Next-Generation Noncompetitive Nanosystems Based on Gambogic Acid: In Silico Identification of Transferrin Receptor Binding Sites, Regulatory Shelf Stability, and Their Preliminary Safety in Healthy Rodents | Academic Article individual record
abstract

© 2019 American Chemical Society. A major challenge in drug delivery is to enhance the transport of drugs across biological barriers, such as the small intestine, the blood-brain barrier, and the blood-retinal/ocular barrier, and to effectively reach the site of action while minimizing the systemic impact. In recent years, piggybacking cell surface receptors have been considered a viable strategy for active drug delivery across the biological barriers. However, the ligands used to target drugs to plasma membrane receptors often have to compete against endogenous ligands, thereby limiting their binding to the cell surface and their transport across barriers. To address this problem, gambogic acid (GA) was identified as a noncompetitive ligand specific to the transferrin receptor (TfR), a receptor present on various barriers. However, the binding sites of the GA on TfR remain unknown, an essential step toward establishing structure-activity relationships. In silico binding site prediction tools, blind docking, and molecular docking simulation confirm that the GA binding site on the TfR is independent of the transferrin-bound iron binding sites. The GA-conjugated polyesters were processed into nanoparticles suitable for drug delivery applications that possess excellent storage stability under regulatory conditions. Traditionally, GA has been used as an anticancer compound that warrants safety assessment. The preliminary studies in healthy rodents on 10-repeated oral doses show no adverse effects. This work will generate paradigm shifting, new knowledge in the field of nanomedicines using unique noncompetitive nanosystems that do not compete with endogenous transferrin.

author list (cited authors)
Arora, M., Ganugula, R., Kumar, N., Kaur, G., Pellois, J. P., Garg, P., & Ravi Kumar, M.
publication date
2019
published in
altmetric score

8.08

citation count

0