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Issue 73, 2016, Issue in Progress
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Computational approaches for the prediction of the selective uptake of magnetofluorescent nanoparticles into human cells

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Abstract

The use of functionalized nanomaterials is of high importance in biomedical applications like the efficient targeting of cancer cells. This paper proposes a comparison of different statistical and mechanistic aspects of new QSAR models generated to predict the selective uptake of a library of surface modified nanoparticles tested in different human cell types. Additionally, a new approach based on the combination of multivariate factorial analysis and QSAR is proposed to generate a 2-dimensional map of the selective uptake of the surface modified nanoparticles into multiple cell types. This map offers an immediate view of the uptake of the nanoparticles, distinguishing among those with high or low uptake in one or more of the studied cells. Finally, QSAR models are generated to predict the coordinates of the studied nanoparticles in the 2D map from their molecular structure. This predictive map is useful to screen new and existing surface modified nanoparticles for diagnostic and biomedical uses.

Graphical abstract: Computational approaches for the prediction of the selective uptake of magnetofluorescent nanoparticles into human cells

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Supplementary files

Article information


Submitted
27 Mar 2016
Accepted
05 Jul 2016
First published
20 Jul 2016

RSC Adv., 2016,6, 68806-68818
Article type
Paper
Author version available

Computational approaches for the prediction of the selective uptake of magnetofluorescent nanoparticles into human cells

E. Papa, J. P. Doucet and A. Doucet-Panaye, RSC Adv., 2016, 6, 68806
DOI: 10.1039/C6RA07898B

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