057 Guangdong, P. R. China.
  • Tingjun Hou
    College of Pharmaceutical Sciences, Zhejiang University , Hangzhou, Zhejiang 310058, China.

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