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Interface-Resolved Network of Protein-Protein Interactions

Overview of attention for article published in PLoS Computational Biology, May 2013
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Title
Interface-Resolved Network of Protein-Protein Interactions
Published in
PLoS Computational Biology, May 2013
DOI 10.1371/journal.pcbi.1003065
Pubmed ID
Authors

Margaret E. Johnson, Gerhard Hummer

Abstract

We define an interface-interaction network (IIN) to capture the specificity and competition between protein-protein interactions (PPI). This new type of network represents interactions between individual interfaces used in functional protein binding and thereby contains the detail necessary to describe the competition and cooperation between any pair of binding partners. Here we establish a general framework for the construction of IINs that merges computational structure-based interface assignment with careful curation of available literature. To complement limited structural data, the inclusion of biochemical data is critical for achieving the accuracy and completeness necessary to analyze the specificity and competition between the protein interactions. Firstly, this procedure provides a means to clarify the information content of existing data on purported protein interactions and to remove indirect and spurious interactions. Secondly, the IIN we have constructed here for proteins involved in clathrin-mediated endocytosis (CME) exhibits distinctive topological properties. In contrast to PPI networks with their global and relatively dense connectivity, the fragmentation of the IIN into distinctive network modules suggests that different functional pressures act on the evolution of its topology. Large modules in the IIN are formed by interfaces sharing specificity for certain domain types, such as SH3 domains distributed across different proteins. The shared and distinct specificity of an interface is necessary for effective negative and positive design of highly selective binding targets. Lastly, the organization of detailed structural data in a network format allows one to identify pathways of specific binding interactions and thereby predict effects of mutations at specific surfaces on a protein and of specific binding inhibitors, as we explore in several examples. Overall, the endocytosis IIN is remarkably complex and rich in features masked in the coarser PPI, and collects relevant detail of protein association in a readily interpretable format.

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The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
India 2 2%
United Kingdom 2 2%
Korea, Republic of 1 1%
Italy 1 1%
Germany 1 1%
Canada 1 1%
China 1 1%
Japan 1 1%
Unknown 81 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 31%
Researcher 27 30%
Student > Bachelor 7 8%
Student > Master 7 8%
Student > Postgraduate 6 7%
Other 14 15%
Unknown 2 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 51%
Biochemistry, Genetics and Molecular Biology 17 19%
Chemistry 5 5%
Computer Science 5 5%
Physics and Astronomy 4 4%
Other 9 10%
Unknown 5 5%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 May 2013.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from PLoS Computational Biology
#7,480
of 8,960 outputs
Outputs of similar age
#131,493
of 207,266 outputs
Outputs of similar age from PLoS Computational Biology
#83
of 106 outputs
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