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从头开始设计药物的化学语言模型:挑战与机遇。

Chemical language models for de novo drug design: Challenges and opportunities.

机构信息

Eindhoven University of Technology, Institute for Complex Molecular Systems and Dept. Biomedical Engineering, Eindhoven, Netherlands; Centre for Living Technologies, Alliance TU/e, WUR, UU, UMC Utrecht, Netherlands.

出版信息

Curr Opin Struct Biol. 2023 Apr;79:102527. doi: 10.1016/j.sbi.2023.102527. Epub 2023 Feb 2.

Abstract

Generative deep learning is accelerating de novo drug design, by allowing the generation of molecules with desired properties on demand. Chemical language models - which generate new molecules in the form of strings using deep learning - have been particularly successful in this endeavour. Thanks to advances in natural language processing methods and interdisciplinary collaborations, chemical language models are expected to become increasingly relevant in drug discovery. This minireview provides an overview of the current state-of-the-art of chemical language models for de novo design, and analyses current limitations, challenges, and advantages. Finally, a perspective on future opportunities is provided.

摘要

生成式深度学习正在加速从头设计药物,它允许按需生成具有所需特性的分子。使用深度学习以字符串形式生成新分子的化学语言模型在这方面取得了特别的成功。得益于自然语言处理方法的进步和跨学科合作,化学语言模型有望在药物发现中变得越来越重要。本文综述了用于从头设计的化学语言模型的最新进展,并分析了当前的局限性、挑战和优势。最后对未来的机遇进行了展望。

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