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J Immunol Methods. 2017 Dec;451:28-36. doi: 10.1016/j.jim.2017.08.004. Epub 2017 Aug 18.

Prediction of antibody structural epitopes via random peptide library screening and next generation sequencing.

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Department of Chemical Engineering, University of California Santa Barbara, CA 93106, USA. Electronic address:
Department of Chemical Engineering, University of California Santa Barbara, CA 93106, USA.


Next generation sequencing (NGS) is widely applied in immunological research, but has yet to become common in antibody epitope mapping. A method utilizing a 12-mer random peptide library expressed in bacteria coupled with magnetic-based cell sorting and NGS correctly identified >75% of epitope residues on the antigens of two monoclonal antibodies (trastuzumab and bevacizumab). PepSurf, a web-based computational method designed for structural epitope mapping was utilized to compare peptides in libraries enriched for monoclonal antibody (mAb) binders to antigen surfaces (HER2 and VEGF-A). Compared to mimotopes recovered from Sanger sequencing of plated colonies from the same sorting protocol, motifs derived from sets of the NGS data improved epitope prediction as defined by sensitivity and precision, from 18% to 82% and 0.27 to 0.51 for trastuzumab and 47% to 76% and 0.19 to 0.27 for bevacizumab. Specificity was similar for Sanger and NGS, 99% and 97% for trastuzumab and 66% and 67% for bevacizumab. These results indicate that combining peptide library screening with NGS yields epitope motifs that can improve prediction of structural epitopes.


Epitope mapping; Next generation sequencing; PepSurf; Random peptide display libraries; Structural epitope

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