高级检索
顾志浩, 郭文浩, 姚和权, 李宣仪, 林克江. 基于人工智能模型筛选与生成先导化合物的研究进展[J]. 中国药科大学学报, 2023, 54(3): 294-304. DOI: 10.11665/j.issn.1000-5048.2023042201
引用本文: 顾志浩, 郭文浩, 姚和权, 李宣仪, 林克江. 基于人工智能模型筛选与生成先导化合物的研究进展[J]. 中国药科大学学报, 2023, 54(3): 294-304. DOI: 10.11665/j.issn.1000-5048.2023042201
GU Zhihao, GUO Wenhao, YAO Hequan, LI Xuanyi, LIN Kejiang. Research progress of the screening and generation of lead compounds based on artificial intelligence model[J]. Journal of China Pharmaceutical University, 2023, 54(3): 294-304. DOI: 10.11665/j.issn.1000-5048.2023042201
Citation: GU Zhihao, GUO Wenhao, YAO Hequan, LI Xuanyi, LIN Kejiang. Research progress of the screening and generation of lead compounds based on artificial intelligence model[J]. Journal of China Pharmaceutical University, 2023, 54(3): 294-304. DOI: 10.11665/j.issn.1000-5048.2023042201

基于人工智能模型筛选与生成先导化合物的研究进展

Research progress of the screening and generation of lead compounds based on artificial intelligence model

  • 摘要: 良好的先导化合物对于药物研发具有深远影响,可以提高药物上市的成功率。利用传统方法发现先导化合物存在成本高且耗时的问题,而人工智能(artificial intelligence,AI)可以高效发现良好的先导化合物。本文系统地总结了通过人工智能的筛选模型与生成模型获得先导化合物的研究进展,按照输入信息的类型归纳整理不同的模型,重点介绍了利用筛选模型实现药物重定位和利用生成模型实现多目标药物设计,探讨了人工智能在先导化合物研究领域的发展前景,为人工智能在先导化合物方面的应用提供新的研究思路。

     

    Abstract: Excellent lead compounds have a profound influence on drug development and can improve the success rate of product launch. It is expensive and time-consuming to discover lead compounds by traditional methods, yet artificial intelligence (AI) can discover good lead compounds efficiently.This article systematically summarizes the research progress of obtaining lead compounds through the screening and generation models of AI, classifies different models according to the type of information input, focuses on drug repurposing by screening model and multi-objective drug design by generation model, and discusses the development prospect of AI in the research field of lead compounds, aiming to provide new research ideas for the application of AI in lead compounds.

     

/

返回文章
返回