title: Evaluation of DOCK 6 as a pose generation and database enrichment tool.
abstract: In conjunction with the recent American Chemical Society symposium titled "Docking and Scoring: A Review of Docking Programs" the performance of the DOCK6 program was evaluated through (1) pose reproduction and (2) database enrichment calculations on a common set of organizer-specified systems and datasets (ASTEX, DUD, WOMBAT). Representative baseline grid score results averaged over five docking runs yield a relatively high pose identification success rate of 72.5 % (symmetry corrected rmsd) and sampling rate of 91.9 % for the multi site ASTEX set (N = 147) using organizer-supplied structures. Numerous additional docking experiments showed that ligand starting conditions, symmetry, multiple binding sites, clustering, and receptor preparation protocols all affect success. Encouragingly, in some cases, use of more sophisticated scoring and sampling methods yielded results which were comparable (Amber score ligand movable protocol) or exceeded (LMOD score) analogous baseline grid-score results. The analysis highlights the potential benefit and challenges associated with including receptor flexibility and indicates that different scoring functions have system dependent strengths and weaknesses. Enrichment studies with the DUD database prepared using the SB2010 preparation protocol and native ligand pairings yielded individual area under the curve (AUC) values derived from receiver operating characteristic curve analysis ranging from 0.29 (bad enrichment) to 0.96 (good enrichment) with an average value of 0.60 (27/38 have AUC ≥ 0.5). Strong early enrichment was also observed in the critically important 1.0-2.0 % region. Somewhat surprisingly, an alternative receptor preparation protocol yielded comparable results. As expected, semi-random pairings yielded poorer enrichments, in particular, for unrelated receptors. Overall, the breadth and number of experiments performed provide a useful snapshot of current capabilities of DOCK6 as well as starting points to guide future development efforts to further improve sampling and scoring.
authors.affiliation: BioMaPS Institute and Department of Chemistry and Chemical Biology, Rutgers University, Piscataway, NJ 08854, USA.
authors.forename: Scott R
authors.initials: SR
authors.lastname: Brozell
authors.forename: Sudipto
authors.initials: S
authors.lastname: Mukherjee
authors.forename: Trent E
authors.initials: TE
authors.lastname: Balius
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Roe
authors.forename: David A
authors.initials: DA
authors.lastname: Case
authors.forename: Robert C
authors.initials: RC
authors.lastname: Rizzo
mesh_terms: D001665:Binding Sites; D030562:Databases, Protein; D008024:Ligands; D008958:Models, Molecular; D011485:Protein Binding; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D008024:Ligands; D011506:Proteins