Protein Structure Prediction

Protein structure prediction aims to determine a protein's 3D shape from its amino acid sequence, crucial for understanding its function and designing new proteins. Current research heavily utilizes deep learning, particularly transformer-based models like AlphaFold and its variants, along with diffusion models and graph neural networks, focusing on improving accuracy, efficiency, and the prediction of protein complexes and dynamic structures. These advancements significantly accelerate drug discovery, protein engineering, and other areas of biological research by providing accurate and readily accessible structural information.