How does nanoparticle design affect targeting selectivity: computer modeling

E.E. Dormidontova
University of Connecticut, US

Keywords: nanoparticle, targeting, selectivity, ligand-receptor interactions, computer modeling


One of the areas of active development of modern nanomedicine is application of polymer tethered nanoparticles for drug/gene delivery and imaging. The optimal nanoparticle design for targeting one type of cell may be quite different from that for another cell and will depend on the density, distribution and mobility of receptors. Computer and theoretical modeling allows a systematic investigation of the influence of multiple factors and provides a unified platform for the comparison of the efficiency of different nanoparticles. While strong interactions with receptors ensure stable attachment of nanoparticles to cell surfaces, this often compromises selectivity as targeted receptors can be present on many different cells including healthy cells. We investigate the dominant factors influencing selectivity of nanoparticle-cell surface interactions and make predictions regarding favorable nanoparticle design for achieving nanoparticle attachment to cells with high receptor density while sparing healthy cells with low density of receptors. In particular, we analyze the onset of nanoparticle adsorption in terms of receptor density and discuss how the onset can be tuned by modifying the nanoparticle design. Based on the obtained data, we make experimentally testable predictions regarding the ways to enhance selectivity of nanoparticle-cell surface interactions by optimizing the nanoparticle architecture.