Literature DB >> 25653145

From the static interactome to dynamic protein complexes: Three challenges.

Chern Han Yong1, Limsoon Wong.   

Abstract

Protein interactions and complexes behave in a dynamic fashion, but this dynamism is not captured by interaction screening technologies, and not preserved in protein-protein interaction (PPI) networks. The analysis of static interaction data to derive dynamic protein complexes leads to several challenges, of which we identify three. First, many proteins participate in multiple complexes, leading to overlapping complexes embedded within highly-connected regions of the PPI network. This makes it difficult to accurately delimit the boundaries of such complexes. Second, many condition- and location-specific PPIs are not detected, leading to sparsely-connected complexes that cannot be picked out by clustering algorithms. Third, the majority of complexes are small complexes (made up of two or three proteins), which are extra sensitive to the effects of extraneous edges and missing co-complex edges. We show that many existing complex-discovery algorithms have trouble predicting such complexes, and show that our insight into the disparity between the static interactome and dynamic protein complexes can be used to improve the performance of complex discovery.

Keywords:  Protein complex; dynamism; protein interaction

Mesh:

Substances:

Year:  2015        PMID: 25653145     DOI: 10.1142/S0219720015710018

Source DB:  PubMed          Journal:  J Bioinform Comput Biol        ISSN: 0219-7200            Impact factor:   1.122


  4 in total

1.  Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-Expression.

Authors:  Xianjun Shen; Li Yi; Xingpeng Jiang; Tingting He; Xiaohua Hu; Jincai Yang
Journal:  PLoS One       Date:  2016-04-21       Impact factor: 3.240

2.  Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

Authors:  Xianjun Shen; Li Yi; Xingpeng Jiang; Tingting He; Jincai Yang; Wei Xie; Po Hu; Xiaohua Hu
Journal:  PLoS One       Date:  2017-10-18       Impact factor: 3.240

3.  Prediction of problematic complexes from PPI networks: sparse, embedded, and small complexes.

Authors:  Chern Han Yong; Limsoon Wong
Journal:  Biol Direct       Date:  2015-08-01       Impact factor: 4.540

4.  RocSampler: regularizing overlapping protein complexes in protein-protein interaction networks.

Authors:  Osamu Maruyama; Yuki Kuwahara
Journal:  BMC Bioinformatics       Date:  2017-12-06       Impact factor: 3.169

  4 in total

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