Structure Based Drug Design

Structure-based drug design (SBDD) leverages protein structures to computationally design molecules with high binding affinity and desirable properties. Current research heavily utilizes generative models, particularly diffusion models and generative flow networks, often incorporating graph neural networks and reinforcement learning to navigate the vast chemical space and optimize for multiple objectives simultaneously. These advancements aim to accelerate drug discovery by efficiently generating and refining drug candidates, potentially reducing development time and costs while improving the success rate of new drug development.