(476d) Brownian Dynamics of Nanoparticle Adhesion at Thermally Fluctuating Membrane Interfaces

Adhesion between nanoparticles and cell membranes is a critical interfacial process in various biological applications, including targeted drug delivery, biosensing, and cellular imaging. In targeted drug delivery, nanocarriers are ligand-functionalized nanoparticles engineered to exhibit specific binding affinities to receptor-expressing cell membranes. Previous studies have extensively explored nanoparticle–membrane interactions using Monte Carlo (MC) simulations with detailed energetic descriptions [1–3]. This study focuses on the hydrodynamic effects at the nanoparticle–membrane interface by investigating the Brownian dynamics of a functionalized nanoparticle undergoing multivalent ligand-receptor binding with a thermally fluctuating membrane surface. We formulate a set of coupled Langevin equations to capture both the translational and rotational motion of the nanoparticle near the membrane. The membrane conformation is modeled through the collective Brownian motion of elastically and hydrodynamically interacting fluid elements. Each ligand-receptor bond is represented as a harmonic potential with a prescribed transition to the unbound state. Our results show that the vertical projection of the bivalent potential of mean force exhibits behavior similar to a monovalent interaction characterized by a bistable energy landscape between the nanoparticle and the membrane. This observation is consistent with prior MC simulations [1] and aligns with assumptions from our earlier work [4]. Additionally, the distribution of multivalency varies with ligand grafting density on the nanoparticle surface. Analysis of nanoparticle trajectories enables the determination of binding rates and equilibrium constants. The binding equilibrium constant increases with grafting density, displaying a step-like rise at intermediate densities. These findings elucidate the interplay between hydrodynamic and binding interactions at the nanoparticle–membrane interface and offer valuable insights for advancing dynamical simulation approaches in targeted drug delivery systems.

References

[1] J. Liu, G. E. R. Weller, B. Zern, P. S. Ayyaswamy, D. M. Eckmann, V. R. Muzykantov, R. Radhakrishnan, Proc. Natl. Acad. Sci. USA 2010, 107, 16530.

[2] N. Ramakrishnan, R. W. Tourdot, D. M. Eckmann, P. S. Ayyaswamy, V. R. Muzykantov, R. Radhakrishnan, R. Soc. Open Sci. 2016, 3, 160260.

[3] S. Farokhirad, S. Kutti Kandy, A. Tsourkas, P. S. Ayyaswamy, D. M. Eckmann, R. Radhakrishnan, Adv. Mater. Interfaces 2021, 8, 2101290.

[4] H.-T. Chung, H.-Y. Yu, Phys. Rev. E 2020, 101, 032604.