GWIDD: a comprehensive resource for genome-wide structural modeling of protein-protein interactions
© Kundrotas et al.;licensee BioMed Central Ltd. 2012
Received: 27 June 2012
Accepted: 11 July 2012
Published: 11 July 2012
Protein-protein interactions are a key component of life processes. The knowledge of the three-dimensional structure of these interactions is important for understanding protein function. Genome-Wide Docking Database (http://gwidd.bioinformatics.ku.edu) offers an extensive source of data for structural studies of protein-protein complexes on genome scale. The current release of the database combines the available experimental data on the structure and characteristics of protein interactions with structural modeling of protein complexes for 771 organisms spanned over the entire universe of life from viruses to humans. The interactions are stored in a relational database with user-friendly interface that includes various search options. The search results can be interactively previewed; the structures, downloaded, along with the interaction characteristics.
Proteins function by interacting with other biologically relevant molecules. Understanding the mechanisms of protein-protein interactions (PPI) is essential for studying life processes at the molecular level. Genome sequencing provided a vast amount of information on proteins at the sequence level. Currently, efforts focus on the function assignment of these proteins based on their three-dimensional (3D) structures and interactions. Interaction maps for specific organisms and biochemical pathways need to be complemented by the structural information. Experimental techniques are limited in their ability to produce the structures on the genome scale. Thus, computational methods are essential for this task .
Structural modeling of PPI has its origins in ab initio techniques based on shape and physicochemical complementarity. More recent approaches take advantage of statistical potentials and machine learning [2, 3]. Despite progress in development of such template-free algorithms, their accuracy in the high-throughput structure determination is limited.
Rapidly increasing amount of data on PPI makes possible application of the template-based methods. Such approaches are based on the observation that monomers with similar sequences and/or structures, generally, have similar binding modes. Several groups assessed the quality of PPI modeling based on sequence alignment to complexes with known structure [4–9]. Studies showed that the majority of such homology-docking models are of acceptable and medium quality, according to the established criteria . An alternative template-based approach takes advantage of the structural similarity between the target and the template complexes [10–13].
The progress in 3D modeling of PPI is reflected in the Genome-Wide Docking Database (GWIDD) , which provides annotated collection of experimental and modeled PPI structures from the entire universe of life spanning from viruses to humans. The resource has user-friendly search interface, providing preview and download options for experimental and modeled PPI structures.
The user can enable the second half of the search interface if information related to the interaction partner is available (‘protein B,’ Figure 2). The search results can be filtered by the structure availability (experimental, modeled, or no structures). Online help is provided in pop-up windows. The search result screen displays all interactions in the database satisfying the input search criteria in the form of an expandable list of GWIDD interaction IDs. For the homology-docking models, the alignments used to build the model are provided, and the model quality is assessed by the sequence identity criteria . Links are provided to download the PDB-format files, along with the text file containing relevant information. Visualization screen is available to display the structures by different interactive representations. A link is provided to download the entire set of sequence-homology models in one gzipped archive.
GWIDD development will incorporate other structural modeling techniques, such as multi-template/threading modeling of interacting proteins, partial structural alignment , and template-free docking by GRAMM [23–25]. A major expansion of GWIDD will be the incorporation of new PPI sources from other publicly available PPI databases. Large-scale systematic benchmarking of the high-through put modeling will be used to assign a confidence score to the modeled structures.
Andrey Tovchigrechko and Tatiana Baronova made important contributions to the GWIDD project at the earlier stages of development. This work was supported by the National Institutes of Health grant R01 GM074255.
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