. 2019 Sep 16;4(14):15956–15965. doi: 10.1021/acsomega.9b01997

Table 2. Comparison of the Prediction Power of Scoring Functions with the Core Sets of PDBbind v2016 and v2013 Benchmarks^a.

scoring functions	RMSE	R
OnionNet	1.278	0.816
K_Deep¹⁷	1.27	0.82
RF-Score-v3¹⁷	1.39	0.80
Pafnucy¹²	1.42	0.78
AGL⁴³	1.271	0.833

scoring functions	SD	R
OnionNet	1.45	0.78
AGL⁴³	1.45	0.792
Pafnucy¹²	1.61	0.70
RF-Score-v3¹²	1.51	0.74
kNN-Score¹⁴	1.65	0.672
X-Score¹⁴	1.78	0.614
ChemScore¹⁴	1.82	0.592
ChemPLP¹⁴	1.84	0.579
AutoDock Vina⁹	1.90	0.54
AutoDock⁹	1.91	0.54

Detailed training and test sets used are reported in Supporting Information Table S1.

Table 2. Comparison of the Prediction Power of Scoring Functions with the Core Sets of PDBbind v2016 and v2013 Benchmarksa.