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Open AccessJournal ArticleDOI

Global topological features of cancer proteins in the human interactome

Pall F. Jonsson, +1 more
- 15 Sep 2006 - 
- Vol. 22, Iss: 18, pp 2291-2297
TLDR
It is shown that cancer proteins contain a high ratio of highly promiscuous structural domains, i.e., domains with a high propensity for mediating protein interactions, reflecting the central roles of proteins, whose mutations lead to cancer.
Abstract
Motivation: The study of interactomes, or networks of protein-protein interactions, is increasingly providing valuable information on biological systems. Here we report a study of cancer proteins in an extensive human protein-protein interaction network constructed by computational methods. Results: We show that human proteins translated from known cancer genes exhibit a network topology that is different from that of proteins not documented as being mutated in cancer. In particular, cancer proteins show an increase in the number of proteins they interact with. They also appear to participate in central hubs rather than peripheral ones, mirroring their greater centrality and participation in networks that form the backbone of the proteome. Moreover, we show that cancer proteins contain a high ratio of highly promiscuous structural domains, i.e., domains with a high propensity for mediating protein interactions. These observations indicate an underlying evolutionary distinction between the two groups of proteins, reflecting the central roles of proteins, whose mutations lead to cancer. Contact: paul.bates@cancer.org.uk Supplementary information: The interactome data are available though the PIP (Potential Interactions of Proteins) web server at http://bmm.cancerresearchuk.org/servers/pip. Further additional material is available at http://bmm.cancerresearchuk.org/servers/pip/bioinformatics/

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Citations
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Journal ArticleDOI

Network Medicine: A Network-Based Approach to Human Disease

TL;DR: Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.
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The human disease network

TL;DR: This paper found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, while the vast majority of disease genes are non-essential and show no tendency to encoding hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network.
Journal Article

human disease network

TL;DR: It is found that essential human genes are likely to encode hub proteins and are expressed widely in most tissues, suggesting that disease genes also would play a central role in the human interactome, and that diseases caused by somatic mutations should not be peripheral.
Journal ArticleDOI

Interactome Networks and Human Disease

TL;DR: In this paper, the authors discuss different types of interactome networks and the insights that can come from analyzing them, including how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.
Journal Article

Interactome networks and human disease

TL;DR: Why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease are detailed.
References
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Journal ArticleDOI

Gene Ontology: tool for the unification of biology

TL;DR: The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Journal ArticleDOI

The Protein Data Bank

TL;DR: The goals of the PDB are described, the systems in place for data deposition and access, how to obtain further information and plans for the future development of the resource are described.
Journal ArticleDOI

The Pfam protein families database

TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
Journal ArticleDOI

Uncovering the overlapping community structure of complex networks in nature and society

TL;DR: After defining a set of new characteristic quantities for the statistics of communities, this work applies an efficient technique for exploring overlapping communities on a large scale and finds that overlaps are significant, and the distributions introduced reveal universal features of networks.
Journal ArticleDOI

Lethality and centrality in protein networks

TL;DR: It is demonstrated that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.
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