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.
Decompdiff: Diffusion models with decomposed priors for structure-based drug design, 2024
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ToolMol integrates evolutionary algorithms with agentic LLMs and precise RDKit tools to optimize multi-objective drug properties, yielding ligands with over 10% better predicted binding affinity and 35% gains in absolute binding free energy on three protein targets.
citing papers explorer
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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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ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery
ToolMol integrates evolutionary algorithms with agentic LLMs and precise RDKit tools to optimize multi-objective drug properties, yielding ligands with over 10% better predicted binding affinity and 35% gains in absolute binding free energy on three protein targets.