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<p>Predicting drug-target interactions (DTI) is a complex task. With the introduction of artificial intelligence (AI) methods such as machine learning and deep learning, AI-based DTI prediction can significantly enhance speed, reduce costs, and screen potential drug design options before conducting actual experiments. However, the application of AI methods also faces several challenges that need to be addressed. This article reviews various AI-based approaches and suggests possible future directions.</p>

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Application of Artificial Intelligence In Drug-target Interactions Prediction: A Review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月13日

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  • Qian Liao,
  • Yu Zhang,
  • Ying Chu,
  • Yi Ding,
  • Zhen Liu,
  • Xianyi Zhao,
  • Yizheng Wang,
  • Jie Wan,
  • Yijie Ding,
  • Prayag Tiwari,
  • Quan Zou,
  • Ke Han

摘要

Predicting drug-target interactions (DTI) is a complex task. With the introduction of artificial intelligence (AI) methods such as machine learning and deep learning, AI-based DTI prediction can significantly enhance speed, reduce costs, and screen potential drug design options before conducting actual experiments. However, the application of AI methods also faces several challenges that need to be addressed. This article reviews various AI-based approaches and suggests possible future directions.