3D Protein

3D protein structure research focuses on understanding and predicting the three-dimensional arrangements of amino acids in proteins, crucial for deciphering their function and designing new therapeutics. Current research emphasizes developing and applying advanced machine learning models, including graph neural networks, diffusion models, and equivariant networks, to predict both static and dynamic protein structures, often leveraging large datasets of experimental structures and molecular dynamics simulations. These advancements are significantly impacting drug discovery, protein engineering, and our fundamental understanding of biological processes by enabling more accurate predictions of protein behavior and interactions.