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Paragraph – Antibody paratope prediction using Graph Neural Networks with minimal feature vectors

Bioinformatics. 2022 Nov 12:btac732. doi: 10.1093/bioinformatics/btac732. Online ahead of print.

ABSTRACT

SUMMARY: The development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce the cost of this process by improving our understanding of antibody-antigen binding. We present Paragraph, a structure-based paratope prediction tool that outperforms current state-of-the-art tools using simpler feature vectors and no antigen information.

AVAILABILITY: Source code is freely available at www.github.com/oxpig/Paragraph.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:36370083 | DOI:10.1093/bioinformatics/btac732

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