Quantitative structure-activity relationships (QSARs) were developed, for cellular uptake of nanoparticles
(NPs) of the same iron oxide core but with different surface-modifying organic molecules, based on linear and non-linear
(epsilon support vector regression (ε-SVR)). A linear QSAR provided high prediction accuracy of R2=0.751 (coefficient
of determination) using 11 descriptors selected from an initial pool of 184 descriptors calculated for the NP surfacemodifying
molecules, while a ε-SVR based QSAR with only 6 descriptors improved prediction accuracy to R2 = 0.806.
The linear and ε-SVR based QSARs both demonstrated good robustness and well spanned applicability domains. It is
suggested that the approach of evaluating pertinent descriptors and their significance, via QSAR analysis, to cellular NP
uptake could support planning and interpretation of toxicity studies as well as provide guidance for the tailor-design NPs
with respect to targeted cellular uptake for various applications.
Keywords: QSAR, nano-QSAR, nanomaterial, nanoparticle uptake, surface modification.
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