Protein Pocket

Protein pockets are three-dimensional indentations on protein surfaces crucial for binding molecules, impacting diverse processes from enzyme catalysis to drug action. Current research intensely focuses on computationally designing and predicting these pockets, employing generative models like diffusion models and graph neural networks to create molecules tailored to specific pockets or design pockets for desired molecules. These advancements leverage techniques such as flow matching, equivariant networks, and multi-objective optimization to improve the accuracy and efficiency of structure-based drug design and enzyme engineering, ultimately accelerating drug discovery and biotechnology applications.