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Computational tools, such as docking and scoring, for modeling the interactions of proteins with drug-like compounds (ligands) hold great promise to speed the discovery of new, safer medications and reduce the cost of the drug discovery process. However, there is still a need for improved methods of predicting ligand poses and affinities or relative affinities.

The D3R aims to help advance such computational technologies as docking and scoring and free energy methods by collecting and enhancing ligand-protein datasets, and using them as a basis for community-wide, blinded prediction challenges. A D3R Grand Challenge centers on a few datasets, each comprising one protein and multiple ligands with measured affinity data, and with protein-ligand co-crystal structures for at least a subset of the ligands. The datasets are selected based on their quality and their suitability to challenge known pitfalls in docking algorithms and scoring functions, and will be archived for ongoing use as modeling benchmarks.

Grand Challenge participants are invited to join D3R workshops to discuss results and help design future rounds!

(Dates shown below are currently subject to adjustment.)

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