NPY1R-targeted peptide-mediated delivery of a dual PPAR?/? agonist to adipocytes enhances adipogenesis and prevents diabetes progression.
Ontology highlight
ABSTRACT: OBJECTIVE:PPAR?/? dual agonists have been in clinical development for the treatment of metabolic diseases including type 2 diabetes and dyslipidemia. However, severe adverse side effects led to complications in clinical trials. As most of the beneficial effects rely on the compound activity in adipocytes, the selective targeting of this cell type is a cutting-edge strategy to develop safe anti-diabetic drugs. The goal of this study was to strengthen the adipocyte-specific uptake of the PPAR?/? agonist tesaglitazar via NPY1R-mediated internalization. METHODS:NPY1R-preferring peptide tesaglitazar-[F7, P34]-NPY (tesa-NPY) was synthesized by a combination of automated SPPS and manual couplings. Following molecular and functional analyses for proof of concept, cell culture experiments were conducted to monitor the effects on adipogenesis. Mice treated with peptide drug conjugates or vehicle either by gavage or intraperitoneal injection were characterized phenotypically and metabolically. Histological analysis and transcriptional profiling of the adipose tissue were performed. RESULTS:In vitro studies revealed that the tesaglitazar-[F7, P34]-NPY conjugate selectively activates PPAR? in NPY1R-expressing cells and enhances adipocyte differentiation and adiponectin expression in adipocyte precursor cells. In vivo studies using db/db mice demonstrated that the anti-diabetic activity of the peptide conjugate is as efficient as that of systemically administered tesaglitazar. Additionally, tesa-NPY induces adipocyte differentiation in vivo. CONCLUSIONS:The use of the tesaglitazar-[F7, P34]-NPY conjugate is a promising strategy to apply the beneficial PPAR?/? effects in adipocytes while potentially omitting adverse effects in other tissues.
SUBMITTER: Wittrisch S
PROVIDER: S-EPMC6931124 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
ACCESS DATA