Dataset Information

PlantMP: a database for moonlighting plant proteins.

ABSTRACT: Moonlighting proteins are single polypeptide chains capable of executing two or more distinct biochemical and/or biological functions. Here, we describe the development of PlantMP, which is a manually curated online-based database of plant proteins that are known to `moonlight'. The database contains searchable UniProt IDs and names, canonical and moonlighting functions, gene ontology numbers, plant species as well as links to the PubMed indexed articles. Proteins homologous to experimentally confirmed moonlighting proteins from the model plant Arabidopsis thaliana are provided as a separate list of `likely moonlighters'. Additionally, we also provide a list of predicted Arabidopsis moonlighting proteins reported in the literature. Currently, PlantMP contains 110 plant moonlighting proteins, 10 `likely moonlighters' and 27 `predicted moonlighters'. Organizing plant moonlighting proteins in one platform enables researchers to conveniently harvest plant-specific raw and processed data such as the molecular functions, biological roles and structural features essential for hypothesis formulation in basic research and for biotechnological innovations.

SUBMITTER: Su B

PROVIDER: S-EPMC6482322 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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PlantMP: a database for moonlighting plant proteins.

Su Bo B Qian Zhuang Z Li Tianshu T Zhou Yuwei Y Wong Aloysius A

Database : the journal of biological databases and curation 20190101

Moonlighting proteins are single polypeptide chains capable of executing two or more distinct biochemical and/or biological functions. Here, we describe the development of PlantMP, which is a manually curated online-based database of plant proteins that are known to `moonlight'. The database contains searchable UniProt IDs and names, canonical and moonlighting functions, gene ontology numbers, plant species as well as links to the PubMed indexed articles. Proteins homologous to experimentally co ...[more]

PMID: 31032837

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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

PlantMP: a database for moonlighting plant proteins.

Publications

PlantMP: a database for moonlighting plant proteins.

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