Computational protocol: B-Pred, a structure based B-cell epitopes prediction server

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Protocol publication

[…] The templates for the protein models were identified by HMM-HMM comparison using the pdb70_7Mar09 Hidden Markov Model (HMM) database via the HHpred server. Psiblast was used for the Multiple Sequence Alignment (MSA) generation method with three MSA generation iterations and a local alignment mode. The E-value threshold was set at 1E-3 for MSA generation and the minimum coverage threshold for MSA hits was set at 20%. Structures predictions were performed by the MODELLER software, using the optimal multiple template of the HHpred server. [...] The Naccess software, was used to calculate the solvent exposure of each residue using the full quaternary structure of the protein (ie, including all protein chains) as input. These solvent exposure values were then compared with the values obtained when using single protein chains as input. The difference in solvent accessibility was calculated in these two cases for each residue. This difference is zero if the residue is not located within a protein-protein interface, and has a negative value otherwise. This simple method allows for the easy identification of the residues located at interfaces, which are subsequently highlighted in the output of the web server’s analysis. [...] For the ElliPro method, the dataset was analyzed using the protein models with the default ElliPro parameters. Of all the predicted epitopes, only the linear ones were considered in the analysis. For the LEPD and the CBTOPE methods, the analysis was performed using the default parameters.For the purpose of this analysis, five different randomized datasets were generated from the main dataset, thereby generating five “test set/training set” pairs. In order to minimize possible biases in the randomization process, each pair was evaluated as an independent training and test set. The performance values were determined by the mean values of the five independent determinations. [...] B-Pred was developed on a Linux Ubuntu 10.04 server running PHP 5.2.3, Perl 5.10.1, Naccess version 2.1.1, and the current release of V3D ( The web server interface, web forms, and data output were written using HTML4.01/CSS and PHP.First, the user uploads or selects a model or structure to work with. After uploading the model or retrieving the structure from the Protein Data Bank (PDB), a job folder is created on the server by a PHP script where the model data and all subsequent analysis data are stored. A job password is then created and stored in a dedicated text file. Once the model file is stored, an interface with the analysis options (sliding window step, analysis thresholds) is shown to the user. After selecting the analysis parameters, the PHP script makes a call to a perl script ( that is in charge of all the analysis steps. The first task executed by the perl script is to call the Naccess application, and retrieve the Naccess solvent exposure data for the selected chain (computed alone) and the Naccess data for the full protein complex. Comparing the data for the chain alone and the data from the full complex identifies the interface residues. The structural data for the selected chain are then analyzed for local model quality by the perl script, which then calls the V3D software. Naccess data, V3D data, and interface determinations are then stored in a text file in csv format. Next, the PHP script reads this detailed analysis file to format the results and generate the server output. presents the server algorithm. With this data, a visualization of the structure is dynamically provided through the Jmol applet. Finally, solvent exposure and model quality charts from the server output are dynamically generated using the JpGraph PHP software. […]

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