Protein Structure

Protein structure research aims to understand and predict the three-dimensional arrangement of amino acids in proteins, crucial for determining their function. Current research heavily utilizes deep learning, employing architectures like graph neural networks, transformers, and diffusion models to analyze protein structures from various data sources (sequences, cryo-EM images, AFM data). These models are applied to tasks such as structure prediction, ligand binding site identification, and protein-protein interaction analysis, improving accuracy and efficiency compared to traditional methods. Advances in this field have significant implications for drug discovery, protein engineering, and our fundamental understanding of biological processes.