|
Adenosine Receptors Dataset
| |
---|
|
|
RMSEPint
|
|
RMSEPext
|
---|
GP Bessel
|
0.64
|
0.70
|
0.70
|
0.63
|
GP Laplacian
|
0.67
|
0.68
|
0.67
|
0.66
|
GP Norm. Polynomial (NP)
|
0.69
|
0.65
|
0.75
|
0.58
|
GP Polynomial
|
0.70
|
0.64
|
0.70
|
0.63
|
GP PUK
|
0.57
|
0.79
|
0.56
|
0.77
|
GP Radial
|
0.65
|
0.69
|
0.65
|
0.68
|
PLS
|
0.29
|
0.97
|
0.30
|
1.00
|
SVM Norm. Polynomial (NP)
|
0.70
|
0.64
|
0.73
|
0.60
|
SVM Polynomial
|
0.71
|
0.63
|
0.71
|
0.62
|
SVM Radial
|
0.68
|
0.65
|
0.70
|
0.64
|
Family QSAR
|
0.31
|
0.70
|
0.31
|
0.96
|
|
Aminergic GPCRs Dataset
| |
|
|
RMSEP
int
|
|
RMSEP
ext
|
GP Bessel
|
0.56
|
0.83
|
0.56
|
0.80
|
GP Laplacian
|
0.62
|
0.78
|
0.63
|
0.75
|
GP Norm. Polynomial (NP)
|
0.69
|
0.68
|
0.72
|
0.66
|
GP Polynomial
|
0.68
|
0.71
|
0.70
|
0.68
|
GP PUK
|
0.46
|
0.93
|
0.46
|
0.90
|
GP Radial
|
0.69
|
0.69
|
0.71
|
0.66
|
PLS
|
0.69
|
0.69
|
0.27
|
1.05
|
SVM Norm. Polynomial (NP)
|
0.69
|
0.68
|
0.72
|
0.66
|
SVM Polynomial
|
0.69
|
0.69
|
0.71
|
0.66
|
SVM Radial
|
0.69
|
0.69
|
0.72
|
0.66
|
Family QSAR
|
0.38
|
0.98
|
0.38
|
0.97
|
|
Dengue virus NS3 proteases Dataset
| |
|
|
RMSEP
int
|
|
RMSEP
ext
|
GP Bessel
|
0.91
|
0.43
|
0.92
|
0.44
|
GP Laplacian
|
0.88
|
0.54
|
0.91
|
0.50
|
GP Linear
|
0.91
|
0.45
|
0.91
|
0.48
|
GP Norm. Polynomial (NP)
|
0.88
|
0.50
|
0.91
|
0.48
|
GP Polynomial
|
0.91
|
0.42
|
0.92
|
0.44
|
GP PUK
|
0.77
|
1.10
|
0.81
|
1.13
|
GP Radial
|
0.91
|
0.45
|
0.91
|
0.45
|
PLS
|
0.90
|
0.45
|
0.91
|
0.49
|
SVM Norm. Polynomial (NP)
|
0.86
|
0.54
|
0.91
|
0.46
|
SVM Polynomial
|
0.89
|
0.46
|
0.90
|
0.51
|
SVM Radial
|
0.90
|
0.48
|
0.90
|
0.48
|
Family QSAR
|
0.29
|
1.19
|
0.48
|
1.13
|
- For the three datasets, the best models are obtained with GP, being the lowest RMSEPext and highest R20 ext values: (i) adenosine receptors: 0.58 and 0.75 with NP kernel, (ii) GPCRs: 0.66 and 0.72 with NP kernel, and (iii) Dengue virus NS3 proteases 0.44 and 0.92 with Bessel kernel. Overall, GP models for the three datasets agree with the validation criteria.
- Abbreviations: RMSEP root mean square error in prediction, Ext. external, Norm Normalized.