Evidence map›Paper›PMID 26580541›Full record

ArticleJournal of chemical theory and computation2014

Sidekick for Membrane Simulations: Automated Ensemble Molecular Dynamics Simulations of Transmembrane Helices.

Benjamin A Hall, Khairul Bariyyah Abd Halim, Amanda Buyan, Beatrice Emmanouil, Mark S P Sansom

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 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

5 authors.

Benjamin A HallDepartment of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.
Khairul Bariyyah Abd HalimDepartment of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.
Amanda BuyanDepartment of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.
Beatrice EmmanouilDepartment of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.
Mark S P SansomDepartment of Biochemistry, University of Oxford , South Parks Road, Oxford OX1 3QU, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council B19456Biotechnology and Biological Sciences Research Council BB/H000267/1Biotechnology and Biological Sciences Research Council BB/I019855/1Biotechnology and Biological Sciences Research Council BB/L002558/1Biotechnology and Biological Sciences Research Council BBS/B/16011Biotechnology and Biological Sciences Research Council BEP17032Wellcome Trust 092970Wellcome Trust 097299
6 · The paper itself

Abstract

The interactions of transmembrane (TM) α-helices with the phospholipid membrane and with one another are central to understanding the structure and stability of integral membrane proteins. These interactions may be analyzed via coarse grained molecular dynamics (CGMD) simulations. To obtain statistically meaningful analysis of TM helix interactions, large (N ca. 100) ensembles of CGMD simulations are needed. To facilitate the running and analysis of such ensembles of simulations, we have developed Sidekick, an automated pipeline software for performing high throughput CGMD simulations of α-helical peptides in lipid bilayer membranes. Through an end-to-end approach, which takes as input a helix sequence and outputs analytical metrics derived from CGMD simulations, we are able to predict the orientation and likelihood of insertion into a lipid bilayer of a given helix of a family of helix sequences. We illustrate this software via analyses of insertion into a membrane of short hydrophobic TM helices containing a single cationic arginine residue positioned at different positions along the length of the helix. From analyses of these ensembles of simulations, we estimate apparent energy barriers to insertion which are comparable to experimentally determined values. In a second application, we use CGMD simulations to examine the self-assembly of dimers of TM helices from the ErbB1 receptor tyrosine kinase and analyze the numbers of simulation repeats necessary to obtain convergence of simple descriptors of the mode of packing of the two helices within a dimer. Our approach offers a proof-of-principle platform for the further employment of automation in large ensemble CGMD simulations of membrane proteins.

Identifiers

PMID26580541
PMCPMC4871227

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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.