Skip to main content

Table 4 Comparison of the predictive performance of Pep-3D-Search with different distance parameters (CA).

From: Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis

PDB ID

1jrh

1bj1

1g9m

1e6j

1n8z

1iqd

1yy9

2adf

1avz

1hx1

Average

CA (distance threshold = 6.5)

TP/PE

5/5

2/10

13/42

10/43

18/36*

7/31

2/10*

0/20

12/31

13/31

 

MCC

0.1119

-0.0014

0.1887

0.2033

0.1664

0.1015

0.019

-0.0367

0.262

0.1889

0.1204

Sensitivity

1.0

0.2

0.3095

0.2326

0.5

0.2258

0.2

0.0

0.3871

0.4194

0.3474

Precision

0.2381

0.1053

0.8667

0.9091

0.9

0.4375

0.1333

0.0

0.75

0.5417

0.4882

CA (distance threshold = 7)

TP/PE

19/40

7/13*

10/39

11/36

20/35*

6/47

10/25

12/36

10/39

13/39

 

MCC

0.3902

0.1442

0.1394

0.2285

0.1856

0.0356

0.1030

0.2153

0.1643

0.152

0.1758

Sensitivity

0.475

0.5833

0.2564

0.3056

0.5714

0.1277

0.4

0.3333

0.2564

0.3333

0.3642

Precision

0.9048

0.3684

0.6667

1.0

1.0

0.375

0.6667

0.8

0.625

0.5417

0.6948

CA (distance threshold = 7.5)

TP/PE

19/38

12/27*

10/45

9/33

18/40

0/36

7/25

12/36

9/37

9/36

 

MCC

0.3947

0.2349

0.1374

0.1812

0.1662

-0.0895

0.0704

0.2153

0.1332

0.0411

0.1485

Sensitivity

0.5

0.4444

0.2222

0.2727

0.45

0.0

0.28

0.3333

0.2432

0.25

0.2996

Precision

0.9048

0.6316

0.6667

0.8182

0.9

0.0

0.4667

0.8

0.5625

0.375

0.6126

CA (distance threshold = 8)

TP/PE

20/39

12/28*

10/40

10/35

17/36

0/37

5/26

13/35

8/39

5/32

 

MCC

0.4248

0.2309

0.1391

0.2047

0.1565

-0.1144

0.0484

0.2378

0.0822

-0.065

0.1345

Sensitivity

0.5128

0.4286

0.25

0.2857

0.4722

0.0

0.1923

0.3714

0.2051

0.1563

0.2874

Precision

0.9524

0.6316

0.6667

0.9091

0.85

0.0

0.3333

0.8667

0.5

0.2083

0.5918

  1. TP: number of true positives; PE: number of residues in the predicted epitope; TN: number of true negatives; FP: number of false positives; FN: number of false negatives; Matthews correlation coefficient ( MCC ) = ( T P â‹… T N ) − ( F P â‹… F N ) ( T P + F P ) ( T P + T N ) ( T N + F P ) ( T N + F N ) MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaeiikaGIaeeyta0Kaee4qamKaee4qamKaeiykaKIaeyypa0tcfa4aaSaaaeaacqGGOaakcqWGubavcqWGqbaucqGHflY1cqWGubavcqWGobGtcqGGPaqkcqGHsislcqGGOaakcqWGgbGrcqWGqbaucqGHflY1cqWGgbGrcqWGobGtcqGGPaqkaeaadaGcaaqaaiabcIcaOiabdsfaujabdcfaqjabgUcaRiabdAeagjabdcfaqjabcMcaPiabcIcaOiabdsfaujabdcfaqjabgUcaRiabdsfaujabd6eaojabcMcaPiabcIcaOiabdsfaujabd6eaojabgUcaRiabdAeagjabdcfaqjabcMcaPiabcIcaOiabdsfaujabd6eaojabgUcaRiabdAeagjabd6eaojabcMcaPaqabaaaaaaa@613F@ ; Sensitivity  ( Se ) = T P T P + F N MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaee4uamLaeeyzauMaeeOBa4Maee4CamNaeeyAaKMaeeiDaqNaeeyAaKMaeeODayNaeeyAaKMaeeiDaqNaeeyEaKNaeeiiaaIaeiikaGIaee4uamLaeeyzauMaeiykaKIaeyypa0tcfa4aaSaaaeaacqWGubavcqWGqbauaeaacqWGubavcqWGqbaucqGHRaWkcqWGgbGrcqWGobGtaaaaaa@4963@ ; Precision  ( Pr ) = T P T P + F P MathType@MTEF@5@5@+=feaagaart1ev2aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaeeiuaaLaeeOCaiNaeeyzauMaee4yamMaeeyAaKMaee4CamNaeeyAaKMaee4Ba8MaeeOBa4MaeeiiaaIaeiikaGIaeeiuaaLaeeOCaiNaeiykaKIaeyypa0tcfa4aaSaaaeaacqWGubavcqWGqbauaeaacqWGubavcqWGqbaucqGHRaWkcqWGgbGrcqWGqbauaaaaaa@466F@ .
  2. *For the cases, the best prediction was found in the second-ranked candidate.