Development of novel galactosylated PLGA nanoparticles for hepatocyte targeting using molecular modelling

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
64 Downloads (Pure)


Doxorubicin-loaded PLGA nanoparticles conjugated with a new galactose-based ligand for the specific recognition by human hepatoma cellular carcinoma cells (Hep G2) were successfully produced. The new targeting compound was selected using molecular docking combined with quantum chemical calculations for modelling and comparing molecular interactions among the H1 subunit of the asialoglycoprotein receptor containing the carbohydrate recognition domain and the ligand. The ligand, bis(1-O-ethyl-β-D-galactopyranosyl)amine, was synthetized, characterized, and subsequently linked to PLGA. Unloaded (PLGA-di-GAL NP) and doxorubicin-loaded (DOX-PLGA-di-GAL NP) nanoparticles were prepared using an emulsion method and characterized. The produced DOX-PLGA-di-GAL NP are spherical in shape with a size of 258 ± 47 nm, a zeta potential of-62.3 mV, and a drug encapsulation efficiency of 83%. The in vitro drug release results obtained show a three-phase release profile. In vitro cell studies confirmed the interaction between Hep G2 cells and PLGA-di-GAL NP. Cell cytotoxicity tests showed that unloaded NP are nontoxic and that DOX-PLGA-di-GAL NP caused a decrease of around 80% in cellular viability. The strategy used in this work to design new targeting compounds represents a promising tool to develop eective hepatocyte targeting drug delivery systems and can be applied to other tissues/organs.

Original languageEnglish
Article number94
Issue number1
Publication statusPublished - 4 Jan 2020


  • Doxorubicin delivery
  • Galactosylated nanoparticles
  • Hepatocyte targeting nanoparticles
  • Molecular modelling for drug targeting
  • Surface modified plga nanoparticles


Dive into the research topics of 'Development of novel galactosylated PLGA nanoparticles for hepatocyte targeting using molecular modelling'. Together they form a unique fingerprint.

Cite this