基于深度学习的药物设计方法

doi:10.3969/j.issn.0253-9608.2021.05.009

摘要/Abstract

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。

关键词: 药物设计, 人工智能, 深度学习, 大数据

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.

Key words: , drug design, artificial intelligence, deep learning, big data

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.

LI Fenglei, HU Qiaoyu, XIONG Ruofan, BAI Fang. Computational drug design methods by deep learning algorithms [J]. Chinese Journal of Nature, 2021, 43(5): 383-390.

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链接本文: https://www.nature.shu.edu.cn/CN/10.3969/j.issn.0253-9608.2021.05.009

https://www.nature.shu.edu.cn/CN/Y2021/V43/I5/383

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基于深度学习的药物设计方法

Computational drug design methods by deep learning algorithms

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