Abstract
Filamentous fd viruses have been used as biotemplates to develop nano sized carriers for biomedical applications. Genetically modified fd viruses with enhanced gold binding properties have been previously obtained by displaying gold binding peptides on viral coat proteins. In order to generate a stable colloidal system of dispersed viruses decorated with AuNPs avoiding aggregation, the underlying binding mechanism of AuNP-peptide interaction should be explored. In this paper, we therefore propose a macro scale self-assembly experiment using 3D printed models of AuNP and the virus to extend our understanding of Au binding process. Moreover, we present our image analysis algorithm which combines image processing techniques and deep learning to automatically examine the coupling state of the particles.
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Acknowledgement
This work was supported by KIST Europe Institutional Program [Project No. 11807].
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Lee, H., Jo, J., Lee, Y.O., Nuriye, K.Z., Abelmann, L. (2019). Deep Learning Analysis of Binding Behavior of Virus Displayed Peptides to AuNPs. In: Fdez-Riverola, F., Mohamad, M., Rocha, M., De Paz, J., González, P. (eds) Practical Applications of Computational Biology and Bioinformatics, 12th International Conference. PACBB2018 2018. Advances in Intelligent Systems and Computing, vol 803. Springer, Cham. https://doi.org/10.1007/978-3-319-98702-6_12
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DOI: https://doi.org/10.1007/978-3-319-98702-6_12
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