Evolution and Topology in the Yeast Protein Interaction Network

Wuchty, Stefan

doi:10.1101/gr.2300204

Cited by 133 publications

(91 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For convenience, we will consider the corresponding interaction networks linking genes whose protein products interact physically and we will refer to the topological parameters of these gene interaction networks. Several authors have found that the fraction of essential genes is 3 to 5 times higher among highly connected genes than among low-connected genes and have proposed that the phenotypic consequences of a gene deletion in yeast are affected to a large extent by the gene degree in the interaction networks ( Jeong et al 2001;Wuchty 2004;Yu et al 2004). However these analyses used data derived from Uetz et al (2000) and/or from the DIP database (Xenarios et al 2000), which present some biases.…”

Section: Results (A)mentioning

confidence: 99%

Gene essentiality and the topology of protein interaction networks

et al. 2005

View full text Add to dashboard Cite

The mechanistic bases for gene essentiality and for cell mutational resistance have long been disputed. The recent availability of large protein interaction databases has fuelled the analysis of protein interaction networks and several authors have proposed that gene dispensability could be strongly related to some topological parameters of these networks. However, many results were based on protein interaction data whose biases were not taken into account. In this article, we show that the essentiality of a gene in yeast is poorly related to the number of interactants (or degree) of the corresponding protein and that the physiological consequences of gene deletions are unrelated to several other properties of proteins in the interaction networks, such as the average degrees of their nearest neighbours, their clustering coefficients or their relative distances. We also found that yeast protein interaction networks lack degree correlation, i.e. a propensity for their vertices to associate according to their degrees. Gene essentiality and more generally cell resistance against mutations thus seem largely unrelated to many parameters of protein network topology.

show abstract

Section: Results (A)mentioning

confidence: 99%

Gene essentiality and the topology of protein interaction networks

et al. 2005

View full text Add to dashboard Cite

show abstract

“…The indispensability of a gene defines its functional significance and when such genes are knocked out the cell becomes unviable [15]. The yeast PIN has also been the objective of several other topological analyses aimed at the detection of protein functionality and evolution [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Virtual identification of essential proteins within the protein interaction network of yeast

2006

View full text Add to dashboard Cite

Topological analysis of large scale protein-protein interaction networks (PINs) is important for understanding the organisational and functional principles of individual proteins. The number of interactions that a protein has in a PIN has been observed to be correlated with its indispensability. Essential proteins generally have more interactions than the non-essential ones. We show here that the lethality associated with removal of a protein from the yeast proteome correlates with different centrality measures of the nodes in the PIN, such as the closeness of a protein to many other proteins, or the number of pairs of proteins which need a specific protein as an intermediary in their communications, or the participation of a protein in different protein clusters in the PIN. These measures are significantly better than random selection in identifying essential proteins in a PIN. Centrality measures based on graph spectral properties of the network, in particular the subgraph centrality, show the best performance in identifying essential proteins in the yeast PIN. Subgraph centrality gives important structural information about the role of individual proteins and permits the selection of possible targets for rational drug discovery through the identification of essential proteins in the PIN.

show abstract

“…16 Previously, there was not a consensus whether hubs were slower-evolving than other proteins or not. 2,5,12,30 Kim et al 16 by integrating structures into protein interaction networks stated that multi-interface hubs were more likely to be essential and more conserved, being members of large and stable complexes as opposed to singlish-interface hubs. In a proceeding study, they found that although singlishinterface hub proteins were more disordered, their interfaces were highly structured, as is the case for multi-interface hubs.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Hot Region Organization in Hub Proteins

2010

View full text Add to dashboard Cite

Abstract-Protein interaction maps constructed from binary interactions reveal that some proteins are highly connected to others (acting as hub proteins), whereas some others have a few interactions (at the edges of the map). This paper addresses hub proteins from a structural point: interfaces. It investigates how hot spots are organized in hub proteins (hot regions). We annotate interfaces as the ones between two date-hubs (DD), two party hubs (PP), and two non-hubs (NN). We investigate the physico-chemical properties of these three types of interfaces focusing on the accessible surface area distribution, hot region organization, and amino acid composition differences. Results reveal that there are significant differences between DD and PP interfaces. More of the hot spots are organized into the hot regions in DD interfaces compared to PP ones. A high fraction of the interfaces are covered by hot regions in DD interfaces. There are more distinct hot regions in DDs. Since the same (or overlapping) DD interfaces should be used repeatedly, different hot regions can be used to bind to different partners. Further, these hot region characteristics can be used to predict whether a given hub interface is involved in a DD or a PP interface type with 80% accuracy.

show abstract

Evolution and Topology in the Yeast Protein Interaction Network

Cited by 133 publications

References 27 publications

Gene essentiality and the topology of protein interaction networks

Gene essentiality and the topology of protein interaction networks

Virtual identification of essential proteins within the protein interaction network of yeast

Analysis of Hot Region Organization in Hub Proteins

Contact Info

Product

Resources

About