Boosting Drug Discovery for Parkinson's: Enhancement of the Delivery of a Monoamine Oxidase-B Inhibitor by Brain-Targeted PEGylated Polycaprolactone-Based Nanoparticles

abstract

The current pharmacological treatments for Parkinson's disease only offer symptomatic relief to the patients and are based on the administration of levodopa and catechol-O-methyltransferase or monoamine oxidase-B inhibitors (IMAO-B). Since the majority of drug candidates fail in pre- and clinical trials, due largely to bioavailability pitfalls, the use of polymeric nanoparticles (NPs) as drug delivery systems has been reported as an interesting tool to increase the stealth capacity of drugs or help drug candidates to surpass biological barriers, among other benefits. Thus, a novel potent, selective, and reversible IMAO-B (chromone C27, IC50 = 670 +/- 130 pM) was encapsulated in poly(caprolactone) (PCL) NPs by a nanoprecipitation process. The resulting C27-loaded PEGylated PCL NPs (similar to 213 nm) showed high stability and no cytotoxic effects in neuronal (SH-SY5Y), epithelial (Caco-2), and endothelial (hCMEC/D3) cells. An accumulation of PEGylated PCL NPs in the cytoplasm of SH-SY5Y and hCMEC/D3 cells was also observed, and their permeation across Caco-2 and hCMEC/D3 cell monolayers, used as in vitro models of the human intestine and blood-brain barrier, respectively, was demonstrated. PEGylated PCL NPs delivered C27 at concentrations higher than the MAO-B IC50 value, which provides evidence of their relevance to solving the drug discovery pitfalls.

keywords

IN-VITRO TRANSPORT; POLYMERIC NANOPARTICLES; PLGA NANOPARTICLES; CONTROLLED-RELEASE; CELLULAR UPTAKE; SH-SY5Y CELLS; BARRIER; MODEL; POLY(EPSILON-CAPROLACTONE); POLYSORBATE-80

subject category

Pharmacology & Pharmacy

authors

Pinto, M; Fernandes, C; Martins, E; Silva, R; Benfeito, S; Cagide, F; Mendes, RE; Paz, FAA; Garrido, J; Remiao, F; Borges, F

our authors

acknowledgements

Pinto, M., Fernandes, C., Benfeito, S., Cagide, F. (NORTE-01-0145-FEDER-000028), Silva, R. (SFRH/BPD/110201/2015) and Mendes, R.F. (SFRH/BD/84231/2012) grants are supported by FCT, POPH and FEDER/COMPETE. The authors also thank the COST action CA15135 for support. This work was funded by FEDER funds through the Operational Programme Competitiveness Factors-FEDER/COMPETE-by national funds (FCT-Foundation for Science and Technology) and Norte Portugal Regional Operational Programme (Grants POCI-01-0145-FEDER-006980-UID/QUI/00081/2013, POCI-01-0145-FEDER-007679-UID/CTM/50011/2013, EXPL/CTM-NAN/0013/2013, POCI-01-0145-FEDER-029164 and NORTE-01-0145-FEDER-000028).

Share this project:

Related Publications

We use cookies for marketing activities and to offer you a better experience. By clicking “Accept Cookies” you agree with our cookie policy. Read about how we use cookies by clicking "Privacy and Cookie Policy".