Bioinformatics Advance Access originally published online on August 12, 2008
Bioinformatics 2008 24(20):2412-2413; doi:10.1093/bioinformatics/btn427
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MPSQ: a web tool for protein-state searching
1Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, 2SCBIT-Inforsense Joint Lab, Shanghai Center for Bioinformation Technology, 100 Qinzhou Road, Shanghai 200235, 3Life Science and Technology College of Shanghai Jiao Tong University, Shanghai and 4School of Life Sciences, Fudan University, Shanghai 200433, China
*To whom correspondence should be addressed.
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ABSTRACT |
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 TOP ABSTRACT 1 INTRODUCTION2 FUNCTION AND USAGE3 CONCLUSION AND PERSPECTIVEACKNOWLEDGEMENTSREFERENCES |
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Summary: MPSQ (multi-protein-states query) is a web-based tool for the discovery of protein states (e.g. biological interactions, covalent modifications, cellular localizations). In particular, large sets of genes can be used to search for enriched state transition network maps (NMs) and features facilitating the interpretation of genomic-scale experiments such as microarrays. One NM collects all the catalogued states of a protein as well as the mutual transitions between the states. For the returned NM, graph visualization is provided for easy understanding and to guide further analysis.
Availability: MPSQ is freely available via the web at http://mpsq.biosino.org/.
Contact: phao{at}sibs.ac.cn; liulei{at}scbit.org; yxli{at}sibs.ac.cn
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1 INTRODUCTION |
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TOPABSTRACT1 INTRODUCTION2 FUNCTION AND USAGE3 CONCLUSION AND PERSPECTIVEACKNOWLEDGEMENTSREFERENCES |
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Currently, the state of a protein is commonly characterized in four ways: (1) small molecule binding information; (2) covalent modifications; (3) interaction with other proteins and (4) sub-cellular localization (Li et al., 2002). Normally, the state transition of a protein induces changes in protein function or properties mainly around the above four aspects. Typically, in certain biological processes, such as cellular signaling, a critical biological switch can be triggered by state transitions of a protein, thus initiating various communication mechanisms.
Compared to an individual state, the protein-state transition events, which can be linked to form a transition network map (NM) integrated with related information, will provide a detailed dynamic information flow about signal transductions among different states. Furthermore, such NM gives a holistic view of how functionally cooperative proteins are mediated by the state transitions.
Recently, a database of the alliance for cellular signaling (AfCS) (Gilman et al., 2002) called Molecule Pages (Li et al., 2002; Saunders et al., 2007) was established to catalogue state information of key proteins in cellular signaling, with the objective of providing building blocks for reconstructing signaling networks. To make full use of this invaluable knowledge resource, especially for the interpretation of the output from high-throughput experiments, e.g. microarrays, we developed a web interface named MPSQ (multi-protein-states query) to assist in the discovery of protein states as well as the enriched transition NMs for a given list of user-specified input genes. We also integrated protein–protein interaction (PPI) data and information from protein biochemical states to permit explicit gene-function linkage queries.
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2 FUNCTION AND USAGE |
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TOPABSTRACT1 INTRODUCTION2 FUNCTION AND USAGE3 CONCLUSION AND PERSPECTIVEACKNOWLEDGEMENTSREFERENCES |
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MPSQ is a publicly accessible web tool with a user-friendly interface, aimed at presenting protein-state information to the biological research community in the most intuitive way. Multiple types of query identifiers are allowed, e.g. Entrez gene ID (Maglott et al., 2007), and the returned information is a mapping between genes and states which are hyperlinked directly to the detail information.
While a state consists of interacting proteins, covalent modifications, bound small molecules, etc., a NM consists of all curated states of a key protein. The concept of ‘network map’ is inherited from the Molecule Pages (Li et al., 2002). An NM is a directed graph in which the vertex represents one particular state of the key protein and the edge represents the transition between states. In other words, one NM collects all the catalogued states of a key protein. Meanwhile, the transition relationships between the numerous states of the NM link the proteins which serve as constituents of the states together, generating a functional block of these proteins. Therefore, for query genes, checking if they participate in the same NM would be of assistance in discovering the functions and relations between them. For instance, if protein A and B are found in the NM of the key protein C, both of them have interactions with C in same or different states, and thus are functionally linked through C. Similarly if a group of genes are found in one NM, they have cooperative functional linkages through interactions with the key protein of the NM. MPSQ returns the NM search result as a table including four fields, NM ID, core protein ID, genes found in the NM and P-value from the hypergeometric distribution-based enrichment analysis. All the states of the NM are listed, and all query genes involved in a given NM are highlighted when a user clicks a NM ID link.
