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Table 2 Performance of the DeepTGIN model

From: DeepTGIN: a novel hybrid multimodal approach using transformers and graph isomorphism networks for protein-ligand binding affinity prediction

Models

R(\(\uparrow\))

RMSE(\(\downarrow\))

MAE(\(\downarrow\))

SD(\(\downarrow\))

CI(\(\uparrow\))

Training

0.927

0.693

0.539

0.690

0.881

Validation

0.736

1.277

0.981

1.254

0.768

PDBbind2016 test set

0.834

1.203

0.949

1.197

0.823

PDBbind2013 test set

0.787

1.388

1.123

1.386

0.792

  1. \(\uparrow\) indicates that larger values indicate better performance, while \(\downarrow\) indicates that smaller values indicate better performance
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Journal of Cheminformatics

ISSN: 1758-2946

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