An extensible automated protein annotation tool: standardizing input and output using validated XML

Motivation: There is a frequent need to apply a large range of local or remote prediction and annotation tools to one or more sequences. We have created a tool able to dispatch one or more sequences to assorted services by defining a consistent XML format for data and annotations. Results: By analyzing annotation tools, we have determined that annotations can be described using one or more of the six forms of data: numeric or textual annotation of residues, domains (residue ranges) or whole sequences. With this in mind, XML DTDs have been designed to store the input and output of any server. Plug-in wrappers to a number of services have been written which are called from a master script. The resulting APATML is then formatted for display in HTML. Alternatively further tools may be written to perform post-analysis.

Predicting protein structures and structural annotation of proteomes

Protein structure prediction methods aim to predict the structures of proteins from their amino acid sequences, utilizing various computational algorithms. Structural genome annotation is the process of attaching biological information to every protein encoded within a genome via the production of three-dimensional protein models.

Proteornics analysis unravels the functional repertoire of coronavirus nonstructural protein 3

Severe acute respiratory syndrome (SARS) coronavirus infection and growth are dependent on initiating signaling and enzyme actions upon viral entry into the host cell. Proteins packaged during virus assembly may subsequently form the first line of attack and host manipulation upon infection. A complete characterization of virion components is therefore important to understanding the dynamics of early stages of infection. Mass spectrometry and kinase profiling techniques identified nearly 200 incorporated host and viral proteins. We used published interaction data to identify hubs of connectivity with potential significance for virion formation. Surprisingly, the hub with the most potential connections was not the viral M protein but the nonstructurall protein 3 (nsp3), which is one of the novel virion components identified by mass spectrometry. Based on new experimental data and a bioinformatics analysis across the Coronaviridae, we propose a higher-resolution functional domain architecture for nsp3 that determines the interaction capacity of this protein. Using recombinant protein domains expressed in Escherichia coli, we identified two additional RNA-binding domains of nsp3. One of these domains is located within the previously described SARS-unique domain, and there is a nucleic acid chaperone-like domain located immediately downstream of the papain-like proteinase domain. We also identified a novel cysteine-coordinated metal ion-binding domain. Analyses of interdomain interactions and provisional functional annotation of the remaining, so-far-uncharacterized domains are presented. Overall, the ensemble of data surveyed here paint a more complete picture of nsp3 as a conserved component of the viral protein processing machinery, which is intimately associated with viral RNA in its role as a virion component.

Proteogenomics and in silico structural and functional annotation of the barley powdery mildew Blumeria graminis f. sp. hordei

Blumeria graminis is an economically important obligate plant-pathogenic fungus, whose entire genome was recently sequenced and manually annotated using ab initio in silico predictions [7]. Employing large scale proteogenomic analysis we are now able to verify independently the existence of proteins predicted by 24% of open reading frame models. We compared the haustoria and sporulating hyphae proteomes and identified 71 proteins exclusively in haustoria, the feeding and effector-delivery organs of the pathogen. These proteins are ‘significantly smaller than the rest of the protein pool and predicted to be secreted. Most do not share any similarities with Swiss–Prot or Trembl entries nor possess any identifiable Pfam domains. We used a novel automated prediction pipeline to model the 3D structures of the proteins, identify putative ligand binding sites and predict regions of intrinsic disorder. This revealed that the protein set found exclusively in haustoria is significantly less disordered than the rest of the identified Blumeria proteins or random (and representative) protein sets generated from the yeast proteome. For most of the haustorial proteins with unknown functions no good templates could be found, from which to generate high quality models. Thus, these unknown proteins present potentially new protein folds that can be specific to the interaction of the pathogen with its host.