标题： 分子进化机制能否增强分子表示？ 显示英文标题

标题： Can Molecular Evolution Mechanism Enhance Molecular Representation?

摘要： 分子进化是通过在化学空间中模拟分子的自然进化过程，以探索潜在的分子结构和性质的过程。 相似分子之间的关系通常通过添加、删除和修改原子和化学键等转化来描述，反映了特定的进化路径。 现有的分子表示方法主要集中在数据挖掘上，例如直接从分子中提取原子级结构和化学键，常常忽略了它们的进化历史。 因此，我们旨在探索通过模拟进化过程来增强分子表示的可能性。 我们提取并分析进化路径中的变化，并探讨将其与现有分子表示相结合。 因此，本文提出了用于分子表示的分子进化网络（MEvoN）。 首先，我们使用原子数较少的分子构建MEvoN，并利用相似性计算生成进化路径。 然后，通过建模原子级的变化，MEvoN揭示了它们对分子性质的影响。 实验结果表明，基于MEvoN的分子性质预测方法在多个分子数据集上显著提升了传统端到端算法的性能。 代码可在 https://anonymous.4open.science/r/MEvoN-7416/ 获取。 显示英文摘要

摘要： Molecular evolution is the process of simulating the natural evolution of molecules in chemical space to explore potential molecular structures and properties. The relationships between similar molecules are often described through transformations such as adding, deleting, and modifying atoms and chemical bonds, reflecting specific evolutionary paths. Existing molecular representation methods mainly focus on mining data, such as atomic-level structures and chemical bonds directly from the molecules, often overlooking their evolutionary history. Consequently, we aim to explore the possibility of enhancing molecular representations by simulating the evolutionary process. We extract and analyze the changes in the evolutionary pathway and explore combining it with existing molecular representations. Therefore, this paper proposes the molecular evolutionary network (MEvoN) for molecular representations. First, we construct the MEvoN using molecules with a small number of atoms and generate evolutionary paths utilizing similarity calculations. Then, by modeling the atomic-level changes, MEvoN reveals their impact on molecular properties. Experimental results show that the MEvoN-based molecular property prediction method significantly improves the performance of traditional end-to-end algorithms on several molecular datasets. The code is available at https://anonymous.4open.science/r/MEvoN-7416/.