Drug Node

Drug node research focuses on representing drugs as nodes within complex networks to predict drug-target interactions, drug-drug interactions, and drug efficacy. Current research employs graph neural networks (GNNs), including graph attention networks and variational graph autoencoders, often incorporating 3D protein structure information and molecular fingerprints to enhance predictive accuracy. These computational approaches aim to accelerate drug discovery by efficiently screening potential drug candidates and predicting potential side effects from drug combinations, ultimately improving drug development and patient safety.