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Computational characterization of moonlighting proteins.

ABSTRACT: Moonlighting proteins perform multiple independent cellular functions within one polypeptide chain. Moonlighting proteins switch functions depending on various factors including the cell-type in which they are expressed, cellular location, oligomerization status and the binding of different ligands at different sites. Although an increasing number of moonlighting proteins have been experimentally identified in recent years, the quantity of known moonlighting proteins is insufficient to elucidate their overall landscape. Moreover, most moonlighting proteins have been identified as a serendipitous discovery. Hence, characterization of moonlighting proteins using bioinformatics approaches can have a significant impact on the overall understanding of protein function. In this work, we provide a short review of existing computational approaches for illuminating the functional diversity of moonlighting proteins.

SUBMITTER: Khan IK

PROVIDER: S-EPMC5003571 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Computational characterization of moonlighting proteins.

Khan Ishita K IK Kihara Daisuke D

Biochemical Society transactions 20141201 6

Moonlighting proteins perform multiple independent cellular functions within one polypeptide chain. Moonlighting proteins switch functions depending on various factors including the cell-type in which they are expressed, cellular location, oligomerization status and the binding of different ligands at different sites. Although an increasing number of moonlighting proteins have been experimentally identified in recent years, the quantity of known moonlighting proteins is insufficient to elucidate ...[more]

PMID: 25399606

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Project description:Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.First, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter's primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.This article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.

Dataset Information

Computational characterization of moonlighting proteins.

Publications

Computational characterization of moonlighting proteins.

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