DEPPA reformulates the denoising process of pocket-aware diffusion models as a multi-step MDP and applies RL fine-tuning with a coarse scheduler to optimize ligands for binding affinity, drug-likeness, synthesizability and diversity on CrossDocked2020.
arXiv preprint arXiv:2308.07413 , year=
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Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
DEPPA reformulates the denoising process of pocket-aware diffusion models as a multi-step MDP and applies RL fine-tuning with a coarse scheduler to optimize ligands for binding affinity, drug-likeness, synthesizability and diversity on CrossDocked2020.
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