基于深度分子生成模型的类天然产物虚拟筛选库设计

doi:10.5246/jcps.2018.07.046

中国药学(英文版) ›› 2018, Vol. 27 ›› Issue (7): 451-459.DOI: 10.5246/jcps.2018.07.046

• 【研究论文】 • 下一篇

基于深度分子生成模型的类天然产物虚拟筛选库设计

李亦博, 周鑫, 刘振明^*, 张亮仁^*

北京大学医学部药学院天然药物及仿生药物国家重点实验室, 北京 100191

收稿日期:2018-05-06 修回日期:2018-06-10 出版日期:2018-07-25 发布日期:2018-06-25
通讯作者: Tel.: +86-010-82802567; +86-010-82805514, E-mail: zmliu@bjmu.edu.cn; liangren@bjmu.edu.cn
基金资助:
The National Natural Science Foundation of China (Grant No. 81573273, 81673279, 21572010 and 21772005) as well as National Major Scientific and Technological Special Project for “Significant New Drugs Development” (Grant No. 2018ZX09735001-003).

Designing natural product-like virtual libraries using deep molecule generative models

Yibo Li, Xin Zhou, Zhenming Liu^*, Liangren Zhang^*

State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University Health Science Center, Beijing 100191, China

Received:2018-05-06 Revised:2018-06-10 Online:2018-07-25 Published:2018-06-25
Contact: Tel.: +86-010-82802567; +86-010-82805514, E-mail: zmliu@bjmu.edu.cn; liangren@bjmu.edu.cn
Supported by:
The National Natural Science Foundation of China (Grant No. 81573273, 81673279, 21572010 and 21772005) as well as National Major Scientific and Technological Special Project for “Significant New Drugs Development” (Grant No. 2018ZX09735001-003).

摘要/Abstract

摘要：

天然产物在新药研发领域占据着重要的地位。在虚拟筛选库中引入天然产物相关的特征将有助于提升这些化合物库的质量。深度生成模型是一类新兴的全新分子设计方法。在此, 我们使用深度分子生成模型构建类天然产物的虚拟筛选库。结果显示, 该模型能够生成高天然产物类似性的化合物。另外, 该模型也能同时控制天然产物类型性以及合成可及性。基于这些特点, 我们可以构造易于合成的类天然产物化合物库, 从而提升虚筛库的实际应用价值。

关键词: 天然产物, 深度学习, 生成模型, 虚拟筛选库设计

Abstract:

Natural products (NPs) have long been recognized as a valuable resource for drug discovery, and bringing NP-related features to virtual libraries is believed to be an effective way to increase the coverage of druggable chemical space. Here, deep learning-based molecule generative model, which is a recent technique in de novo molecule design, was applied to generate virtual libraries with NP-like properties. Results demonstrated that the model was effective in generating molecules that highly resemble NPs. Moreover, the model was also found to be capable of generating NP-like molecules that were also easy to synthesize, significantly increasing the practical value of the compound library.

Key words: Natural product, Deep learning, Generative model, Virtual library design

中图分类号:

R916

Supporting:

李亦博, 周鑫, 刘振明, 张亮仁. 基于深度分子生成模型的类天然产物虚拟筛选库设计[J]. 中国药学(英文版), 2018, 27(7): 451-459.

Yibo Li, Xin Zhou, Zhenming Liu, Liangren Zhang. Designing natural product-like virtual libraries using deep molecule generative models[J]. Journal of Chinese Pharmaceutical Sciences, 2018, 27(7): 451-459.

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基于深度分子生成模型的类天然产物虚拟筛选库设计

Designing natural product-like virtual libraries using deep molecule generative models

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