Most of the functionality available in OEDocking is also available in toolkit form via the OEDocking TK.
POSIT - Ligand guided pose prediction
POSIT is designed to use bound ligand information to improve pose prediction. Using a combination of OpenEye approaches, including structure generation, shape alignment and flexible fitting, it produces a predicted pose whose accuracy depends on similarity measures to known ligand poses. As such, it produces a reliability estimate for each predicted pose - an industry first.
The estimate is computed using both the 2D and the 3D similarity of the ligand being fit to the known bound ligand. In addition, if provided with a selection of receptors from a crystallographic series, POSIT will automatically determine which receptor is best suited for pose prediction.
FRED - Fast exhaustive docking
FRED is a fast and effective docking application whose performance is significantly more reliable, i.e. lower variance, than most other programs [1,2].
FRED performs a systematic, exhaustive, nonstochastic examination of all possible poses within the protein active site, filters for shape complementarity  and pharmacophoric features before selecting and optimizing poses using the Chemgauss4 scoring function.
HYBRID - Ligand guided docking
HYBRID is a docking program that can utilize bound ligand information in a seamless manner. Like FRED, HYBRID performs a systematic, exhaustive, nonstochastic examination of all possible poses within the protein active site; however, instead of filtering the poses based on their shape complementarity to the active site, they are filtered on their shape and chemical complementarity to a known bound ligand. This ligand-guided docking provides statistically improved enrichment compared to many docking tools .
- "FRED Pose Prediction and Virtual Screening Accuracy", M. McGann, J. Chem. Inf. Model., 2011, 51 (3), 578-596
- "Comparison of Topological, Shape, and Docking Methods in Virtual Screening", G.B. McGaughey, R.P. Sheridan, C.I. Bayly, J.C. Culberson, C. Kreatsolas, S. Lindsley, V. Maiorov, J.-F. Truchon and W.D. Cornell, J. Chem. Inf. Model., 2007, 47 (4), 1504-1519
- "Gaussian docking functions", M.R. McGann, H.R. Almond, A. Nicholls, J.A. Grant and F.K. Brown, Biopolymers, 2003, 68 (1), 76-90