Chaos-embedded particle swarm optimization approach for protein-ligand docking and virtual screening

Table 3 Number of actives and decoys in the DUD-E datasets for virtual screening test after preprocessing

Target	Type	Active	Decoy	Failed active\(^{\mathrm{a}}\)	Failed decoy\(^{\mathrm{a}}\)
(a) DIV8: Diverse target subset
akt1	Kinase	293	16,448	0	2
ampc	Enzyme	48	2850	0	0
cp3a4	Cytochrome	170	11,798	0	2
cxcr4	G protein-coupled receptor	40	3414	0	0
gcr	Nuclear receptor	258	14,996	0	4
hivpr	Protease	536	35,743	0	7
hivrt	Enzyme	337	18,887	1	4
kif11	Other	116	6847	0	3
Total		1794	110,983	1	22

Target	Type	Active	Decoy	Failed active\(^{\mathrm{a}}\)	Failed decoy\(^{\mathrm{a}}\)
(b) NR11: Nuclear receptor target subset
andr	Androgen receptor	269	14,349	0	1
esr1	Estrogen receptor alpha	383	20,685	0	0
esr2	Estrogen receptor beta	367	20,199	0	0
gcr	Glucocorticoid receptor	258	14,996	0	4
mcr	Mineralocorticoid receptor	94	5150	0	0
ppara	Peroxisome proliferator-activated receptor alpha	373	19,399	0	0
ppard	Peroxisome proliferator-activated receptor delta	240	12,250	0	0
pparg	Peroxisome proliferator-activated receptor gamma	484	25,298	0	2
prgr	Progesterone receptor	293	15,814	0	0
rxra	Retinoid X receptor alpha	131	6950	0	0
thb	Thyroid hormone receptor beta-1	103	7450	0	0
Total		2995	162,540	0	7

\(^{\mathrm{a}}\)Actives and decoys which failed to pass all the preprocessing steps were not included in the virtual screening experiments

ISSN: 1758-2946