Protected Peptide Nanoparticles: Experiments and Brownian Dynamics Simulations of the Energetics of Assembly

Abstract

Soluble peptides, susceptible to degradation and clearance in therapeutic applications, have been formulated into protected nanoparticles for the first time through the process of kinetically controlled, block copolymer directed rapid precipitation using Flash NanoPrecipitation. Complementary Brownian dynamics simulations qualitatively model the nanoparticle formation process. The simulations corroborate the hypothesis that the size of nanoparticles decreases with increasing supersaturation. Additionally, the influence of the polymer-peptide interaction energy on the efficiency of nanoparticle protection by polymer surface coverage is elucidated in both experiments and simulations.

A comparison of implicit- and explicit-solvent simulations of self-assembly in block copolymer and solute systems

“…1 One solution to this problem is to use amphiphilic block copolymer micelles as "containers" to carry such molecules. [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] The hydrophilic block forms a corona that sterically stabilizes the particles. In order to be useful, such particles must be sufficiently small (50-400 nm in diameter) and biocompatible.…”

“…Some of these studies focused on systems in which no solvent is present at all (i.e., nanoparticle-polymer composites), [26][27][28][29][30][31] whereas others investigated the formation of polymer-protected nanoparticles in solvent. 12,[32][33][34][35] Most of the latter were either carried out under conditions in which the polymer/solute/nanoparticle concentrations were substantially higher than those encountered in the flash nanoprecipitation process (ppm), or they did not employ a methodology that simulated the dynamic evolution of the system. For example, Chen et al 33 used dissipative particle dynamics (DPD) to study a system containing solvent, diblock copolymers, and hydrophobic solutes, but the lowest solute and copolymer volume fractions studied were 10% and 5%, respectively.…”

“…Chen et al recently simulated the flash nanoprecipitation process at near-experimental concentrations using Brownian dynamics (BD) simulations of an implicit-solvent model, focusing on the effects of the solute-solute and solute-polymer interaction strengths on the nanoparticle size and polymer distribution on their surface. 12 In this work, we develop a new explicit-solvent model and extend the implicit-solvent model of Chen et al 12,36 for the flash nanoprecipitation process. Implicit-solvent models allow one to simulate larger systems for longer times than one can access with their explicit-solvent counterparts, especially when the vast majority of the system is comprised of solvent, as is the case here.…”

“…First, the mixing time has been estimated to be in the range of milliseconds. 5,[10][11][12]16 Second, the concentrations of the solute and diblock are, respectively, ∼30 and ∼5.3 molecules per million solvent molecules (after mixing). 13 Third, a typical nanoparticle formed in the process has a diameter around 100 nm or greater and contains hundreds of thousands of solute molecules.…”

A competitive aggregation model for Flash NanoPrecipitation

“…Using Brownian dynamics simulations [24,25], it has been shown that during the FNP process organic particles aggregate with each other or onto the hydrophobic block (A-block) of the copolymer, while the hydrophilic block (B-block) of the copolymer stretches in the non-solvent to stabilize the resulting nanoparticles. As the resulting copolymer-organic particle aggregates form micelles, organic protected nanoparticles are formed in the interior of the micelles and further growth is arrested.…”