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 3 Accuracy metrics for antagonist 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	6533	CERAPP consensus	0.15	0.91	0.53	0.88	0.55	0.26
1	6533	Morgan kNN arithm k = 3	0.04	0.99	0.52	0.95	0.53	0.26
1	6533	Morgan kNN geom k = 3	0.00	1.00	0.50	0.96	0.51	0.24
1	6533	Morgan kNN exp k = 3 X = 1.5	0.04	0.99	0.52	0.95	0.53	0.26
1	6533	Indigo kNN arithm k = 10	0.04	0.99	0.52	0.95	0.57	0.28
1	6533	Indigo kNN geom k = 10	0.00	1.00	0.50	0.96	0.50	0.24
1	6533	Indigo kNN exp k = 10 X = 1.5	0.05	0.99	0.52	0.95	0.57	0.28
1	6533	Indigo GkNN k = 10 X = 3 Y = 7	0.10	0.98	0.54	0.94	0.57	0.29
1	6533	Indigo GkNN k = 10 X = 5 Y = 15	0.10	0.98	0.54	0.94	0.57	0.29
3	1707	CERAPP consensus	0.17	0.90	0.53	0.87	0.58	0.27
3	1707	Morgan kNN arithm k = 3	0.09	0.99	0.54	0.95	0.57	0.29
3	1707	Morgan kNN geom k = 3	0.00	1.00	0.50	0.95	0.53	0.25
3	1707	Morgan kNN exp k = 3 X = 1.5	0.10	1.00	0.55	0.96	0.57	0.30
3	1707	Indigo kNN arithm k = 10	0.12	1.00	0.56	0.96	0.65	0.35
3	1707	Indigo kNN geom k = 10	0.00	1.00	0.50	0.95	0.50	0.24
3	1707	Indigo kNN exp k = 10 X = 1.5	0.14	1.00	0.57	0.96	0.65	0.36
3	1707	Indigo GkNN k = 10 X = 3 Y = 7	0.18	0.99	0.58	0.95	0.65	0.36
3	1707	Indigo GkNN k = 10 X = 5 Y = 15	0.18	0.99	0.58	0.95	0.65	0.36
5	431	CERAPP consensus	0.24	0.89	0.56	0.84	0.67	0.32
5	431	Morgan kNN arithm k = 3	0.14	0.99	0.56	0.93	0.61	0.32
5	431	Morgan kNN geom k = 3	0.00	1.00	0.50	0.93	0.52	0.24
5	431	Morgan kNN exp k = 3 X = 1.5	0.17	1.00	0.58	0.94	0.61	0.34
5	431	Indigo kNN arithm k = 10	0.10	1.00	0.55	0.94	0.65	0.33
5	431	Indigo kNN geom k = 10	0.00	1.00	0.50	0.93	0.50	0.23
5	431	Indigo kNN exp k = 10 X = 1.5	0.10	1.00	0.55	0.94	0.65	0.33
5	431	Indigo GkNN k = 10 X = 3 Y = 7	0.17	0.99	0.58	0.93	0.65	0.35
5	431	Indigo GkNN k = 10 X = 5 Y = 15	0.17	0.99	0.58	0.93	0.65	0.35
7	103	CERAPP consensus	0.31	0.91	0.61	0.84	0.67	0.34
7	103	Morgan kNN arithm k = 3	0.23	0.98	0.60	0.88	0.68	0.36
7	103	Morgan kNN geom k = 3	0.00	1.00	0.50	0.87	0.54	0.24
7	103	Morgan kNN exp k = 3 X = 1.5	0.23	1.00	0.62	0.90	0.68	0.38
7	103	Indigo kNN arithm k = 10	0.08	1.00	0.54	0.88	0.79	0.38
7	103	Indigo kNN geom k = 10	0.00	1.00	0.50	0.87	0.50	0.22
7	103	Indigo kNN exp k = 10 X = 1.5	0.15	0.98	0.57	0.87	0.80	0.39
7	103	Indigo GkNN k = 10 X = 3 Y = 7	0.23	0.98	0.60	0.88	0.80	0.43
7	103	Indigo GkNN k = 10 X = 5 Y = 15	0.31	0.99	0.65	0.90	0.80	0.47
9	46	CERAPP consensus	0.40	1.00	0.70	0.87	0.73	0.44
9	46	Morgan kNN arithm k = 3	0.30	0.97	0.64	0.83	0.73	0.38
9	46	Morgan kNN geom k = 3	0.00	1.00	0.50	0.78	0.55	0.22
9	46	Morgan kNN exp k = 3 X = 1.5	0.30	1.00	0.65	0.85	0.73	0.40
9	46	Indigo kNN arithm k = 10	0.10	1.00	0.55	0.80	0.79	0.35
9	46	Indigo kNN geom k = 10	0.00	1.00	0.50	0.78	0.50	0.20
9	46	Indigo kNN exp k = 10 X = 1.5	0.20	0.97	0.59	0.80	0.79	0.37
9	46	Indigo GkNN k = 10 X = 3 Y = 7	0.30	0.97	0.64	0.83	0.80	0.42
9	46	Indigo GkNN k = 10 X = 5 Y = 15	0.40	1.00	0.70	0.87	0.80	0.49

“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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