Skip to main content

Advertisement

Table 16 Mean Δ EF and standard deviation using the best α coefficients (approach B2)

From: Improving structural similarity based virtual screening using background knowledge

  MCS ext ECFP ext
DuD set 1% 5% 10% 1% 5% 10%
HMGR 6.1 ± 10.5 2.1 ± 0.9 0.8 ± 0.4 2.7 ± 6.8 4.3 ± 5.6 1.5 ± 2.5
ER 8.1 ± 6.1 10.4 ± 2.9 4.6 ± 1.5 6.3 ± 5.4 10.0 ± 2.0 4.2 ± 1.3
PPAR γ 4.6 ± 10.6 3.9 ± 5.5 1.7 ± 2.8 4.1 ± 10.7 3.5 ± 5.6 1.7 ± 2.5
P38 MAP 5.4 ± 6.4 5.4 ± 3.4 1.4 ± 0.1 3.9 ± 5.7 6.7 ± 3.8 1.4 ± 0.1
TK 17.4 ± 5.2 11.4 ± 4.8 4.7 ± 1.6 16.5 ± 8.4 11.4 ± 3.5 4.6 ± 2.1
FXa 3.5 ± 11.2 5.7 ± 5.1 2.5 ± 2.6 3.5 ± 11.0 5.0 ± 5.2 2.2 ± 2.6
ADA 9.7 ± 5.4 7.2 ± 2.6 2.4 ± 1.1 7.3 ± 7.2 6.9 ± 2.7 2.4 ± 1.0
DHFR 3.0 ± 6.0 0.8 ± 1.6 0.0 ± 0.0 2.4 ± 1.2 0.4 ± 0.9 0.0 ± 0.0
ACHE 10.1 ± 12.0 9.6 ± 5.8 4.5 ± 2.9 11.2 ± 12.2 9.4 ± 5.9 4.4 ± 2.8
COX-2 12.0 ± 10.3 10.8 ± 6.3 2.8 ± 2.8 6.7 ± 10.3 5.5 ± 4.9 2.2 ± 2.6
w/d/l 9 / 1 / 0 9 / 0 / 1 9 / 1 / 0 8 / 0 / 2 4 / 0 / 6 8 / 0 / 2
  1. Mean Δ EF and standard deviation using the best α coefficients for extended similarites MCS ext and ECFP ext for the receptor specific decoy sets DuD set at 1%, 5% and 10% of the database. The extension fingerprint is calculated from 10% (20% for HMGR, TK and ADA) of the ligands (approach B2). Improvements of MCS ext compared to MCS as well as ECFP ext compared to ECFP are marked in bold print. w/d/l = wins/draws/losses.