Structure-based molecular docking and molecular dynamics simulations study for the identification of dipeptidyl peptidase 4 inhibitors in type 2 diabetes

Xi Chen, Bin Xue, Shadma Wahab, Armiya Sultan, Mohammad Khalid, Song Yang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Inhibition of dipeptidyl peptidase-4 (DPP4) activity has emerged as a promising therapeutic approach for the treatment of type 2 diabetes mellitus (T2DM). Bioinformatics-driven approaches have emerged as crucial tools in drug discovery. Molecular docking and molecular dynamics (MD) simulations are effective tools in drug discovery, as they reduce the time and cost associated with experimental screening. In this study, we employed structure-assisted in-silico methods, including molecular docking and MD simulations, to identify SRT2183, a small molecule that may potentially inhibit the activity of DPP4 enzyme. The interaction between the small molecule "SRT2183" and DPP4 exhibited a binding affinity of −9.9 Kcal/Mol, leading to the formation of hydrogen bonds with the amino acid residues MET348, SER376, and THR351 of DPP4. The MD simulations over a period of 100 ns indicated stable protein-ligand interactions, with no significant conformational rearrangements observed within the simulated timeframe. In conclusion, our results suggest that the small molecule SRT2183 may have the potential to inhibit the DPP4 enzyme and pave the way for the therapeutics of T2DM. Communicated by Ramaswamy H. Sarma.

Original languageEnglish
Pages (from-to)1445-1458
Number of pages14
JournalJournal of Biomolecular Structure and Dynamics
Volume43
Issue number3
DOIs
StatePublished - 2025

Keywords

  • Dipeptidyl peptidase-4
  • MD simulation
  • SRT2183
  • molecular docking
  • small molecule inhibitor

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