open access publication

Article, 2024

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG–PLGA Polymer Nanoparticles

Nano Letters, ISSN 1530-6984, 1530-6992, Volume 24, 6, Pages 2011-2017, 10.1021/acs.nanolett.3c04558

Contributors

De Castro, Raquel López-Ríos [1] Ziolek, Robert M 0000-0003-4011-9658 [1] [2] Ulmschneider, Martin B 0000-0001-8103-0516 [1] Lorenz, Christian D 0000-0003-1028-4804 (Corresponding author) [1]

Affiliations

  1. [1] King's College London
    2. [NORA names: United Kingdom; Europe, Non-EU; OECD];
  2. [2] Kvantify Aps, DK-2300, Copenhagen S, Denmark
    3. [NORA names: Denmark; Europe, EU; Nordic; OECD]

Abstract

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.

Keywords

EEK, NPs, PEG-PLGA, acid, anticancer, anticancer peptides, applications, cancer, capability, clinical translation, coarse-grained molecular dynamics simulations, conformation, controlled release capability, data, delivery formulations, delivery vehicles, design, design of nanoparticles, drug, drug delivery formulations, drug delivery vehicles, drug solubilization, dynamics simulations, efficient clinical translation, experimental structural data, formulation, learning techniques, letter, local microenvironment, location, machine learning techniques, mechanism, microenvironment, molecular dynamics simulations, molecular mechanisms, nanoparticles, peptide, polyethylene, polymer, polymer nanoparticles, polymeric nanoparticles, region, release capability, self-assembly, simulation, solubilization, solubulization, storage locations, structural data, technique, technology, therapeutic applications, therapeutic peptides, translation, unsupervised machine learning techniques, vehicle

Funders

  • Engineering and Physical Sciences Research Council
  • Biotechnology and Biological Sciences Research Council

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