3D Ligand

3D ligand design focuses on computationally generating molecules with optimal binding properties to target proteins, a crucial step in drug discovery. Current research emphasizes developing advanced deep learning models, such as diffusion models and equivariant neural networks, to predict and generate these 3D structures, often incorporating multi-objective optimization and decomposition strategies to improve efficiency and realism. These methods aim to overcome limitations of traditional approaches by leveraging the power of 3D information and incorporating physical and chemical properties into the design process. The ultimate goal is to accelerate drug development by efficiently identifying and designing potent and synthesizable drug candidates.