Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization

In three linesDEPPA optimizes pocket-aware diffusion models for drug design via reinforcement learning. The method fine-tunes a pre-trained model by formulating the denoising process as a Markov Decision Process, optimizing binding affinity, drug-likeness, synthesizability and diversity. On CrossDocked2020 benchmark, DEPPA achieves Vina Score -8.5 kcal/mol.

Summary generated by Claude — human-verified