Computational model for nanocarrier binding to endothelium validated using in vivo, in vitro, and atomic force...

Area of Science:

• Computational biology
• Biophysics
• Nanotechnology

Background:

• Targeted drug delivery relies on nanocarriers (NCs) binding to specific cell surfaces.
• Understanding the biophysical interactions between NCs and endothelial cells (ECs) is critical for optimizing NC design.

Purpose of the Study:

• To develop and validate a computational methodology for calculating nanocarrier binding free energy to endothelial cells.
• To investigate the impact of antibody surface coverage on nanocarrier binding affinity and identify optimal coverage thresholds.

Main Methods:

• Utilized Metropolis Monte Carlo (MC) simulations and the Weighted Histogram Analysis Method (WHAM) to compute binding free energy.
• Validated computational models against in vitro cell-culture experiments, in vivo animal studies, and atomic force microscopy (AFM) measurements.

Main Results:

• The computational model quantitatively predicts nanocarrier binding affinities, showing strong agreement with experimental data.
• A critical threshold for antibody surface coverage (σ(s)) was identified, below which binding affinity drastically decreases.
• Model predictions for NC rupture force and in vivo targeting align well with experimental observations.

Conclusions:

• The developed computational protocol provides a quantitative and predictive approach for designing and optimizing functionalized nanocarriers.
• This methodology establishes the mechanical, thermodynamic, and physiological consistency of nanocarrier-cell interactions.
• The findings are crucial for advancing targeted vascular drug delivery systems.