Evidence map›Paper›PMID 33868895›Full record

ArticleIn silico pharmacology2021

Exploring the antidiabetic potential of compounds isolated from

Victor Okoliko Ukwenya, Sunday Aderemi Adelakun, Olusola Olalekan Elekofehinti

Open access · greenAbstract read
In one paragraph

Article in In silico pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Journal of diabetes and metabolic disorders · 2023
    Article
  4. Article
  5. Review
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

3 authors at 1 institution in 1 country.

Victor Okoliko UkwenyaDepartment of Human Anatomy, School of Health and Health Technology, Federal University of Technology, Akure, Nigeria.ORCID 0000-0002-8772-5578
Sunday Aderemi AdelakunDepartment of Human Anatomy, School of Health and Health Technology, Federal University of Technology, Akure, Nigeria.
Olusola Olalekan ElekofehintiBioinformatics and Molecular Biology Unit, Department of Biochemistry, School of Sciences, Federal University of Technology, Akure, Nigeria.
Federal University of Technology · NG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus is becoming an important public health challenge worldwide and especially in developing nations. About 8.8 percent of the world adult population has been reported to have diabetes. Glutamine-fructose-6-phosphate amidotransferase 1 (GFAT1) catalyses the first committed step in the pathway for biosynthesis of hexosamines in mammals, and its inhibition has been thought to prevent hyperglycaemia. Dipeptidyl peptidase-4 (DPP-4), on the other hand, degrades hormone glucagon-like peptide-1 (GLP-1), an enzyme that plays a major role in the enhancement of glucose-dependent insulin secretion, making these two proteins candidate targets for diabetes. To find potential inhibitors of DPP-4 and GFAT1 from Anacardium occidentale using a computational approach, glide XP (extra precision) docking, Induced Fit Docking (IFD), Binding free energy of the compounds were determined against prepared crystal structure of DPP-4 and GFAT1 using the Maestro molecular interface of Schrödinger suites. The Lipinski's rule of five (RO5) and ADME properties of the compounds were assessed. Predictive models for both protein targets were built using AutoQSAR. This study identified 8 hit compounds. Most of these compounds passed the RO5 and were within the recommended range for defined ADME parameters. In addition, the predicted pIC50 for the hit compounds were promising. The results obtained from the present study can be used to design an antidiabetic drug. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40203-021-00084-z.

Indexed as

Diabetes mellitusDPP-4GFAT1InsulinMolecular docking studies

Identifiers

PMID33868895
PMCPMC8019409
OpenAlexW3152755832

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.