Protein Complex Structure

Predicting the 3D structures of protein complexes, assemblies of multiple protein chains, is a crucial challenge in structural biology with implications for drug discovery and understanding biological function. Current research focuses on improving the accuracy and efficiency of prediction methods, employing deep learning architectures like graph neural networks and generative adversarial networks to overcome the computational complexity of modeling these intricate structures. These advancements leverage diverse data sources, including synthesized AFM images and protein sequence information, and incorporate sophisticated techniques for structure refinement and quality assessment. Ultimately, improved protein complex structure prediction will accelerate research in various fields, including drug design and vaccine development.