Evidence map›Paper›PMID 32938999›Full record

ArticleScientific reports2020

GLN: a method to reveal unique properties of lasso type topology in proteins.

Wanda Niemyska, Kenneth C Millett, Joanna I Sulkowska

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
0.3field-weighted citation impact, top 47% 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

16 citing papers in PubMed, 3 citations in OpenAlex.

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  8. Folds from fold: Exploring topological isoforms of a single-domain protein.Proceedings of the National Academy of Sciences of the United States of America · 2024
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  14. Are there double knots in proteins? Prediction andFrontiers in molecular biosciences · 2023
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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

3 authors at 2 institutions in 2 countries.

Wanda NiemyskaFaculty of Mathematics, Informatics and Mechanics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland.
Kenneth C MillettDepartment of Mathematics, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.
Joanna I SulkowskaCentre of New Technologies, University of Warsaw, Banacha 2c, 02-097, Warsaw, Poland. jsulkowska@cent.uw.edu.pl.
University of Warsaw · PLUniversity of California, Santa Barbara · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a matrix diagram-for a pair of a loop and a tail-to study both the geometry and topology of proteins with closed loops e.g. lassos. We show that the GLN method is a significantly faster technique to detect entanglement in lasso proteins in comparison with other methods. Based on the GLN technique, we conduct comprehensive analysis of all proteins deposited in the PDB and compare it to the statistical properties of the polymers. We show how high and low GLN values correlate with the internal exibility of proteins, and how the GLN in the form of a matrix diagram can be used to study folding and unfolding routes. Finally, we discuss how the GLN method can be applied to study entanglement between two structures none of which are closed loops. Since this approach is much faster than other linking invariants, the next step will be evaluation of lassos in much longer molecules such as RNA or loops in a single chromosome.

Indexed as

Models, MolecularModels, TheoreticalProtein FoldingAlgorithmsAnimalsDatabases, ProteinDatasets as TopicHumansMolecular Dynamics SimulationProtein ConformationProteinsProteins

Identifiers

PMID32938999
PMCPMC7494857
OpenAlexW3023914365

What OpenQuestion holds

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LicenceCC BY
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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.