ArticleScientific data2022
A dataset comprised of binding interactions for 104,972 antibodies against a SARS-CoV-2 peptide.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Article
- Antibody Affinity Maturation by Yeast Mating against a Diverse Antigen Library Enhances Antibody Resistance to Viral Mutations.ACS pharmacology & translational science · 2026Article
- Protein foundation models: a comprehensive survey.Science China. Life sciences · 2026Review
- Fitness Landscape for Antibodies 2: Benchmarking Reveals That Protein AI Models Cannot Yet Consistently Predict Developability Properties.bioRxiv : the preprint server for biology · 2025Article
- Article
- Review
- AlphaBind, a domain-specific model to predict and optimize antibody-antigen binding affinity.mAbs · 2025Article
- PANCS-Binders: a rapid, high-throughput binder discovery platform.Nature methods · 2025Article
- Learning the language of antibody hypervariability.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Applying computational protein design to therapeutic antibody discovery - current state and perspectives.Frontiers in immunology · 2025Review
- SResearch (Washington, D.C.) · 2025Article
- A comprehensive overview of recent advances in generative models for antibodies.Computational and structural biotechnology journal · 2024Review
- Development and experimental validation of computational methods for human antibody affinity enhancement.Briefings in bioinformatics · 2024Article
- De novo generation of SARS-CoV-2 antibody CDRH3 with a pre-trained generative large language model.Nature communications · 2024Article
- AntiFormer: graph enhanced large language model for binding affinity prediction.Briefings in bioinformatics · 2024Article
- The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design.Journal of biomedical science · 2024Review
- Building Representation Learning Models for Antibody Comprehension.Cold Spring Harbor perspectives in biology · 2024Review
- Machine learning optimization of candidate antibody yields highly diverse sub-nanomolar affinity antibody libraries.Nature communications · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The dataset presented here contains quantitative binding scores of scFv-format antibodies against a SARS-CoV-2 target peptide collected via an AlphaSeq assay that can be used in the development and benchmarking of machine learning models. Starting from three seed sequences identified from a phage display campaign using a human naïve library, four sets of 29,900 antibodies were designed in silico by creating all k = 1 mutations and random k = 2 and k = 3 mutations throughout the complementary-determining regions (CDRs). Of the 119,600 designs, 104,972 were successfully built in to the AlphaSeq library and target binding was subsequently measured with 71,384 designs resulting in a predicted affinity value for at least one of the triplicate measurements. Data include antibodies with predicted affinity measurements ranging from 37 pM to 22 mM. To our knowledge, this dataset is the largest, publicly available dataset that contains antibody sequences, antigen sequence and quantitative measurements of binding scores and provides an opportunity to serve as a benchmark to evaluate antibody-specific representation models for machine learning.
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