Document Detail

Protein charge and mass contribute to the spatio-temporal dynamics of protein-protein interactions in a minimal proteome.
MedLine Citation:
PMID:  23420643     Owner:  NLM     Status:  MEDLINE    
We constructed and simulated a "minimal proteome" model using Langevin dynamics. It contains 206 essential protein types that were compiled from the literature. For comparison, we generated six proteomes with randomized concentrations. We found that the net charges and molecular weights of the proteins in the minimal genome are not random. The net charge of a protein decreases linearly with molecular weight, with small proteins being mostly positively charged and large proteins negatively charged. The protein copy numbers in the minimal genome have the tendency to maximize the number of protein-protein interactions in the network. Negatively charged proteins that tend to have larger sizes can provide a large collision cross-section allowing them to interact with other proteins; on the other hand, the smaller positively charged proteins could have higher diffusion speed and are more likely to collide with other proteins. Proteomes with random charge/mass populations form less stable clusters than those with experimental protein copy numbers. Our study suggests that "proper" populations of negatively and positively charged proteins are important for maintaining a protein-protein interaction network in a proteome. It is interesting to note that the minimal genome model based on the charge and mass of Escherichia coli may have a larger protein-protein interaction network than that based on the lower organism Mycoplasma pneumoniae.
Yu Xu; Hong Wang; Ruth Nussinov; Buyong Ma
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, N.I.H., Intramural; Research Support, Non-U.S. Gov't     Date:  2013-03-18
Journal Detail:
Title:  Proteomics     Volume:  13     ISSN:  1615-9861     ISO Abbreviation:  Proteomics     Publication Date:  2013 Apr 
Date Detail:
Created Date:  2013-04-12     Completed Date:  2013-09-20     Revised Date:  2014-04-02    
Medline Journal Info:
Nlm Unique ID:  101092707     Medline TA:  Proteomics     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  1339-51     Citation Subset:  IM    
Copyright Information:
© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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MeSH Terms
Bacterial Proteins / chemistry,  metabolism
Cluster Analysis
Computer Simulation
Cytoplasm / genetics,  metabolism
Escherichia coli Proteins / chemistry,  metabolism
Models, Biological*
Molecular Weight
Pneumonia, Mycoplasma / metabolism
Protein Interaction Maps / physiology*
Proteins / chemistry*,  genetics,  metabolism*
Grant Support
HHSN261200800001E/CA/NCI NIH HHS; HHSN261200800001E//PHS HHS
Reg. No./Substance:
0/Bacterial Proteins; 0/Escherichia coli Proteins; 0/Proteins; 0/Proteome

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