To help users better understand a NM, an interactive picture was generated for NM visualization. An example NM picture is illustrated in Figure 1: each node represents a state, with the green node representing the states in which any query genes were found. In contrast, other states of the NM are colored red. Directed arrows between nodes represent the state transitions.
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While the NM presents states and their mutual transitions, explicit functional linkages, e.g. physical interactions between the query genes reflect their molecular-level relationships. MPSQ uses protein–protein interaction data derived from curated biochemical protein-state information to present such molecular-level linkages. Internally a vertex-induced subgraph strategy is adopted. In order to find a more indicative functional subgraph from the protein interaction network, MPSQ expands the vertex set by including both the query genes and their direct neighbors in the network. Thus, closely related genes will be selected and emerge as a compact subgraph that can be visualized with query genes highlighted as red for better understanding with the software ‘medusa’ (Hooper and Bork, 2005). As a complement and comparison, PPI data from other databases are also available for query. Currently, the PPI networks from the molecular interaction database (Chatr-aryamontri et al., 2007) and IntAct database (Kerrien et al., 2007) are integrated.
To facilitate users wishing to cross-reference existing databases, the Kyoto Encyclopedia of Genes and Genomes database (Kanehisa, 2002) pathway database and Gene Ontology (Ashburner et al., 2000) are stored locally and provided for query.
In addition to gene identifiers, users are able to specify a batch of state IDs to retrieve state information, with the search results being returned according to user's preferences—a feature allowing users to browse the data of most interest to them.
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3 CONCLUSION AND PERSPECTIVE |
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TOPABSTRACT1 INTRODUCTION2 FUNCTION AND USAGE3 CONCLUSION AND PERSPECTIVEACKNOWLEDGEMENTSREFERENCES |
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Proteins do not function in isolation, but rather as part of molecular networks (Saghatelian and Cravatt, 2005). Currently many databases collect the molecular interaction data, for instance, the STRING database (von Mering et al., 2003) contains protein functional associations for over 1 500 000 proteins. However, in the cellular context, proteins are also regulated by other mechanisms like small molecules, covalent modifications, etc. To give a more dynamic description of proteins in vivo, the pioneer LiveDIP database (Duan et al., 2002) collected states information of yeast proteins and aimed to describe protein interactions using the protein states and state transitions. The Molecule Pages database, first proposed a full definition of protein states and catalogued the state information for over 4000 key proteins which are believed to have important functions in cellular signaling (Li et al., 2002).
MPSQ is a web interface for Molecule Pages and designed to promote the utilization of biochemical protein-state information in the biological research community. Despite batch retrieval, MPSQ allows to search for enriched NMs which imply functional blocks. Compared to the most often used functional modules constructed from protein interaction networks (Segal et al., 2003), protein-state NM which includes all the states of the key protein is a dynamic outline of the protein in vivo. On the other hand, protein interaction data are integrated in MPSQ for protein functional linkage query.
MPSQ updates every month and has been run robustly for over 1 year. In the future more biological data will be integrated and analyzed in parallel with the states information. With the continuing accumulation of available state data and ongoing integration with other biological resources, MPSQ will provide more functions in systems biology research.
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ACKNOWLEDGEMENTS |
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TOPABSTRACT1 INTRODUCTION2 FUNCTION AND USAGE3 CONCLUSION AND PERSPECTIVEACKNOWLEDGEMENTSREFERENCES |
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We thank Haiwei Fan for technical help. We also thank the anonymous reviewers for their helpful suggestions.
Funding: National High-Tech R&D Program of China (863) (grant 2006AA02Z334, 2007AA02Z304, 2006AA020406, 2007DFA31040); Shanghai Committee of Science and Technology (grant 07dz22004, 07ZR14085); the National Basic Research Program of China (grant 2006CB910700, 2003CB715901); the Key Research Program of Chinese Academy of Sciences (grant KSCX2-YW-R-112).
Conflict of Interest: none declared.
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FOOTNOTES |
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Associate Editor: Jonathan Wren
Received on May 22, 2008; revised on July 13, 2008; accepted on August 12, 2008
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