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.“,”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.