树(集合论)
计算机科学
节点(物理)
化学空间
生成模型
拓扑(电路)
图形
戒指(化学)
理论计算机科学
生成语法
人工智能
药物发现
数学
化学
组合数学
物理
量子力学
生物化学
有机化学
作者
Mingyuan Xu,Hongming Chen
标识
DOI:10.1021/acs.jcim.3c01626
摘要
De novo molecular design plays an important role in drug discovery. Here, a novel generative model, Tree-Invent, was proposed to integrate topological constraints in the generation of a molecular graph. In this model, a molecular graph is represented as a topological tree in which a ring system, a nonring atom, and a chemical bond are regarded as the ring node, single node, and edge, respectively. The molecule generation is driven by three independent submodels for carrying out operations of node addition, ring generation, and node connection. One unique feature of the generative model is that the topological tree structure can be specified as a constraint for structure generation, which provides more precise control of structure generation. Combined with reinforcement learning, the Tree-Invent model could efficiently explore targeted chemical space. Moreover, the Tree-Invent model is flexible enough to be used in versatile molecule design settings such as scaffold decoration, scaffold hopping, and linker generation.
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