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Artificial Intelligence Chemistry2025Journal

ChiralCat: Molecular Chirality Classification with Enhanced Spatial Representation Using Learnable Queries

Yichuan Peng, Gufeng Yu, Runhan Shi, Letian Chen, Xi Wang, Wenjie Du, Xiaohong Huo, Yang Yang

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Abstract

ChiralCat strengthens molecular chirality classification by using learnable queries to extract and organize spatial information. The model is designed to better represent stereochemical differences that are difficult to capture from conventional molecular encodings.

In brief

A spatial representation method for molecular chirality classification using learnable queries.