Suppr超能文献

从头开始的分子设计与化学语言模型。

De Novo Molecular Design with Chemical Language Models.

机构信息

ETH Zurich, Department of Chemistry and Applied Biosciences, RETHINK, Zurich, Switzerland.

Eindhoven University of Technology, Department of Biomedical Engineering, Eindhoven, Netherlands.

出版信息

Methods Mol Biol. 2022;2390:207-232. doi: 10.1007/978-1-0716-1787-8_9.

Abstract

Artificial intelligence (AI) offers new possibilities for hit and lead finding in medicinal chemistry. Several instances of AI have been used for prospective de novo drug design. Among these, chemical language models have been shown to perform well in various experimental scenarios. In this study, we provide a hands-on introduction to chemical language modeling. A technique based on recurrent neural networks is discussed in detail, together with a step-by-step guide to applying this AI method for focused compound library design. The program code is freely available at URL: github.com/ETHmodlab/de_novo_design_RNN .

摘要

人工智能(AI)为药物化学中的命中和先导发现提供了新的可能性。已经有几种 AI 被用于前瞻性的从头药物设计。在这些方法中,化学语言模型在各种实验场景中表现良好。在这项研究中,我们提供了化学语言建模的实践介绍。详细讨论了基于递归神经网络的技术,并提供了一个逐步指南,用于应用此 AI 方法进行有针对性的化合物库设计。程序代码可在 URL:github.com/ETHmodlab/de_novo_design_RNN 处免费获得。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验