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ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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Coarse-grained simulations of protein partitioning in membranes with varying levels of SDPE

Authors: Javanainen, Matti;

Coarse-grained simulations of protein partitioning in membranes with varying levels of SDPE

Abstract

The free energies of transfer between liquid ordered (Lo) and liquid disordered (Ld) domains was calculated for three proteins (Adenosine A2 receptor, A2AR; dopamine D2 receptor, D2R; and glucose transporter (GLUT)) using coarse-grained molecular dynamics simulations together with free energy perturbation. Each of these proteins was embedded in a Lo membrane consisting of DSPC, cholesterol, and varying levels (0–16 mol%) of SDPE. First, the lipids were allowed to reorganize during a 10 microsecond simulations. Then, for each protein and for each SDPE concentration, the DSPC lipids were mutated into DOPC ones and the free energy of this change was calculated. This process was repeated in the absence of the proteins for each SDPE concentration. By substracting the corresponding values for the protein-containing and protein-free cases, the free energy of transfer between Lo and Ld domains was calculated for each of the proteins as a function of SDPE concentration. All simulations were performed using the Martini force field [1] and the GROMACS simulation package [2]. For more details of the setup and the simulations, please see the related paper at DOI: 10.1371/journal.pcbi.1007033. The original equilibration simulations (10 microseconds in the presence of the protein and SDPE and shorter in the absence of either SDPE or the protein). The run input files for these simulations are provided as X_PUFAY_EQ.tpr and the trajectories as X_PUFAY_EQ.xtc, where X stands for the protein (or says 'NOPROT' for the case without protein) and Y for the SDPE concentration. The run input files for the free energy of transfer simulations are provided as the tar files; one tar for each protein and one for the protein-free case. Each of these tars contains a folder for each used SDPE concentration, including the more realistic membrane compositions (with a suffix 'REAL'). For each SDPE concentration, the run input files (tpr) and the simulation input parameter files (mdp) for each window in the free energy perturbation are provided. Here, the windows are numbered from 0 to 26, where 0 corresponds to DSPC and 26 to DOPC. Also, for each SDPE concentration, common topology (top), index (ndx) and start configuration (gro) are provided. The molecule definitions (itp) are provided in the TOP.tar archive. [1] DOI: 10.1021/jp071097f ; DOI: 10.1021/ct700324x ; DOI: 10.1021/ct300646g [2] DOI: 10.1016/j.softx.2015.06.001

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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