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Paper-reported evidence

DEELIG: A Deep Learning Approach to Predict Protein-Ligand Binding Affinity

2021 · Peer-reviewed · PMC archival version PMC8274096.1

Paper-reported results. The values below come from this source, not an independent rewire.it run.

Open primary paper →DOI: 10.1177/11779322211030364

Primary full text verified using Europe PMC XML; venue: Bioinformatics and Biology Insights; PMC ID: PMC8274096.

2 verified numerical rows · source checked 2026-09-15

Paper-reportedAuthor's model

DEELIG

Protein–ligand binding affinity prediction

Reported score
0.889
Metric
Pearson R
Dataset / split
PDBbind core v2016 v2016

Source paper reports DEELIG on PDBbind core set.

Table 2, DEELIG row, PDBbind v2016 columnVerify at source →
Paper-reportedCompiled from another paper

TOPBP (Complex)

Protein–ligand binding affinity prediction

Reported score
0.861
Metric
Pearson R
Dataset / split
PDBbind core v2016 v2016

Source table compiles a previously published comparator; protocol equivalence is not established.

Table 2, TOPBP (Complex) row, PDBbind v2016 columnVerify at source →