Protein-protein interactions (PPIs) regulate essential cellular processes and represent an important class of therapeutic targets; however, discovering effective modulators of PPIs remains a formidable challenge. Although deep learning approaches have been widely explored for PPI modulator discovery, many rely on simpl...
Lai-Ying Yang, Jing Chen, Hong Tan et al.· Journal of Chemical Informat...· 0 citations
This work proposes ARF-GNN, an adaptive receptive field graph neural network tailored for protein function prediction, which dynamically models structural context via hierarchical multi-hop neighborhood aggregation and introduces a dual-branch meta-learning framework.
Zhiqiang Hui, Weizhong Lu, Yi-Yi Xia et al.· Computational biology and ch...· 0 citations
RGTBind, a graph transformer that combines multi-scale radial basis function distance encoding with a learnable threshold-gating mechanism to model spatially informative residue interactions, achieved the best F1, AUC, and MCC among the compared methods.
Yi Qiu, Duo Zhao, Y. Ye et al.· Journal of Molecular Modelin...· 0 citations
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