Exploration of Drug Science

From: Heterogeneous graph convolutional neural network for protein-ligand scoring

Table 7. Metrics computed on the CASF 2013

Method	Trained on PDBbind	N	R_p↑	SD↓	MAE↓	RMSE↓
GoldScore^a [24]	-	195	0.48	1.97	-	-
ChemScore^b [24]	-	195	0.59	1.82	-	-
X-Score^HM [24]	-	195	0.61	1.78	-	-
DeepBindRG [5]	2018	195	0.64	-	1.48	1.82
Pafnucy [4]	2016	195	0.70	1.61	-	1.62
OnionNet [7]	2016	108	0.78	1.45	1.21	1.50
AGL-Score^c [8]	2007 (refined)	195	0.79	-	-	1.97
IGN^c [10]	2016	85	0.83	-	-	-
HGScore	2016	195	0.79	1.39	1.11	1.39

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The scoring function was used with the software ^a Gold and ^b Sybyl. ^c the number of tested complexes is too low to be compared with the other methods. ↑ indicates that the larger the value, the better; ↓ indicates that the smaller the value, the better. N is the number of tested complexes, some methods have been tested only on a subset of the benchmark. -: not applicable

Declarations

Acknowledgments

The authors thank the supercomputer center ROMEO for providing CPU-GPU times.

Author contributions

KC: Conceptualization, Software, Writing—original draft, Writing—review & editing. AG: Software, Writing— review & editing, Supervision. XV, SB, and LAS: Writing—review & editing, Supervision. All authors read and approved the submitted version.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

The datasets analyzed for this study can be found in the PDBbind website http://pdbbind.org.cn/.

Funding

This work was supported by the Association Nationale de la Recherche et de la Technologie (ANRT) through a CIFRE grant [2020/0691]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

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