Protein Folding

Protein folding, the process by which a linear amino acid chain adopts a unique 3D structure, is a central problem in biology with implications for disease and drug design. Current research focuses on developing accurate and efficient computational models, employing techniques like diffusion models, deep reinforcement learning, and graph neural networks to predict folding pathways and structures, often leveraging protein language models and advanced sampling methods. These advancements are improving the prediction of protein structures and kinetics, leading to better understanding of protein function and facilitating the design of novel proteins with specific properties.