Diffusion of curcumin in PLGA-based carriers for drug delivery: a molecular dynamics study

Abstract

Context: The rapid growth and diversification of drug delivery systems have been significantly supported by advancements in micro- and nano-technologies, alongside the adoption of biodegradable polymeric materials like poly(lactic-co-glycolic acid) (PLGA) as microcarriers. These developments aim to reduce toxicity and enhance target specificity in drug delivery. The use of in silico methods, particularly molecular dynamics (MD) simulations, has emerged as a pivotal tool for predicting the dynamics of species within these systems. This approach aids in investigating drug delivery mechanisms, thereby reducing the costs associated with design and prototyping. In this study, we focus on elucidating the diffusion mechanisms in curcumin-loaded PLGA particles, which are critical for optimizing drug release and efficacy in therapeutic applications.

Methods: We utilized MD to explore the diffusion behavior of curcumin in PLGA drug delivery systems. The simulations, executed with GROMACS, modeled curcumin molecules in a representative volume element of PLGA chains and water, referencing molecular structures from the Protein Data Bank and employing the CHARMM force field. We generated PLGA chains of varying lengths using the Polymer Modeler tool and arranged them in a bulk-like environment with Packmol. The simulation protocol included steps for energy minimization, T and p equilibration, and calculation of the isotropic diffusion coefficient from the mean square displacement. The Taguchi method was applied to assess the effects of hydration level, PLGA chain length, and density on diffusion.

Results: Our results provide insight into the influence of PLGA chain length, hydration level, and polymer density on the diffusion coefficient of curcumin, offering a mechanistic understanding for the design of efficient drug delivery systems. The sensitivity analysis obtained through the Taguchi method identified hydration level and PLGA density as the most significant input parameters affecting curcumin diffusion, while the effect of PLGA chain length was negligible within the simulated range. We provided a regression equation capable to accurately fit MD results. The regression equation suggests that increases in hydration level and PLGA density result in a decrease in the diffusion coefficient.

Keywords: Diffusion; Mass transfer; Molecular dynamics; Polymeric carriers; Water.

Fig. 1

a Morphology of curcumin-loaded DPPs using Scanning Electron Microscope; b rendering of a simulated PLGA box, filled with curcumin (in yellow) and water; c rendering of a single chain of PLGA; d rendering of a single molecule of curcumin. Colors in c and d indicate different atoms type: carbon in grey, oxygen in red, and hydrogen in white

Fig. 2

Exemplified mean square displacement (MSD) of a solvent, b curcumin, and c PLGA

Fig. 3

Histograms of diffusion coefficient (D) for water (a and d), PLGA (b and e), and curcumin (c and f) for DOE1 and DOE2, respectively — logarithmic scale

Fig. 4

Spearman’s correlation coefficient (from -1 to +1, see color bar) between the input variables (hydration level H, PLGA chain length L, and PLGA density P) and the diffusion coefficients of water, PLGA, and curcumin molecules measured by MD. Levels with $H=0$ g/cm³ are not considered in this analysis, to avoid null values of water diffusivity

Fig. 5

Diffusion coefficient of curcumin ($D_c$) as a function of the hydration level (H), PLGA chain length (L), and PLGA density (P) explored by MD in this study (dots), and best fitted by Eq. 4 (background, continuous color). a $L=$ 1.8 nm. b $L=$ 14.7 nm. c $P=$ 0.804 g/cm³. d $P=$ 1.340 g/cm³

Fig. 6

Comparison between the diffusion coefficient of curcumin ($D_c$) calculated with MD simulations and predicted by regression Eq. 6. Points lying on the identity line correspond to the highest regression accuracy