Evidence map›Paper›PMID 38565703›Full record

ArticleScientific reports2024

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.

Fateme Zare, Elaheh Ataollahi, Pegah Mardaneh, Amirhossein Sakhteman, Valiollah Keshavarz, Aida Solhjoo, Leila Emami

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
14.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 41 citations in OpenAlex.

  1. Identification of novel HIF2α inhibitors: a structure-based virtual screening approach.Journal of enzyme inhibition and medicinal chemistry · 2026
    Article
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  5. Article
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  8. ADMET & DMPK · 2026
    Review
  9. Article
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  13. FeBMC chemistry · 2025
    Article
  14. Review
  15. Article
  16. Journal of Taibah University Medical Sciences · 2025
    Article
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  18. Review
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Fateme Zare *Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Elaheh Ataollahi *Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Pegah Mardaneh *Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Amirhossein SakhtemanChair of Proteomics and Bioanalytics, Technical University of Munich (TUM), 85354, Freising, Germany.
Valiollah KeshavarzDepartment of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Aida SolhjooDepartment of Quality Control of Drug Products, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran. aida.solhjoo86@gmail.com.
Leila EmamiPharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, Shiraz, Iran. emamil@sums.ac.ir.
Shiraz University of Medical Sciences · IRTechnical University of Munich · DE

Funding

Shiraz Transplant Research Center, Shiraz University of Medical Sciences 27202
6 · The paper itself

Abstract

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

Indexed as

Dipeptidyl-Peptidase IV InhibitorsMolecular Dynamics SimulationBinding SitesDensity Functional TheoryDipeptidyl Peptidase 4LigandsMolecular Docking SimulationDipeptidyl Peptidase 4Dipeptidyl-Peptidase IV InhibitorsLigandsADMETDFTDPP4 inhibitorMM/PBSAMolecular dynamics simulationStructure-based virtual screening

Identifiers

PMID38565703
PMCPMC10987597
OpenAlexW4393398081

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.