Evidence map›Paper›PMID 20084418›Full record

ArticleJournal of molecular modeling2010

"Fuzzy oil drop" model applied to individual small proteins built of 70 amino acids.

Katarzyna Prymula, Kinga Sałapa, Irena Roterman

Abstract read
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Article in Journal of molecular modeling, 2010. 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
–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

2 citing papers in PubMed.

  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.

Katarzyna PrymulaDepartment of Bioinformatics, Telemedicine Jagiellonian University - Collegium Medicum, Lazarza 16, 31-530, Krakow, Poland.
Kinga Sałapa
Irena Roterman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The proteins composed of short polypeptides (about 70 amino acid residues) representing the following functional groups (according to PDB notation): growth hormones, serine protease inhibitors, antifreeze proteins, chaperones and proteins of unknown function, were selected for structural and functional analysis. Classification based on the distribution of hydrophobicity in terms of deficiency/excess as the measure of structural and functional specificity is presented. The experimentally observed distribution of hydrophobicity in the protein body is compared to the idealized one expressed by a three-dimensional Gauss function. The differences between these two distributions reveal the specificity of structural/functional characteristics of the protein. The residues of hydrophobicity deficiency versus the idealized distribution are assumed to indicate cavities with the potential to bind ligands, while the residues of hydrophobicity excess are interpreted as potentially participating in protein-protein complexation. The distribution of hydrophobicity irregularity seems to be specific for particular structures and functions of proteins. A comparative analysis of such profiles is carried out to identify the potential biological activity of proteins of unknown function.

Indexed as

Models, MolecularProtein Structure, TertiaryAlgorithmsAmino AcidsAntifreeze ProteinsBinding SitesComputational BiologyDatabases, ProteinGrowth HormoneHydrophobic and Hydrophilic InteractionsMolecular ChaperonesMolecular WeightProtein BindingProtein ConformationProteinsSerine Proteinase InhibitorsAmino AcidsAntifreeze ProteinsGrowth HormoneMolecular ChaperonesProteinsSerine Proteinase Inhibitors

Identifiers

What OpenQuestion holds

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Registered trials

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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.