Effect of ligand conjugation site on the micellization of Bio-Targeted PLGA-Based nanohybrids: A computational biology approach

Abstract

In this study, the effect of ligand binding position on the polymeric nanoparticles (NPs) is based on poly(lactic-co-glycolic acid) (PLGA) with two different polymer chain length at the atomistic level was presented. We explored the conjugation of riboflavin (RF) ligand from the end of the ribityl chain (N-10) to the polymer strands as well as from the amine group on the isoalloxazine head (N-3). The energy interactions for all samples revealed that the NPs containing ligands from N-10 positions have higher total attraction energies and lower stability in comparison with their peers conjugated from N-3. As NPs containing RF conjugated from N-3 exhibit the lower energy level with 20% and 10% of RF-containing composition for lower and higher. The introduction of RF from the N-10 position in any composition has increased the energy level of nanocarriers. The results of Gibb's free energy confirm the interatomic interaction energies trend where the lowest Gibbs free energy level for N-3 NPs occurs at 20 and 10% of RF-containing polymer content for PLGA10- and PLGA11- based NPs. Furthermore, with N-10 samples based on both polymers, non-targeted models form the stablest particles in each category. These findings are further confirmed with molecular docking analysis which revealed affinity energy of RF toward polymer chain from N-3 and N-10 are −981.57 kJ/mole and −298.23 kJ/mole, respectively. This in-silico study paves the new way for molecular engineering of the bio-responsive PLGA-PEG-RF micelles and can be used to nanoscale tunning of smart carriers used in cancer treatment.

Communicated by Ramaswamy H. Sarma

Graphical Abstract

Keywords:

• PLGA-PEG
• riboflavin
• molecular dynamic (MD) simulations
• conjugation site

Acknowledgements

The authors wish to acknowledge Bahram Bastan for his support in the reviewing and editing of the present work. We would also like to show our appreciation to Mohammad Mahdi Nematollahi, Ali Mohammadi, and Ebrahim Ghasemy for the contribution to the editing of this work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Author contribution

Reza Maleki and Mohammad Khedri conceived and designed the simulation; Mohammad Khedri carried out the simulations with, visualization of output data, analyze the data Sima Rezvantalab, Mohammad Khedri wrote the manuscript with support from Reza Maleki. The research was supervised and directed by Nima Rezaei and Sima Rezvantalab. All authors contributed to investigation, conceptualization, methodology, analysis, and were involved in the writing process.