BMC Systems Biology

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Calculation of the relative metastabilities of proteins in subcellular compartments of Saccharomyces cerevisiae

Jeffrey M Dick

Author Affiliations

Department of Earth and Planetary Science, University of California, 307 McCone Hall, #4767 Berkeley, CA 94720-4767, USA

Current address : School of Earth and Space Exploration, Arizona State University, P.O. Box 871404, Tempe, AZ 85287-1404, USA

BMC Systems Biology 2009, 3:75 doi:10.1186/1752-0509-3-75

Published: 18 July 2009

Additional files

Additional file 1:

Program script and data files for generating figures. This program script and supporting files were used to generate the figures shown above. To generate the figures, the contents of the zip file can be placed into the R working directory before loading the CHNOSZ package (version 0.8). Then read in the script with source('plot.R'). More details on the operation are provided at the top of the script file.

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Additional file 2:

Amino acid compositions of reference model proteins. Overall amino acid compositions of proteins in subcellular locations of S. cerevisiae were calculated from YeastGFP localization [8] and abundance [9] data downloaded from http://yeastgfp.ucsf.edu/ webcite combined with protein compositions downloaded from the Saccharomyces Genome Database http://www.yeastgenome.org/ webcite. The amino acid compositions of the reference model proteins were used to calculate the properties listed in Table 3.

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Additional file 3:

Interactions between subcellular compartments in yeast. This file lists statements from Refs. [43,47,46,50] used to identify the interactions between proteins in different compartments of Saccharomyces cerevisiae that are listed in Table 4.

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Additional file 4:

Intercompartmental protein reactions. This table lists chemical reactions between residue equivalents of reference model proteins for interactions identified above. The charges of the reference model proteins were calculated at 25°C, 1 bar and pH = 7.

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Additional file 5:

Abundance data for model proteins for compartments. For the up to 50 most abundant model proteins in each compartment are listed the ORF name, sequence length, average nominal oxidation state of carbon (Eqn. 6), computed standard molal Gibbs energy at 25°C and 1 bar of the ionized protein and charge at pH = 7 and calculated and experimental logarithm of activity. This file also identifies the outlying points labeled with letters in Fig. 3.

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Additional file 6:

Abundance comparison for model proteins for compartments and complexes. Scatterplots of experimental vs. calculated logarithm of activity of model proteins in subcellular compartments were generated for a range of logarithm of oxygen fugacity from -82 to -70.5. The legend of each diagram indicates the logarithm of oxygen fugacity ("O2"in the legend), root mean square deviation ("rmsd" in the legend; RMSD in Eqn. 7) and the Spearman rank correlation coefficient ("rr" in the legend; ρ in Eqn. 8).

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Additional file 7:

Identities of proteins in selected complexes. Lists the proteins in the selected model complexes and whether their abundances are reported in the YeastGFP dataset. Proteins without experimental abundance data were not used in the comparisons discussed in this study.

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Additional file 8:

Plots of relative abundances of model proteins for complexes. The calculated relative abundances of model proteins in selected complexes are shown as a function of log .

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Additional file 9:

Abundance data for model proteins for complexes. For model proteins in selected complexes (see Additional File 7) are listed the ORF name, sequence length, average nominal oxidation state of carbon (Eqn. 6), computed standard molal Gibbs energy at 25°C and 1 bar of the ionized protein and charge at pH = 7 and calculated and experimental logarithm of activity.

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Additional file 10:

Calculation of p-values for abundance rank correlations. This file lists calculated p-values for the Spearman rank correlation coefficients and describes the steps used in the calculations.

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