High-performance computer-aided drug design is a promising field, in which drug-target affinity (DTA) prediction serves as a core step to reduce R&D costs and improve efficiency. However, current DTA methods suffer from insufficient multi-modal representation and lack interpretability. We propose MAIDTA, an interpretab...
Ming-Hao Li, Ming-Lei Dong, Hong-Lei Li et al.· Computer Methods in Biomecha...· 0 citations
DSC-BSite is proposed, a dynamic-static collaborative multimodal graph learning framework for residue-level binding site prediction that achieves competitive performance across multiple evaluation metrics, with particularly strong results in Recall on UniProtSMB and Precision and MCC on SJC.
A novel model SSIPIN is proposed for protein function prediction, using three types of data including protein sequences, protein-protein interaction networks (PPIN) and protein tertiary structures, which outperforms existing methods on multiple datasets.
Shuai Li, Mingxuan Li, Mandong Hu et al.· International Journal of Mac...· 0 citations
CMD-PLA is proposed as a dynamics-aware framework for protein-ligand affinity prediction, and the conformational evolution of the ligand is explicitly modeled as a pocket-dependent dynamical process rather than an isolated static update.
Hao Li, Dongjiang Niu, Xiaofeng Wang et al.· Computational biology and ch...· 0 citations
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