[Advances in using artificial intelligence for predicting protein-ligand binding affinity].

Journal: Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Published Date:

Abstract

The binding of proteins and ligands is a crucial aspect of life processes. The calculation of the protein-ligand binding affinity (PLBA) offers valuable insights into protein function, drug screening targets protein receptors, and enzyme modifications. In recent years, artificial intelligence (AI) has experienced rapid advancements, becoming widely used in PLBA prediction. This is attributed to its robust feature extraction ability, superior algorithm accuracy, and speedy calculations. Our paper aims to provide a comprehensive overview of AI predication process, associated resources, application scenarios, challenges, and potential solutions, serving as a valuable reference for the relevant research endeavors.

Authors

  • Yinan Yun
    School of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, Zhejiang, China.
  • Shimeng Liu
    Jiaxing Synbiolab Biotech Co. Ltd., Jiaxing 314001, Zhejiang, China.
  • Qi Dai
    The First Clinical Medical College, Guangxi University of Chinese Medicine, Nanning 530001, China.
  • Jin Zhang
    Department of Otolaryngology, The Second People's Hospital of Yibin, Yibin, Sichuan, China.
  • Xiao Wang
    Research Centre of Basic Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.