免疫化学专刊

基于深度学习的药物设计方法

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  • 上海科技大学 免疫化学研究所,上海 201210

收稿日期: 2021-05-30

  网络出版日期: 2021-10-25

Computational drug design methods by deep learning algorithms 

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  • Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai 201210, China

Received date: 2021-05-30

  Online published: 2021-10-25

摘要

药物研发是一个长周期、高投入和高风险的过程。随着科学技术的不断革新,生物医学数据呈爆炸式增长,为深度学习技术在生物医药领域的应用带来了契机,同时也为加速新药研发赋予了前所未有的希望。文章围绕药物设计流程,简要介绍深度学习算法在药物靶标发现、分子生成、基于配体的药物设计和基于结构的药物设计4个主要环节中的应用和研究进 展。

本文引用格式

李风雷, 胡乔宇, 熊若凡, 白芳 . 基于深度学习的药物设计方法[J]. 自然杂志, 2021 , 43(5) : 383 -390 . DOI: 10.3969/j.issn.0253-9608.2021.05.009

Abstract

Drug design and development is a long term, expensive and high-risk process. The continuous innovation of science and technology, as well as the explosive growth of the biomedical data brings unprecedented opportunities for the applications of deep learning algorithms in biomedical areas to expediate the drug development. In this review, we briefly overview and list the state-ofthe-art deep learning-driven drug design methods for identifying drug targets, molecular generation, ligand-based and structure-based drug design.

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