Liu Yingxu, Xu Chengcheng, Yang Xinyi, Zhang Yanmin, Chen Yadong, Liu Haichun
School of Science, China Pharmaceutical University, Nanjing, 210009, China.
Mol Divers. 2024 Aug;28(4):2411-2427. doi: 10.1007/s11030-024-10942-5. Epub 2024 Aug 4.
The deep molecular generative model has recently become a research hotspot in pharmacy. This paper analyzes a large number of recent reports and reviews these models. In the central part of this paper, four compound databases and two molecular representation methods are compared. Five model architectures and applications for deep molecular generative models are emphatically introduced. Three evaluation metrics for model evaluation are listed. Finally, the limitations and challenges in this field are discussed to provide a reference and basis for developing and researching new models published in future.
深度分子生成模型最近已成为药学领域的一个研究热点。本文分析了大量近期报告并对这些模型进行了综述。在本文的核心部分，比较了四个化合物数据库和两种分子表示方法。着重介绍了深度分子生成模型的五种模型架构及其应用。列出了用于模型评估的三个评估指标。最后，讨论了该领域的局限性和挑战，以便为未来发表的新模型的开发和研究提供参考和依据。
