Artificial intelligence in peptide-based drug design.

Journal: Drug discovery today
PMID: 39842504

Abstract

Protein-protein interactions (PPIs) are fundamental to a variety of biological processes, but targeting them with small molecules is challenging because of their large and complex interaction interfaces. However, peptides have emerged as highly promising modulators of PPIs, because they can bind to protein surfaces with high affinity and specificity. Nonetheless, computational peptide design remains difficult, hindered by the intrinsic flexibility of peptides and the substantial computational resources required. Recent advances in artificial intelligence (AI) are paving new paths for peptide-based drug design. In this review, we explore the advanced deep generative models for designing target-specific peptide binders, highlight key challenges, and offer insights into the future direction of this rapidly evolving field.

Authors

  • Silong Zhai
    School of Pharmaceutical Sciences, Zhejiang University of Technology, Hangzhou 310014, China.
  • Tiantao Liu
    Faculty of Applied Science, Macao Polytechnic University, 999078, Macao.
  • Shaolong Lin
    Faculty of Applied Science, Macao Polytechnic University, 999078, Macao.
  • Dan Li
    State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University and Collaborative Innovation Center, Chengdu, Sichuan 610041, PR China.
  • Huanxiang Liu
    Lanzhou University.
  • Xiaojun Yao
    Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao, 999078, PR China.
  • Tingjun Hou
    College of Pharmaceutical Sciences, Zhejiang University , Hangzhou, Zhejiang 310058, China.

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