Can Molecular Evolution Mechanism Enhance Molecular Representation?
Kun Li, Longtao Hu, Xiantao Cai, Jia Wu, Wenbin Hu

TL;DR
This paper introduces MEvoN, a molecular evolutionary network that incorporates evolutionary pathways into molecular representations, significantly improving molecular property prediction accuracy over traditional methods.
Contribution
The paper presents a novel approach to molecular representation by integrating evolutionary pathways, enhancing predictive performance beyond existing data-driven methods.
Findings
MEvoN improves molecular property prediction accuracy.
Evolutionary pathways provide valuable information for molecular representations.
The method outperforms traditional algorithms on multiple datasets.
Abstract
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…
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Taxonomy
TopicsRNA and protein synthesis mechanisms · Various Chemistry Research Topics · Microbial Natural Products and Biosynthesis
MethodsFocus
