Due to their shared genetic history, antibodies from the same clonotype often bind to the same epitope. This knowledge is used in immune repertoire mining, where known binders are used to search bulk sequencing repertoires to identify new binders. However current computational methods cannot identify epitope convergence between antibodies from different clonotypes, limiting the sequence diversity of antigen-specific antibodies which can be identified. We describe how the antibody binding site, the paratope, can be used to cluster antibodies with common antigen reactivity from different clonotypes. Our method, paratyping, uses the predicted paratope to identify these novel cross clonotype matches. We experimentally validated our predictions on a Pertussis toxoid dataset. Our results show that even the simplest abstraction of the antibody binding site, using only the length of the loops involved and predicted binding residues, is sufficient to group antigen-specific antibodies and provide additional information to conventional clonotype analysis.

中文翻译：

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通过识别抗百日咳类毒素抗体证明了一种用于免疫库挖掘的计算方法，该方法可识别来自不同克隆型的新型结合物

由于具有相同的遗传史，来自同一克隆型的抗体通常会结合到同一表位。此知识用于免疫库挖掘中，在该库中，使用已知的结合物搜索大量测序库以识别新结合物。然而，当前的计算方法不能识别来自不同克隆型的抗体之间的表位融合，从而限制了可以识别的抗原特异性抗体的序列多样性。我们描述了抗体结合位点，互补位如何可用于聚类具有来自不同克隆型的常见抗原反应性的抗体。我们的方法，类型识别，使用预测的互补位来识别这些新颖的交叉克隆型匹配。我们在百日咳类毒素数据集上通过实验验证了我们的预测。