Evidence map›Paper›PMID 22643976›Full record

ArticleJournal of molecular modeling2012

Stochastic simulation of structural properties of natively unfolded and denatured proteins.

David Curcó, Catherine Michaux, Guillaume Roussel, Emmanuel Tinti, Eric A Perpète, Carlos Alemán

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Article in Journal of molecular modeling, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

6 authors.

David CurcóDepartament d'Enginyeria Química, Facultat de Química, Universitat de Barcelona, Marí i Franques 1, Barcelona, 08028, Spain.
Catherine Michaux
Guillaume Roussel
Emmanuel Tinti
Eric A Perpète
Carlos Alemán

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A new simulation strategy based on a stochastic process has been developed and tested to study the structural properties of the unfolded state of proteins at the atomistic level. The procedure combines a generation algorithm to produce representative uncorrelated atomistic microstructures and an original relaxation method to minimize repulsive non-bonded interactions. Using this methodology, a set of 14 unfolded proteins, including seven natively unfolded proteins as well as seven "classical" proteins experimentally described in denaturation conditions, has been investigated. Comparisons between the calculated and available experimental values of several properties, at hydrodynamic and atomic level, used to describe the unfolded state, such as the radius of gyration, the maximum length, the hydrodynamic radius, the diffusion coefficient, the sedimentation coefficient, and the NMR chemical shifts, reflect a very good agreement. Furthermore, our results indicate that the relationship between the radius of gyration and the hydrodynamic radius deviates from the Zimm's theory of polymer dynamics for random coils, as was recently observed using single-molecule fluorescent methods. Simulations reveal that the interactions between atoms separated by three chemical bonds (1-4 interactions) play a crucial role in the generation process, suggesting that the unfolded state is essentially governed by bonding and short-range non-bonding interactions.

Indexed as

Computer SimulationProtein DenaturationProtein FoldingAmino Acid SequenceHumansLinear ModelsPeptidesProtein ConformationProteinsStochastic ProcessesThermodynamicsUbiquitinPeptidespolyalanineProteinsUbiquitin

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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.