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Table 2 The average accuracy and success rate by MODPEP2.0, PEP-FOLD, ETKDG, and mETKDG for the peptides with different length ranges when an ensemble of 100 conformations were considered for each peptide. The numbers in bold fonts indicate the best performances for the corresponding length ranges

From: Efficient 3D conformer generation of cyclic peptides formed by a disulfide bond

Cyclic Peptide

cRMSD (Ã…)

Success Rate (%)

Length

Number

MODPEP2.0

PEP-FOLD\(^\mathrm{a}\)

ETKDG\(^\mathrm{b}\)

mETKDG\(^\mathrm{c}\)

MODPEP2.0

PEP-FOLD

ETKDG

mETKDG

( 0, 10]

35

0.70

1.89

1.68

1.57

100.00

66.67

77.14

85.71

(10, 15]

83

1.28

2.19

2.70

2.44

90.36

65.06

38.55

56.10

(15, 20]

37

2.34

2.85

3.89

3.55

64.86

51.35

20.00

22.86

(20, 25]

32

2.64

3.65

5.98

4.69

65.62

28.12

0.00

0.00

(25, 30]

6

3.22

4.63

5.20

5.26

33.33

33.33

0.00

0.00

ALL

193

1.66

2.62

3.16

2.72

81.35

54.95

37.50

50.00

  1. \(^{\mathrm{a}}\)The data of PEP-FOLD is based on the 182 cyclic peptides from 9 to 30 in length because PEP-FOLD cannot model 11 cyclic peptides with less than nine aa
  2. \({^{\mathrm{b}}}\)The data of ETKDG is based on the 176 cyclic peptides modeled because ETKDG cannot model 17 cyclic peptides in the test set
  3. \({^{\mathrm{c}}}\)The data of mETKDG is based on the 168 cyclic peptides modeled because mETKDG cannot model 25 cyclic peptides in the test set
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Journal of Cheminformatics

ISSN: 1758-2946

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