An evaluation of human protein-protein interaction data in the public domain

Mathivanan, Suresh; Periaswamy, Balamurugan; Gandhi, Tejas; Kandasamy, Kumaran; Suresh, Shubha; Mohmood, Riaz; Ramachandra, Y. L.; Pandey, Akhilesh

doi:10.1186/1471-2105-7-s5-s19

Cited by 194 publications

(161 citation statements)

References 29 publications

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“…We find the trend to be present in many interaction datasets that are based on both literature curation efforts and high-throughput screens (SI Table 6) (18,20). Because these datasets have small overlap among each other (23), it is reasonable to assume that in a complete interaction network, one would observe the same result. Furthermore, the trend is present in two different estimations of positive selection based on the dN/dS ratio test (6,10).…”

mentioning

confidence: 65%

Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context

Kim

Korbel

Gerstein

2007

Proc. Natl. Acad. Sci. U.S.A.

131

128

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Because of recent advances in genotyping and sequencing, human genetic variation and adaptive evolution in the primate lineage have become major research foci. Here, we examine the relationship between genetic signatures of adaptive evolution and network topology. We find a striking tendency of proteins that have been under positive selection (as compared with the chimpanzee) to be located at the periphery of the interaction network. Our results are based on the analysis of two types of genome evolution, both in terms of intra-and interspecies variation. First, we looked at single-nucleotide polymorphisms and their fixed variants, single-nucleotide differences in the human genome relative to the chimpanzee. Second, we examine fixed structural variants, specifically large segmental duplications and their polymorphic precursors known as copy number variants. We propose two complementary mechanisms that lead to the observed trends. First, we can rationalize them in terms of constraints imposed by protein structure: We find that positively selected sites are preferentially located on the exposed surface of proteins. Because central network proteins (hubs) are likely to have a larger fraction of their surface involved in interactions, they tend to be constrained and under negative selection. Conversely, we show that the interaction network roughly maps to cellular organization, with the periphery of the network corresponding to the cellular periphery (i.e., extracellular space or cell membrane). This suggests that the observed positive selection at the network periphery may be due to an increase of adaptive events on the cellular periphery responding to changing environments.protein structure ͉ network centrality ͉ single-nucleotide change ͉ copy number variant ͉ structural variant W ith the advent of genomic sequence data and, more recently, large-scale genetic variation data (1, 2), it has become possible to examine genes or genomic regions for signs of recent evolutionary adaptation in our genome, characterized as signatures of positive selection (3, 4). Typically, tests for positive selection predict adaptation by testing and rejecting the hypothesis of neutral mutation (5) or variation for a given genomic region.Despite considerable advances in the field of genetics, the actual molecular relationship of recent evolutionary events with biophysical properties of associated proteins such as structural characteristics and network connectivity (i.e., protein interactions) has as yet not been studied in detail. Understanding the extent of recent mutations, polymorphisms, and adaptation beyond their effect on the gene level is crucial because most complex cellular processes only come about through the interplay and interactions of many different proteins. On the other hand, although recent proteomic surveys have suggested that proteins with many interaction partners are subject to considerable structural constraints, the connection with human genome variation has not yet been considered. Thus, by combining knowledge fr...

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mentioning

confidence: 65%

Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context

Kim

Korbel

Gerstein

2007

Proc. Natl. Acad. Sci. U.S.A.

131

128

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“…As there are so many protein-protein interaction database publicly and each database has their own features, we constructed an in-house database with HPRD, IntAct, MIPS, BIND, DIP, MINT, PDZBase and Reactome databases recommended by a previous study (Mathivanan et al, 2006). To demonstrate the potential relationships among the differentially expressed genes, we matched the differentially expressed genes to PPI data that have been collected from the above in-house database.…”

Section: Protein-protein Interaction Network Constructionmentioning

confidence: 99%

Meta-analysis of Gene Expression Data Identifies Causal Genes for Prostate Cancer

Wang¹,

Hao²,

Zhou³

et al. 2013

Asian Pacific Journal of Cancer Prevention

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“…For a review of these databases focusing on human-specific interactions, see [30]. These datasets vary according to the quality of the data source and curation that they offer.…”

Section: Interaction Networkmentioning

confidence: 99%

From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV‐1 replication

Börner

Hermle

Sommer

et al. 2010

Biotechnology Journal

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RNA interference (RNAi) has emerged as a powerful technique for studying loss‐of‐function phenotypes by specific down‐regulation of gene expression, allowing the investigation of virus‐host interactions by large‐scale high‐throughput RNAi screens. Here we present a robust and sensitive small interfering RNA screening platform consisting of an experimental setup, single‐cell image and statistical analysis as well as bioinformatics. The workflow has been established to elucidate host gene functions exploited by viruses, monitoring both suppression and enhancement of viral replication simultaneously by fluorescence microscopy. The platform comprises a two‐stage procedure in which potential host factors are first identified in a primary screen and afterwards re‐tested in a validation screen to confirm true positive hits. Subsequent bioinformatics allows the identification of cellular genes participating in metabolic pathways and cellular networks utilised by viruses for efficient infection. Our workflow has been used to investigate host factor usage by the human immunodeficiency virus‐1 (HIV‐1), but can also be adapted to other viruses. Importantly, we expect that the description of the platform will guide further screening approaches for virus‐host interactions. The ViroQuant‐CellNetworks RNAi Screening core facility is an integral part of the recently founded BioQuant centre for systems biology at the University of Heidelberg and will provide service to external users in the near future.

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An evaluation of human protein-protein interaction data in the public domain

Cited by 194 publications

References 29 publications

Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context

Positive selection at the protein network periphery: Evaluation in terms of structural constraints and cellular context

Meta-analysis of Gene Expression Data Identifies Causal Genes for Prostate Cancer

From experimental setup to bioinformatics: An RNAi screening platform to identify host factors involved in HIV‐1 replication

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