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Table 3 DeepFrag-k and ProFold folds classifications accuracies for DD-dataset

From: DeepFrag-k: a fragment-based deep learning approach for protein fold recognition

# Fold ID Fold Name DeepFrag-k Accuracy ProFold Accuracy
1 a.1 Globin-like 98.0 100.0
2 a.3 Cytochrome c 95.0 100.0
3 a.4 DNA/RNA-binding 3-helical bundle 85.9 60.0
4 a.24 4-Helical up-and-down bundle 91.5 87.5
5 a.26 4-Helical cytokines 98.9 88.9
6 a.39 EF hand-like 90.8 77.8
7 b.1 Immunoglobulin-like β-sandwich 91.1 84.1
8 b.6 Cupredoxin-like 78.7 66.7
9 b.121 Nucleoplasmin-like/VP 91.3 92.3
10 b.29 ConA-like lectins/glucanases 76.7 66.7
11 b.34 SH3-like barrel 78.0 50.0
12 b.40 OB-Fold 80.4 68.4
13 b.42 β-Trefoil 89.0 100.0
14 b.47 Trypsin-like serine proteases 75.0 50.0
15 b.60 Lipocalins 90.5 100.0
16 c.1 TIM β/α-barrel 93.8 93.8
17 c.2 FAD/NAD(P)-binding domain 89.7 91.7
18 c.3 Flavodoxin-like 60.2 46.2
19 c.23 NAD(P)-binding Rossmann 90.2 85.2
20 c.37 P-loop containing NTH 79.5 50.0
21 c.47 Thioredoxin-fold 97.5 87.5
22 c.55 Ribonuclease H-like motif 75.3 58.3
23 c.69 α/β-Hydrolases 78.4 71.4
24 c.93 Periplasmic binding protein-like 92.0 100.0
25 d.15 β-Grasp (ubiquitin-like) 69.4 25.0
26 d.58 Ferredoxin-like 76.8 59.3
27 g.3 Knottins (small inhibitors, toxins, lectins) 88.2 96.3
Accuracy    85.3 76.2