Curated Antibody Binding Affinity Datasets (AbCDR-Binding)
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This dataset contains six curated antibody-antigen binding affinity datasets, as used in the paper Preferential CDR masking in paired antibody language models improves binding affinity prediction".Contents:Six binding affinity datasets covering diverse antigen systems:D44 dataset (N=2,048): Single-point mutants of anti-lysozyme antibody D44.1G6 dataset (N=4,275): Single-point mutants of anti-lysozyme antibody HyHEL-10Trastuzumab dataset (N=422): Single-point mutants of therapeutic anti-HER2 antibodyanti-Fluorescein dataset (N=11,052): Single and combinatorial mutants binding to fluoresceinanti-H1 Hemagglutinin dataset (N=1,038): Single and combinatorial mutants targeting influenza H1anti-HR2 SARS-CoV-2 dataset (N=71,830): Combinatorial mutants targeting SARS-CoV-2 spike protein Data sources:D44, G6: Koenig et al. (2017), Warszawski et al. (2019)Trastuzumab: Shanehsazzadeh et al. (2023)anti-Fluorescein: Adams et al. (2016)anti-H1 Hemagglutinin: Petersen et al. (2024)anti-HR2 SARS-CoV-2: Lim et al. (2023) CitationIf you use this dataset, please cite both the original data sources and our publication: Talaei, M., Walker, K. C., Hao, B., Jolley, E., Jin, Y., Kozakov, D., Misasi, J., Vajda, S., Paschalidis, I. Ch., & Joseph-McCarthy, D. (2025). Preferential CDR masking in paired antibody language models improves binding affinity prediction. bioRxiv. DOI: 10.1101/2025.10.31.685149
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Publication Details
Subfield
Radiology, Nuclear Medicine and Imaging
Field
Medicine
Domain
Health Sciences
Confidence Score
52%
Source
Scholar Data Model