Evidence map›Paper›PMID 25816209›Full record

ArticlePloS one2015

An in silico insight into novel therapeutic interaction of LTNF peptide-LT10 and design of structure based peptidomimetics for putative anti-diabetic activity.

Sonali Gopichand Chavan, Deepti Dileep Deobagkar

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

3 citing papers in PubMed, 14 citations in OpenAlex.

  1. Current pharmaceutical biotechnology · 2026
    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

2 authors at 1 institution in 1 country.

Sonali Gopichand ChavanBioinformatics Centre, University of Pune, Pune, Maharashtra, India.
Deepti Dileep DeobagkarBioinformatics Centre, University of Pune, Pune, Maharashtra, India; Department of Zoology, Center of Advanced Studies, University of Pune, Pune, Maharashtra, India.
Savitribai Phule Pune University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lethal Toxin Neutralizing Factor (LTNF) obtained from Opossum serum (Didephis virginiana) is known to exhibit toxin-neutralizing activity for envenomation caused by animals, plants and bacteria. Small synthetic peptide- LT10 (10mer) derived from N-terminal fraction of LTNF exhibit similar anti-lethal and anti-allergic property. In our in silico study, we identified Insulin Degrading Enzyme (IDE) as a potential target of LT10 peptide followed by molecular docking and molecular dynamic (MD) simulation studies which revealed relatively stable interaction of LT10 peptide with IDE. Moreover, their detailed interaction analyses dictate IDE-inhibitory interactions of LT10 peptide. This prediction of LT10 peptide as a novel putative IDE-inhibitor suggests its possible role in anti-diabetic treatment since IDE- inhibitors are known to assist treatment of Diabetes mellitus by enhancing insulin signalling. Furthermore, series of structure based peptidomimetics were designed from LT10 peptide and screened for their inhibitory interactions which ultimately led to a small set of peptidomimetic inhibitors of IDE. These peptidomimetic thus might provide a new class of IDE-inhibitors, those derived from LT10 peptide.

Indexed as

AnimalsDiabetes Mellitus, Type 2Drug DesignHypoglycemic AgentsInsulysinMolecular Docking SimulationMolecular Dynamics SimulationOpossumsPeptide FragmentsPeptidomimeticsStructure-Activity RelationshipHypoglycemic AgentsInsulysinPeptide FragmentsPeptidomimetics

Identifiers

PMID25816209
PMCPMC4376886
OpenAlexW2041401376

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.