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Table 20 Win/loss counts for all random folds for extended similarites on DuD set ( α ∈ (0.0, 0.1); approach B2)

From: Improving structural similarity based virtual screening using background knowledge

 

     ECFP ext

     MCS ext

 

     c1%

     5%

     10%

     1%

     5%

     10%

 

Win

Loss

Win

Loss

Win

Loss

Win

Loss

Win

Loss

Win

Loss

HMGR

102

8

88

22

98

12

48

7

49

6

55

0

ER

70

40

74

36

74

36

87

23

89

21

67

43

PPAR γ

93

17

86

24

88

22

69

41

95

15

72

38

P38 MAP

93

17

96

14

103

7

93

17

100

10

110

0

TK

75

35

95

15

94

16

96

14

85

25

82

28

FXa

101

9

67

43

80

30

99

11

84

26

83

27

ADA

86

24

79

31

98

12

60

39

88

11

76

23

DHFR

75

35

107

3

110

0

100

10

110

0

110

0

ACHE

86

24

95

15

96

14

87

23

98

12

94

16

COX-2

69

41

76

34

78

32

65

45

86

24

90

20

Sum

850

250

863

237

919

181

804

230

884

150

839

195

  1. Win/loss counts for all 110 random folds (10 repetitions * 11 αs) for extended similarites MCS ext and ECFP ext versus their base similarities MCS and ECFP 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).
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Journal of Cheminformatics

ISSN: 1758-2946

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