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Artificial intelligence in peptide-based drug design

  • Silong Zhai
  • , Tiantao Liu
  • , Shaolong Lin
  • , Dan Li
  • , Huanxiang Liu
  • , Xiaojun Yao
  • , Tingjun Hou
  • Macao Polytechnic University
  • Zhejiang University

研究成果: Review article同行評審

26 引文 斯高帕斯(Scopus)

摘要

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.

原文English
文章編號104300
期刊Drug Discovery Today
30
發行號2
DOIs
出版狀態Published - 2月 2025

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