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license: cc-by-4.0 |
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# SARS-CoV-2 Nanobody Interaction Dataset (AVIDa-SARS-CoV-2) |
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## Dataset Overview |
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This dataset features the antigen-variable domain of heavy chain antibody (VHH) interactions obtained from two alpacas immunized with SARS-CoV-2 spike proteins. It includes binary labels indicating the binding or non-binding of diverse VHH sequences to 12 SARS-CoV-2 mutants, including variants such as Delta and Omicron. |
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The dataset is designed to evaluate the ability of computational models to predict nanobody binding across different viral variants, which is crucial for understanding antibody cross-reactivity and developing therapeutics against emerging variants. |
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## Data Collection |
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The data was collected from experiments with two alpacas immunized with SARS-CoV-2 spike proteins. Binding assays were conducted to determine whether specific VHH sequences bind to different SARS-CoV-2 variants. Further details are described in the paper "A SARS-CoV-2 Interaction Dataset and VHH Sequence Corpus for Antibody Language Models." |
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## Dataset Structure |
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The dataset is strategically split into training, validation, and test sets to evaluate model generalization: |
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- **Training set**: Covers wild-type (WT), mild mutations (D614G), conserved regions (S2-domain), and immune escape variants (PMS) |
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- **Validation set**: Contains Kappa and Lambda variants that models have never seen before, useful for hyperparameter tuning |
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- **Test set**: Includes Alpha, Beta, Delta, and Omicron variants for final real-world generalization assessment |
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### File Format |
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#### Main Dataset Files (train.csv / val.csv / test.csv) |
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| Column | Description | |
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|--------|-------------| |
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| VHH_sequence | Amino acid sequence of VHH | |
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| Ag_label | Antigen Type | |
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| label | Binary label represented by 1 for binding pair and 0 for non-binding pair | |
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| subject_species | Species of the subject from which VHH was collected | |
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| subject_name | Name of the subject from which VHH was collected | |
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| subject_sex | Sex of the subject from which VHH was collected | |
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#### Antigen Sequences embeddings (antigen_embeddings.pt) |
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precomputed antigen sequence embeddings through ESM-2 (650M) |
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## Uses and Limitations |
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### Uses |
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- Develop models to predict nanobody binding to SARS-CoV-2 variants |
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- Identify nanobodies with broad cross-reactivity against multiple variants |
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- Understand the impact of viral mutations on antibody recognition |
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- Design therapeutic nanobodies with resistance to viral escape |
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## Evaluation Metrics |
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Model performance is evaluated using: |
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- Accuracy |
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- F1 Score |
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- Precision |
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- Recall |
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- AUROC (Area Under the Receiver Operating Characteristic curve) |
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- AUPRC (Area Under the Precision-Recall Curve) |
