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Protein-ligand modeling (Posted October 11, 2016)
  • Successful prediction of ligand-protein poses depends on the entire workflow, including factors extrinsic to the core docking algorithm, such as how the ligand and protein structures are prepared, the conformation of the protein selected, and the treatment of crystallographic waters.
  • The success of docking and scoring predictions is not clearly correlated with the software used.
  • Using existing structural information, such as cocrystal structures of small molecules with the target protein, can increase docking success rates. For example, known poses of similar ligands can guide positioning of the new ligand, and better docking results may be obtained by docking a new ligand into a binding site solved with another ligand with the same chemotype.
  • Human inspection and intervention can lead to improved pose predictions.
  • Ranking or scoring of affinities remains challenging, even in cases where co-crystal structures of the ligands are available.
  • Explicit solvent free energy methods have not yet outperformed faster scoring methods in blinded protein-ligand affinity predictions.
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