Journal of Cheminformatics

Table 5 Average AUC of ROCS_SC with multiple conformers and the 4D FAP_OA

From: 4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening

		ROCS_SC			4D FAP_OA AUC
target	AUC₁	AUC₁₀	AUC₁₀₀	AUC₁₀₀₀
ACE	0.69	0.85	0.82	0.77	0.89
AChE	0.76	0.75	0.77	0.78	0.72
ADA	0.63	0.76	0.60	0.59	0.67
ALR2	0.45	0.47	0.49	0.50	0.63
AmpC	0.77	0.86	0.88	0.88	0.90
AR	0.81	0.80	0.79	0.79	0.89
CDK2	0.78	0.70	0.69	0.67	0.75
COMT	0.32	0.27	0.33	0.34	0.97
COX-1	0.62	0.62	0.58	0.57	0.63
COX-2	0.95	0.94	0.95	0.95	0.93
DHFR	0.68	0.45	0.91	0.89	0.99
EGFr	0.81	0.82	0.95	0.95	0.98
ER_agonist	0.92	0.93	0.94	0.94	0.85
ER_antagonist	0.94	0.97	0.98	0.98	0.92
FGFr1	0.53	0.61	0.51	0.45	0.63
FXa	0.61	0.49	0.66	0.64	0.62
GART	0.43	0.50	0.77	0.84	0.82
GPB	0.84	0.93	0.94	0.94	0.97
GR	0.81	0.81	0.77	0.76	0.92
HIVPR	0.71	0.61	0.58	0.61	0.21
HIVRT	0.71	0.71	0.72	0.71	0.56
HMGR	0.76	0.90	0.94	0.93	0.97
HSP90	0.69	0.71	0.66	0.64	0.86
InhA	0.72	0.81	0.78	0.79	0.69
MR	0.83	0.86	0.86	0.85	0.91
NA	0.97	0.96	0.97	0.97	0.97
P38	0.46	0.49	0.48	0.48	0.75
PARP	0.63	0.59	0.58	0.58	0.77
PDE5	0.68	0.58	0.59	0.56	0.78
PDGFrb	0.41	0.39	0.30	0.28	0.60
PNP	0.56	0.58	0.88	0.89	0.94
PPAR_γ	0.87	0.68	0.74	0.91	0.96
PR	0.74	0.73	0.68	0.69	0.94
RXR_α	0.88	0.98	0.97	0.95	0.98
SAHH	0.96	0.96	0.98	0.98	0.98
SRC	0.51	0.50	0.39	0.34	0.53
thrombin	0.54	0.66	0.66	0.55	0.59
TK	0.68	0.84	0.88	0.89	0.87
trypsin	0.41	0.49	0.57	0.65	0.80
VEGFr2	0.61	0.54	0.44	0.39	0.64
avg. rank	3.55	3.26	2.96	3.2	2

AUC values of ROCS_SC (AUC(1)), ROCS_SC on multiple conformer data sets (AUC(10), AUC(100), and AUC(1000)), and the 4D FAP_OA on the original DUD data sets. The number in brackets indicates the number of sampled conformers. Bold values indicate the best results with respect to the data set. The last row contains the average rank of each approach on all 40 data sets with respect to the other approaches. ROCS_SC results were taken from Venkatraman et al. [21]

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