3D Molecule

3D molecule generation is a rapidly advancing field focused on computationally designing molecules with desired properties, primarily for drug discovery. Current research heavily utilizes diffusion models, variational flow networks, and graph neural networks, often incorporating techniques like equivariance and reinforcement learning to generate stable and biologically relevant 3D structures, sometimes conditioned on textual descriptions or target protein structures. These advancements offer significant potential for accelerating drug development by enabling the efficient exploration of vast chemical spaces and the design of molecules with optimized binding affinities and other crucial properties.