Evidence map›Paper›PMID 25396726›Full record

ArticlePloS one2014

Finding needles in a haystack: application of network analysis and target enrichment studies for the identification of potential anti-diabetic phytochemicals.

Shaik M Fayaz, Valsala S Suvanish Kumar, Krishnamurthy G Rajanikant

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
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.

Shaik M FayazSchool of Biotechnology, National Institute of Technology Calicut, Calicut 673601, India.
Valsala S Suvanish KumarSchool of Biotechnology, National Institute of Technology Calicut, Calicut 673601, India.
Krishnamurthy G RajanikantSchool of Biotechnology, National Institute of Technology Calicut, Calicut 673601, India.
National Institute of Technology Calicut · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus is a debilitating metabolic disorder and remains a significant threat to public health. Herbal medicines have been proven to be effective anti-diabetic agents compared to synthetic drugs in terms of side effects. However, the complexity in their chemical constituents and mechanism of action, hinder the effort to discover novel anti-diabetic drugs. Hence, understanding the biological and chemical basis of pharmacological action of phytochemicals is essential for the discovery of potential anti-diabetic drugs. Identifying important active compounds, their protein targets and the pathways involved in diabetes would serve this purpose. In this context, the present study was aimed at exploring the mechanism of action of anti-diabetic plants phytochemicals through network and chemical-based approaches. This study also involves a focused and constructive strategy for preparing new effective anti-diabetic formulations. Further, a protocol for target enrichment was proposed, to identify novel protein targets for important active compounds. Therefore, the successive use of network analysis combined with target enrichment studies would accelerate the discovery of potential anti-diabetic phytochemicals.

Indexed as

Binding SitesDatabases, FactualDiabetes MellitusDNA Topoisomerases, Type IIHumansHypoglycemic AgentsModels, TheoreticalMolecular Docking SimulationPhytochemicalsPlants, MedicinalProteinsProtein Structure, TertiaryDNA Topoisomerases, Type IIHypoglycemic AgentsPhytochemicalsProteins

Identifiers

PMID25396726
PMCPMC4232558
OpenAlexW2001792199

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.