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. 2019 Sep 15;20(18):4574. doi: 10.3390/ijms20184574

Table 2.

Consensus docking methods.

Source T a Posing b F c Consensus Strategy Analysis Ref.
DUD-E/
PDB
102/3 4 4 Standard Deviation Consensus (SDC),
Variable SDC (vSDC)
Rank/Score curves
Hit recovery count
Chaput, 2016 [121]
DUD-E 21 8 8 Gradient Boosting EF, ROCAUC Ericksen, 2017 [124]
PDBBind
DUD
228/1 Vina, AutoDock 2 Compound rejection if pose RMSD > 2.0 Å Success rate Houston, 2013 [114]
PDB 3 GAsDock 2 Multi-Objective Scoring Function Optimisation EF Kang, 2019 [108]
mTOR d Inhibitors 1 Glide 26 Linear Combination BEI Correlation Li, 2018 [119]
PDB 220 FlexX 9 Several e Compression and Accuracy Oda, 2006 [120]
DUD-E 102 Dock 3.6 15 Genetic Algorithm used to combine SF components EF, BEDROC Perez-Castillo, 2019 [116]
PDBBind 1300 7 7 RMSD-based pose consensus, multivariate linear regression Success rate Plewczynski, 2011 [115]
DUD 35 10 10 Compound rejection based on RMSD consensus level EF Poli, 2016 [112]
PDBBind 3535 11 11 Selection of representative pose with minimum RMSD Success rate Ren, 2018 [111]
PDB 100 AutoDock 11 Supervised Learning (Random Forests),
Rank-by-rank
Average RMSD,
Success rate
Teramoto, 2007 [125]
PDB
DUD
130/3 10 10 Compound rejection based on RMSD consensus level EF, ROCAUC Tuccinardi (2014) [113]
PDBBind CSAR 421 Glide 7 Support Vector Rank Regression Top pose /Top Rank Wang, 2013 [126]
PDB 4 GEMDOCK
GOLD
2 Rank-by-rank,
Rank-by-score
Rank/Score curve, GH Score, CS index Yang, 2005 [127]

a Total number of targets used in the assay; b Posing software used. If more than two software were used, than only the number is indicated; c Number of scoring functions used; d In this study, the dataset was composed of 25 mammalian target of rapamycin (mTOR) kinase inhibitors retrieved from the literature and six mTOR crystal structures retrieved from PDB; e The purpose of this study was to evaluate several different consensus strategies (e.g., rank-by-vote, rank-by-number, etc).