Evidence map›Paper›PMID 24756879›Full record

ArticleProteins2014

A simple contact mapping algorithm for identifying potential peptide mimetics in protein-protein interaction partners.

Alex Krall, Jonathan Brunn, Spandana Kankanala, Michael H Peters

Abstract read
In one paragraph

Article in Proteins, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

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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

4 authors.

Alex KrallDepartment of Computer Science, Virginia Commonwealth University, Richmond, Virginia, 23284.
Jonathan Brunn
Spandana Kankanala
Michael H Peters

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A simple, static contact mapping algorithm has been developed as a first step at identifying potential peptide biomimetics from protein interaction partner structure files. This rapid and simple mapping algorithm, "OpenContact" provides screened or parsed protein interaction files based on specified criteria for interatomic separation distances and interatomic potential interactions. The algorithm, which uses all-atom Amber03 force field models, was blindly tested on several unrelated cases from the literature where potential peptide mimetics have been experimentally developed to varying degrees of success. In all cases, the screening algorithm efficiently predicted proposed or potential peptide biomimetics, or close variations thereof, and provided complete atom-atom interaction data necessary for further detailed analysis and drug development. In addition, we used the static parsing/mapping method to develop a peptide mimetic to the cancer protein target, epidermal growth factor receptor. In this case, secondary, loop structure for the peptide was indicated from the intra-protein mapping, and the peptide was subsequently synthesized and shown to exhibit successful binding to the target protein. The case studies, which all involved experimental peptide drug advancement, illustrate many of the challenges associated with the development of peptide biomimetics, in general.

Indexed as

AlgorithmsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsBiomimetic MaterialsErbB ReceptorsHIV Envelope Protein gp41Hydrophobic and Hydrophilic InteractionsPeptidesProtein Interaction MapsProtein Structure, TertiaryProto-Oncogene Proteins c-mycRepressor ProteinsBasic Helix-Loop-Helix Leucine Zipper Transcription FactorsEGFR protein, humanErbB ReceptorsHIV Envelope Protein gp41MNT protein, humanMYC protein, humanPeptidesProto-Oncogene Proteins c-mycRepressor Proteinspeptide mimeticsprotein-protein interactionsstatic mapping

Identifiers

PMID24756879
PMCPMC4369124

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.