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Paragraph-antibody paratope prediction using graph neural networks with minimal feature vectors
Lewis Chinery1, Newton Wahome2, Iain Moal3
1Department of Statistics, University of Oxford, Oxford OX1 3LB, UK.
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 And Implementation:
Source code is freely available at www.github.com/oxpig/Paragraph.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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