Muzykantov, Vladimir R

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  • Publication
    Computational Model or Nanocarrier Binding to Endothelium Validated Using in Vivo, in Vitro and Atomic Force Microscopy Experiments
    (2010-09-21) Liu, Jin; Zern, Blaine; Ayyaswamy, Portonovo S; Eckmann, David M; Muzykantov, Vladimir R; Radhakrishnan, Ravi; Weller, Gregory E.R.
    A computational methodology based on Metropolis Monte Carlo (MC) and the weighted histogram analysis method (WHAM) has been developed to calculate the absolute binding free energy between functionalized nanocarriers (NC) and endothelial cell (EC) surfaces. The calculated NC binding free energy landscapes yield binding affinities that agree quantitatively when directly compared against analogous measurements of specific antibodycoated NCs (100 nm in diameter) to intracellular adhesion molecule- 1 (ICAM-1) expressing EC surface in in vitro cell-culture experiments. The effect of antibody surface coverage (σs) of NC on binding simulations reveals a threshold σs value below which the NC binding affinities reduce drastically and drop lower than that of single anti-ICAM-1 molecule to ICAM-1. The model suggests that the dominant effect of changing σs around the threshold is through a change in multivalent interactions; however, the loss in translational and rotational entropies are also important. Consideration of shear flow and glycocalyx does not alter the computed threshold of antibody surface coverage. The computed trend describing the effect of σs on NC binding agrees remarkably well with experimental results of in vivo targeting of the anti- ICAM-1 coated NCs to pulmonary endothelium in mice. Model results are further validated through close agreement between computed NC rupture-force distribution and measured values in atomic force microscopy (AFM) experiments. The three-way quantitative agreement with AFM, in vitro (cell-culture), and in vivo experiments establishes the mechanical, thermodynamic, and physiological consistency of our model. Hence, our computational protocol represents a quantitative and predictive approach for model-driven design and optimization of functionalized nanocarriers in targeted vascular drug delivery