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Table 3 Performance of QRNAS on RNA Puzzle #6 models in terms of model accuracy, as compared to RNAfitme and sander from the AMBER package

From: QRNAS: software tool for refinement of nucleic acid structures

RNA Puzzle

#6 model

RMSD [Å]

INF_all

INF_nWC

Clashscore

Starting

QRNAS

RNAfitme

sander

Starting

QRNAS

RNAfitme

sander

Starting

QRNAS

RNAfitme

sander

Starting

QRNAS

RNAfitme

sander

6_blanchet_1

21.39

22.29

22.34

22.30

0.761

0.754

0.742

0.761

0.462

0.462

0.405

0.462

0.74

0.00

1.28

0.55

6_blanchet_2

20.94

21.76

21.77

21.75

0.744

0.726

0.713

0.744

0.434

0.418

0.316

0.434

0.37

0.00

0.18

0.37

6_blanchet_3

20.57

21.32

21.32

21.31

0.745

0.754

0.696

0.745

0.405

0.452

0.337

0.405

0.55

0.00

1.10

0.74

6_blanchet_4

21.46

22.21

22.24

22.22

0.763

0.752

0.724

0.763

0.418

0.434

0.372

0.418

0.55

0.18

1.47

0.55

6_blanchet_5

23.54

24.19

24.18

24.18

0.724

0.728

0.706

0.724

0.337

0.372

0.337

0.337

0.74

0.55

0.92

0.74

6_bujnicki_1

36.50

37.00

36.98

36.96

0.720

0.721

0.729

0.720

0.300

0.224

0.194

0.300

0.55

0.00

0.55

0.55

6_bujnicki_2

30.47

30.93

30.90

30.89

0.701

0.692

0.699

0.701

0.254

0.337

0.323

0.254

1.29

0.18

1.10

1.29

6_bujnicki_3

31.79

32.14

32.11

32.09

0.637

0.638

0.651

0.637

0.258

0.258

0.270

0.258

1.11

0.37

0.92

1.11

6_bujnicki_4

31.64

32.07

32.05

32.04

0.657

0.652

0.646

0.657

0.135

0.135

0.115

0.135

1.84

0.18

1.28

1.84

6_chen_1

23.89

24.30

24.29

24.29

0.673

0.676

0.690

0.673

0.200

0.183

0.237

0.200

0.37

0.00

0.37

0.37

6_chen_2

21.73

22.13

22.17

22.15

0.656

0.662

0.663

0.656

0.200

0.283

0.254

0.200

0.18

0.18

0.55

0.18

6_chen_3

23.25

23.62

23.62

23.63

0.681

0.674

0.685

0.681

0.200

0.200

0.183

0.200

0.55

0.18

0.55

0.55

6_chen_4

21.71

22.15

22.11

22.12

0.669

0.688

0.699

0.669

0.224

0.298

0.316

0.224

1.84

0.18

1.65

1.84

6_chen_5

23.17

23.56

23.52

23.53

0.672

0.676

0.676

0.669

0.224

0.149

0.183

0.224

17.51

10.69

12.29

17.14

6_das_2

13.05

13.48

13.46

13.45

0.765

0.766

0.744

0.765

0.422

0.462

0.488

0.422

20.65

0.00

10.64

20.28

6_das_3

15.26

15.57

15.54

15.54

0.756

0.755

0.750

0.756

0.488

0.513

0.422

0.488

18.79

0.18

7.89

19.90

6_das_4

11.29

11.62

11.61

11.59

0.766

0.770

0.749

0.766

0.488

0.513

0.537

0.488

28.02

4.98

15.04

28.39

6_das_5

15.29

15.58

15.57

15.56

0.782

0.796

0.789

0.782

0.488

0.537

0.474

0.488

14.74

0.00

6.97

14.56

6_dokholyan_1

25.32

26.07

26.05

26.05

0.705

0.705

0.704

0.705

0.323

0.299

0.488

0.323

11.06

0.00

6.97

11.24

6_dokholyan_2

25.92

26.58

26.57

26.55

0.703

0.718

0.706

0.703

0.298

0.270

0.239

0.298

9.40

0.00

5.50

9.22

6_dokholyan_3

25.58

26.21

26.20

26.18

0.691

0.696

0.689

0.691

0.298

0.298

0.283

0.298

9.22

0.00

5.69

9.40

6_dokholyan_4

24.27

24.95

24.95

24.93

0.708

0.691

0.725

0.708

0.338

0.338

0.299

0.338

9.59

0.00

6.42

9.95

6_dokholyan_5

22.07

22.62

22.60

22.58

0.704

0.708

0.709

0.704

0.338

0.316

0.447

0.338

10.51

0.00

7.71

10.69

average

23.05

23.58

23.57

23.56

0.712

0.713

0.708

0.712

0.327

0.337

0.365

0.327

6.96

0.78

4.22

7.02