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Table 3 Comparison of the scoring powers of BsN-Score, BgN-Score, SNN-Score, Random Forests (RF), and the four top performing conventional SFs on four protein-family-specific tests sets.

From: BgN-Score and BsN-Score: Bagging and boosting based ensemble neural networks scoring functions for accurate binding affinity prediction of protein-ligand complexes

HIV protease (N= 112)

Trypsin (N= 73)

Scoring function

R p 1

R s 2

SD 3

RMSE4

D5

Scoring function

R p 1

R s 2

SD 3

RMSE4

D5

X-Score::HPScore

0.341

0.339

1.54

1.509

N

SYBYL::ChemScore

0.829

0.773

0.95

-

U

BsN::XARG

0.290

0.230

1.56

1.705

Y

DS::Ludi2

0.823

0.791

0.96

-

U

RF::XARG

0.289

0.219

1.519

1.719

Y

X-Score::HSScore

0.817

0.824

0.97

1.401

N

BgN-Score::XARG

0.287

0.209

1.58

1.860

Y

DS::PLP2

0.797

0.774

1.02

-

U

SYBYL::ChemScore

0.255

0.228

1.58

-

U

BgN-Score::XAR

0.776

0.719

1.06

1.070

Y

DrugScore::PairSurf

0.225

0.170

1.59

-

U

RF::XAR

0.774

0.753

1.07

1.133

Y

DS::PMF04

0.183

0.200

1.61

-

U

BsN-Score::AR

0.766

0.709

1.08

1.119

Y

SNN-Score::X

0.039

0.048

1.64

2.255

Y

SNN-Score::X

0.735

0.672

1.14

1.209

Y

RF::XARG

0.964

0.975

0.44

0.588

N

BsN-Score::XARG

0.937

0.920

0.59

0.678

N

BsN-Score::XARG

0.918

0.922

0.64

0.710

N

RF::XARG

0.934

0.08

0.60

0.657

N

BgN-Score::XARG

0.848

0.808

1.02

1.024

N

BgN-Score::XARG

0.892

0.848

0.76

0.805

N

SNN-Score::X

0.748

0.716

1.08

1.085

N

SNN-Score::X

0.829

0.789

0.940

0.957

N

Carbonic anhydrase ( N = 44)

Thrombin ( N = 38)

Scoring function

R p 1

R s 2

SD 3

RMSE 4

D 5

Scoring function

R p 1

R s 2

SD 3

RMSE 4

D 5

DS::PLP2

0.800

0.772

0.84

-

U

SNN-Score::X

0.756

0.704

1.38

1.433

Y

SYBYL::G-Score

0.706

0.646

0.99

-

U

BgN-Score::XARG

0.722

0.726

1.48

1.552

Y

SYBYL::ChemScore

0.699

0.631

1.00

-

U

BsN-Score::XARG

0.699

0.637

1.58

1.603

Y

BsN-Score::X

0.674

0.434

1.03

3.418

Y

RF::XARG

0.697

0.693

1.52

1.674

Y

SNN-Score::X

0.631

0.451

1.08

3.561

Y

DS::PLP1

0.667

0.672

1.58

-

U

SYBYL::PMF-Score

0.627

0.618

1.09

-

U

SYBYL::G-Score

0.667

0.626

1.58

-

U

BgN-Score::XA

0.625

0.423

1.09

3.642

Y

X-Score::HSScore

0.666

0.586

1.58

1.737

N

RF::XARG

0.601

0.374

1.11

3.393

Y

DrugScore::Pair

0.651

0.622

1.61

-

U

BsN-Score::XARG

0.948

0.921

0.44

1.004

N

BsN-Score::XARG

0.913

0.938

0.86

1.155

N

RF::XARG

0.910

0.860

0.57

1.140

N

RF::XARG

0.910

0.934

0.86

1.125

N

BgN-Score::XARG

0.884

0.766

0.65

1.320

N

BgN-Score::XARG

0.858

0.876

1.08

1.320

N

SNN-Score::X

0.652

0.310

1.05

1.687

N

SNN-Score::X

0.761

0.756

1.37

1.374

N

  1. 1 R p is the Pearson correlation coefficient between predicted and measured BA values of complexes in this protein-family-specific test set.
  2. 2 R s is the Spearman correlation coefficient between predicted and measured BA values of complexes in this protein-family-specific test set.
  3. 3 SD is the standard deviation of errors between predicted and measured BA values of complexes in this protein-family-specific test set.
  4. 4 RMSE is the root-mean-square of errors between predicted and measured BA values of the test complexes in in this protein-family-specific test set. Test RMSE is not available for conventional SFs except for X-Score that we have re-constructed. Training RMSE is not reported in this table because the values are very similar to RMSEtrain in Table 1 due to the overlap between the training data sets of the two experiments.
  5. 5 This indicates whether the test set complexes are disjoint from (D = Y) or overlap with (D = N) the training set complexes for NN and RF models. Any overlap between the training and test data of the conventional SFs is unknown (D = U) to us.
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BMC Bioinformatics

ISSN: 1471-2105

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