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Ai Precision Medicine

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Ai Precision Medicine

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Research Frontiers in Graph Neural Networks for Protein-Drug Interactions

GNN-based approaches to model and predict binding affinities and interaction mechanisms between therapeutic compounds and target proteins.

Equivariant Graph Architectures in Biomolecular Binding Prediction
Message Passing Dynamics Across Protein Conformational Landscapes
Graph Heterogeneity in Multi-Modal Drug-Target Networks
Topological Invariants for Drug Efficacy and Off-Target Effects
Temporal Graph Evolution in Pharmacokinetic-Pharmacodynamic Systems
Attention Mechanisms in Allosteric Protein-Ligand Recognition
Hypergraph Representations of Protein Complex Assembly Dynamics
Graph Generalization Across Unseen Protein Families and Mutations
Neural Geometry in Structure-Activity Relationship Landscapes
Interpretable Node Embeddings for Personalized Drug Response Prediction

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