Evidence map›Paper›PMID 33349244›Full record

ArticleBMC bioinformatics2020

Predicting substitutions to modulate disorder and stability in coiled-coils.

Yasaman Karami, Paul Saighi, Rémy Vanderhaegen, Denis Gerlier, Sonia Longhi, Elodie Laine, Alessandra Carbone

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Review
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

7 authors at 2 institutions in 1 country.

Yasaman KaramiCNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. yasaman.karami@pasteur.fr.
Paul SaighiCNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France.
Rémy VanderhaegenCNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France.
Denis GerlierCIRI, International Center for Infectiology Research, INSERM, U1111, Université Claude Bernard Lyon 1, CNRS, UMR5308, Ecole Normale Supérieure de Lyon, Univ Lyon, Lyon, France.
Sonia LonghiCNRS, Architecture et Fonction des Macromolécules Biologiques (AFMB), UMR 7257, Aix-Marseille University, Marseille, France.
Elodie LaineCNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. elodie.laine@upmc.fr.
Alessandra CarboneCNRS, IBPS, UMR 7238, Laboratoire de Biologie Computationnelle et Quantitative (LCQB), Sorbonne Université, 75005, Paris, France. alessandra.carbone@lip6.fr.ORCID http://orcid.org/0000-0003-2098-5743
Centre National de la Recherche Scientifique · FRUniversité Claude Bernard Lyon 1 · FR

Funding

Commissariat Général à l'Investissement ANR-10-EQPX- 29-01Commissariat Général à l'Investissement ANR-11-BINF-0003Commissariat Général à l'Investissement ANR-11-IDEX-0004-02Commissariat Général á l'Investissement (FR) ANR-11-LABX-0037-01
6 · The paper itself

Abstract

backgroundCoiled-coils are described as stable structural motifs, where two or more helices wind around each other. However, coiled-coils are associated with local mobility and intrinsic disorder. Intrinsically disordered regions in proteins are characterized by lack of stable secondary and tertiary structure under physiological conditions in vitro. They are increasingly recognized as important for protein function. However, characterizing their behaviour in solution and determining precisely the extent of disorder of a protein region remains challenging, both experimentally and computationally.

resultsIn this work, we propose a computational framework to quantify the extent of disorder within a coiled-coil in solution and to help design substitutions modulating such disorder. Our method relies on the analysis of conformational ensembles generated by relatively short all-atom Molecular Dynamics (MD) simulations. We apply it to the phosphoprotein multimerisation domains (PMD) of Measles virus (MeV) and Nipah virus (NiV), both forming tetrameric left-handed coiled-coils. We show that our method can help quantify the extent of disorder of the C-terminus region of MeV and NiV PMDs from MD simulations of a few tens of nanoseconds, and without requiring an extensive exploration of the conformational space. Moreover, this study provided a conceptual framework for the rational design of substitutions aimed at modulating the stability of the coiled-coils. By assessing the impact of four substitutions known to destabilize coiled-coils, we derive a set of rules to control MeV PMD structural stability and cohesiveness. We therefore design two contrasting substitutions, one increasing the stability of the tetramer and the other increasing its flexibility.

conclusionsOur method can be considered as a platform to reason about how to design substitutions aimed at regulating flexibility and stability.

Indexed as

Amino Acid SequenceComputational BiologyMeasles virusMolecular Dynamics SimulationNipah VirusProtein DomainsProtein StabilityProtein Structure, SecondaryViral ProteinsViral ProteinsCoiled-coilMolecular dynamicsProtein disorderProtein dynamicsProtein stabilityProtein structure

Identifiers

PMID33349244
PMCPMC7751101
OpenAlexW3116945358

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.