Evidence map›Paper›PMID 26180540›Full record

ArticleComputational and mathematical methods in medicine2015

Evolutionary Influenced Interaction Pattern as Indicator for the Investigation of Natural Variants Causing Nephrogenic Diabetes Insipidus.

Steffen Grunert, Dirk Labudde

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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.

Steffen GrunertHochschule Mittweida, University of Applied Sciences, Technikumplatz 17, 09648 Mittweida, Germany.
Dirk LabuddeHochschule Mittweida, University of Applied Sciences, Technikumplatz 17, 09648 Mittweida, Germany.
Hochschule Mittweida · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The importance of short membrane sequence motifs has been shown in many works and emphasizes the related sequence motif analysis. Together with specific transmembrane helix-helix interactions, the analysis of interacting sequence parts is helpful for understanding the process during membrane protein folding and in retaining the three-dimensional fold. Here we present a simple high-throughput analysis method for deriving mutational information of interacting sequence parts. Applied on aquaporin water channel proteins, our approach supports the analysis of mutational variants within different interacting subsequences and finally the investigation of natural variants which cause diseases like, for example, nephrogenic diabetes insipidus. In this work we demonstrate a simple method for massive membrane protein data analysis. As shown, the presented in silico analyses provide information about interacting sequence parts which are constrained by protein evolution. We present a simple graphical visualization medium for the representation of evolutionary influenced interaction pattern pairs (EIPPs) adapted to mutagen investigations of aquaporin-2, a protein whose mutants are involved in the rare endocrine disorder known as nephrogenic diabetes insipidus, and membrane proteins in general. Furthermore, we present a new method to derive new evolutionary variations within EIPPs which can be used for further mutagen laboratory investigations.

Indexed as

AlgorithmsAquaporin 2Arginine VasopressinBiomarkersComputational BiologyComputer GraphicsDatabases, ProteinDiabetes Insipidus, NephrogenicDNA Mutational AnalysisEvolution, MolecularHumansImaging, Three-DimensionalMutationPhosphorylationPituitary GlandProtein ConformationAquaporin 2Arginine VasopressinAVPR2 protein, humanBiomarkersReceptors, Vasopressin

Identifiers

PMID26180540
PMCPMC4477446
OpenAlexW1558278889

What OpenQuestion holds

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LicenceCC BY
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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.