Protein Ligand

Protein-ligand interactions are crucial for understanding biological processes and drug discovery, with primary research objectives focused on accurately predicting binding affinity and 3D structure of complexes. Current research heavily utilizes machine learning, employing graph neural networks, diffusion models, and transformer architectures to analyze protein and ligand structures, often incorporating geometric and physicochemical information to improve prediction accuracy and efficiency. These advancements significantly impact drug development by enabling faster and more accurate virtual screening, leading to improved drug design and reduced development costs.