Research article
A proposed syntax for Minimotif Semantics, version 1
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* Corresponding authors: Michael R Gryk gryk@uchc.edu - Martin R Schiller martin.schiller@unlv.edu
1 Department of Molecular, Microbial, and Structural Biology, University of Connecticut Health Center, 263 Farmington Ave. Farmington, CT 06030-3305 USA
2 Department of Computer Science and Engineering, University of Connecticut, 371 Fairfield Rd., Storrs, CT 06269-2155 USA
3 University of Nevada, Las Vegas, School of Life Sciences, 4505 Maryland Pkwy., Las Vegas, NV 89154-4004 USA
BMC Genomics 2009, 10:360 doi:10.1186/1471-2164-10-360
Published: 5 August 2009Abstract
Background
One of the most important developments in bioinformatics over the past few decades has been the observation that short linear peptide sequences (minimotifs) mediate many classes of cellular functions such as protein-protein interactions, molecular trafficking and post-translational modifications. As both the creators and curators of a database which catalogues minimotifs, Minimotif Miner, the authors have a unique perspective on the commonalities of the many functional roles of minimotifs. There is an obvious usefulness in standardizing functional annotations both in allowing for the facile exchange of data between various bioinformatics resources, as well as the internal clustering of sets of related data elements. With these two purposes in mind, the authors provide a proposed syntax for minimotif semantics primarily useful for functional annotation.
Results
Herein, we present a structured syntax of minimotifs and their functional annotation. A syntax-based model of minimotif function with established minimotif sequence definitions was implemented using a relational database management system (RDBMS). To assess the usefulness of our standardized semantics, a series of database queries and stored procedures were used to classify SH3 domain binding minimotifs into 10 groups spanning 700 unique binding sequences.
Conclusion
Our derived minimotif syntax is currently being used to normalize minimotif covalent chemistry and functional definitions within the MnM database. Analysis of SH3 binding minimotif data spanning many different studies within our database reveals unique attributes and frequencies which can be used to classify different types of binding minimotifs. Implementation of the syntax in the relational database enables the application of many different analysis protocols of minimotif data and is an important tool that will help to better understand specificity of minimotif-driven molecular interactions with proteins.