AgenticPosesRanker ranks docking poses using six deterministic physical tools and LLM reasoning, achieving 50% best-pose accuracy that matches the Smina baseline on a balanced 10-system, 162-pose benchmark.
Knowledge-based scoring function to predict protein– ligand interactions.Journal of Molecular Biology, 295(2):337–356, 2000
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AgenticPosesRanker: An Agentic AI Framework for Physically Grounded Ranking of Protein-Ligand Docking Poses
AgenticPosesRanker ranks docking poses using six deterministic physical tools and LLM reasoning, achieving 50% best-pose accuracy that matches the Smina baseline on a balanced 10-system, 162-pose benchmark.