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Ai Virtual Screening

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Ai Virtual Screening

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Research Frontiers in Graph Neural Networks Drug Discovery

Development of GNN architectures for molecular property prediction and binding affinity estimation in virtual screening workflows.

Equivariant Graph Learning in 3D Molecular Geometry
Message Passing Dynamics at Protein-Ligand Binding Interfaces
Heterogeneous Graph Representations of Multi-Target Pharmacology
Generalization Across Chemical Space in Graph Neural Networks
Continuous Molecular Descriptors from Graph Latent Spaces
Attention Mechanisms for Scaffold-Hopping and Analogue Design
Uncertainty Quantification in Graph-Based Binding Predictions
Graph Convolutional Strategies for Protein Structure Prediction
Transferability of Graph Models Across Disease Targets
Interpretable Node Features in Drug Metabolism Prediction

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