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. 2014 Oct 29;31(5):707–713. doi: 10.1093/bioinformatics/btu724

Table 5.

Comparison with two existing methods

Ligands AMP ATP FMN GLC NAD ACR
Number of pocketsa 43/46 38/44 48/49 15/27 38/39 5/8

Rel. P-S2.0 2.94 3.93 4.47 2.24 11.15 12.39
pAUC eFSeekb 0.12 0.18 0.61 2.04 0.24 7.50
AUC P-S2.0 0.74 0.78 0.80 0.61 0.88 0.88
APocc 0.64 0.75 0.76 0.45 0.88 0.64

ADN ANP BCN GLO HEC MLT MPO PLP PMP

14/15 33 4/6 5/6 12/13 15/18 7 29/30 6/7

2.64 5.10 2.95 26.6 14.1 3.05 2.73 7.10 3.27
0.52 0.31 8.35 9.86 2.02 1.13 0.76 0.64 0.25
0.69 0.81 0.79 0.93 0.85 0.65 0.66 0.80 0.72
0.61 0.77 0.48 0.81 0.68 0.43 0.36 0.66 0.90

aThe number of query pockets used for the comparison with eF-Seek (left) and Apoc (right). The numbers are different because common entries between the pocket databases by Patch-Surfer2.0 and eF-Seek were used as queries. Only one number is shown when the number were the same for eF-Seek and Apoc. The average AUC of receiver operator characteristic of the number of queries are shown.

bFor the performance comparison with eF-Seek, we computed partial AUC (pAUC) that is the AUC computed up to the maximum false-positive rate (FPR) against the pAUC of the random retrieval up to the same FPR. Thus, rel_pAUC = pAUC/pAUCrandom where pAUC = AUC/(1.0*maxFPR).

cAPoc was run locally using the same database as Patch-Surfer2.0.