4 papers
RetroMPA: A Molecular Property-Aware Auxiliary Framework for Enhancing Retrosynthesis Prediction
Mianzhi Liu, Fan Xiao, Zhiliang Yu +5
Retrosynthesis is a cornerstone of drug discovery and organic synthesis. While data-driven deep learning models have shown remarkable progress, they autonomously learn reaction pat…
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Guikun Chen, Xu Zhang, Xiaolin Hu +3
Chemical reaction data is a pivotal asset, driving advances in competitive fields such as pharmaceuticals, materials science, and industrial chemistry. Its proprietary nature rende…
SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation
Fanglei Xue, Meihan Zhang, Shuqi Li +5
Targeted protein degradation (TPD) induced by small molecules has emerged as a rapidly evolving modality in drug discovery, targeting proteins traditionally considered "undruggable…
Noise-Tolerant Hybrid Prototypical Learning with Noisy Web Data
Chao Liang, Linchao Zhu, Zongxin Yang +2
We focus on the challenging problem of learning an unbiased classifier from a large number of potentially relevant but noisily labeled web images given only a few clean labeled ima…