247
Views
4
CrossRef citations to date
0
Altmetric
Research Articles

In-silico identification of peroxisome proliferator-activated receptor (PPAR)α/γ agonists from Ligand Expo Components database

, , , &
Pages 1853-1864 | Received 16 Oct 2019, Accepted 02 Mar 2020, Published online: 01 Apr 2020
 

Abstract

PPARα and PPARγ play important roles in regulating glucose and lipid metabolism. In recent years, the development of dual PPAR agonists has become a hot topic in the field of anti-diabetic medicinal chemistry. The dual PPARα/γ agonists can both improve metabolism and reduce side effects caused by single drugs, and has become a promising strategy for designing effective drugs for the treatment of type 2 diabetes. In this study, by means of virtual screening, molecular docking and ADMET prediction technology, a representative compound with higher docking score, lower toxicity than original ligands was gained from the Ligand Expo Components database. It was observed through MD simulation that the representative compound not only has the function of activating the PPARα target and the PPARγ target, but also show a more favorable binding mode when the representative compound binds to the two receptors compared to the original ligands. Our results provided an approach to rapidly find novel PPARα/γ dual agonists for the treatment of type 2 diabetes mellitus (T2DM).

This paper explores novel compounds targeting PPARα/γ dual agonists by using molecular docking, ADMET prediction, and molecular dynamics simulation methods. The specific flowchart is as follows:

    Highlights

  1. The results show that the skeleton of compound M80 is not only similar to Saroglitazar but also higher than that of Saroglitazar in activity.

  2. This study explained the binding modes of saroglitazar-PPARα/γ complexes and provided structure reference for the research and development of novel PPARα/γ dual agonists.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Disclosure statement

Authors declare no conflicts of interest.

Additional information

Funding

This work was supported by the Natural Science Foundation of Tianjin (18JCYBJC28800).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,074.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.