Exploring non-linear distance metrics in the structure–activity space: QSAR models for human estrogen receptor

Balabin, Ilya A.; Judson, Richard S.

doi:10.1186/s13321-018-0300-0

Journal of Cheminformatics

Table 2 Accuracy metrics for agonist activity evaluation with different numbers of activity sources per chemical

From: Exploring non-linear distance metrics in the structure–activity space: QSAR models for human estrogen receptor

# sources	# chemicals	Model and parameters	Sensitivity	Specificity	Bal accuracy	Accuracy	ROC AUC	Score
1	6197	CERAPP consensus	0.71	0.95	0.83	0.94	0.85	0.67
1	6197	Morgan kNN arithm k = 10	0.55	0.96	0.75	0.94	0.82	0.58
1	6197	Morgan kNN geom k = 2	0.38	0.99	0.69	0.97	0.72	0.48
1	6197	Morgan kNN exp k = 10 X = 1.5	0.59	0.97	0.78	0.95	0.83	0.61
1	6197	Morgan GkNN k = 10 X = 1 Y = 1	0.58	0.96	0.77	0.94	0.82	0.59
1	6197	Morgan GkNN k = 10 X = 1 Y = 3	0.59	0.97	0.78	0.95	0.83	0.61
1	6197	Morgan GkNN k = 10 X = 1.5 Y = 3	0.64	0.93	0.78	0.92	0.82	0.59
1	6197	Morgan GkNN k = 20 X = 1.5 Y = 5	0.64	0.94	0.79	0.93	0.83	0.61
3	1553	CERAPP consensus	0.93	0.94	0.94	0.94	0.98	0.87
3	1553	Morgan kNN arithm k = 10	0.77	0.95	0.86	0.94	0.94	0.76
3	1553	Morgan kNN geom k = 2	0.57	0.99	0.78	0.97	0.80	0.60
3	1553	Morgan kNN exp k = 10 X = 1.5	0.82	0.97	0.89	0.96	0.95	0.81
3	1553	Morgan GkNN k = 10 X = 1 Y = 1	0.82	0.96	0.89	0.95	0.94	0.79
3	1553	Morgan GkNN k = 10 X = 1 Y = 3	0.83	0.97	0.90	0.96	0.95	0.82
3	1553	Morgan GkNN k = 10 X = 1.5 Y = 3	0.88	0.93	0.90	0.92	0.95	0.79
3	1553	Morgan GkNN k = 20 X = 1.5 Y = 5	0.88	0.94	0.91	0.94	0.94	0.80
5	456	CERAPP consensus	0.96	0.93	0.94	0.94	0.99	0.88
5	456	Morgan kNN arithm k = 10	0.81	0.94	0.88	0.93	0.94	0.77
5	456	Morgan kNN geom k = 2	0.68	1.00	0.84	0.96	0.86	0.69
5	456	Morgan kNN exp k = 10 X = 1.5	0.92	0.97	0.94	0.96	0.96	0.87
5	456	Morgan GkNN k = 10 X = 1 Y = 1	0.89	0.95	0.92	0.94	0.95	0.82
5	456	Morgan GkNN k = 10 X = 1 Y = 3	0.92	0.97	0.94	0.96	0.96	0.87
5	456	Morgan GkNN k = 10 X = 1.5 Y = 3	0.94	0.92	0.93	0.92	0.96	0.82
5	456	Morgan GkNN k = 20 X = 1.5 Y = 5	0.94	0.95	0.94	0.95	0.96	0.86
7	128	CERAPP consensus	0.95	0.95	0.95	0.95	1.00	0.90
7	128	Morgan kNN arithm k = 10	0.88	0.98	0.93	0.95	0.95	0.84
7	128	Morgan kNN geom k = 2	0.76	1.00	0.88	0.94	0.90	0.74
7	128	Morgan kNN exp k = 10 X = 1.5	0.91	0.99	0.95	0.97	0.96	0.89
7	128	Morgan GkNN k = 10 X = 1 Y = 1	0.94	0.99	0.97	0.98	0.96	0.90
7	128	Morgan GkNN k = 10 X = 1 Y = 3	0.94	1.00	0.97	0.98	0.97	0.92
7	128	Morgan GkNN k = 10 X = 1.5 Y = 3	0.94	0.91	0.93	0.92	0.96	0.82
7	128	Morgan GkNN k = 20 X = 1.5 Y = 5	0.94	0.97	0.95	0.96	0.97	0.89
9	57	CERAPP consensus	0.92	1.00	0.96	0.97	1.00	0.93
9	57	Morgan kNN arithm k = 10	0.79	1.00	0.89	0.93	0.93	0.78
9	57	Morgan kNN geom k = 2	0.79	1.00	0.89	0.93	0.92	0.77
9	57	Morgan kNN exp k = 10 X = 1.5	0.84	1.00	0.92	0.95	0.94	0.82
9	57	Morgan GkNN k = 10 X = 1 Y = 1	0.84	1.00	0.92	0.95	0.94	0.82
9	57	Morgan GkNN k = 10 X = 1 Y = 3	0.84	1.00	0.92	0.95	0.94	0.82
9	57	Morgan GkNN k = 10 X = 1.5 Y = 3	0.89	0.92	0.91	0.91	0.94	0.78
9	57	Morgan GkNN k = 20 X = 1.5 Y = 5	0.89	0.97	0.93	0.95	0.94	0.84

“kNN arithm”, “kNN geom”, and “kNN exp” indicate the kNN models with the arithmetic, geometric, and exponential averaging, respectively. The cumulative score shown in the last column is the product of balanced accuracy, accuracy, and ROC AUC. Italic font indicates accuracy metric values that exceed those for the CERAPP consensus model

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