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Bcepred: Prediction of linear B-cell epitopes, using physico-chemical properties

We evaluated the performance of existing linear B-cell epitope prediction methods based on physico-chemical properties on a non-redundant dataset. The dataset consists of 1029 B-cell epitopes obtained from Bcipep database and equally number of non-epitopes obtained randomly from Swiss-Prot database. The prediction accuracy for models based of various properties varies from 52.92% and 57.53%. We achived highest accuracy of 58.70% at threshold 2.38, when we combined four amino acid properties( hydrophilicity, flexibility, polarity and exposed surface).

Based on our evaluation and analysis we have developed a web server Bcepred for predicting linear B-cell epitopes in a protein sequence. This server allows users to predict B-cell epitopes using any of the physico-chemical properties ( hydrophilicity, flexibility/mobility, accessibility, polarity, exposed surface and turns) or combination of properties.

It presents the results in graphical and tabular frame. In case of graphical frame, this server plot the residue properties along protein backbone, which assist the users in rapid visulaziation of B-cell epitope on protein. The peak of the amino acid residue segment above the threshold value (default is 2.38) is considered as predicted B-cell epitope. The tabular output is in the form of a table, which will give the normalized score of the selected properties with the corresponding amino acid residue of a protein along with the maximum, minimum and averages values of the combined methods, selected.

The server is able to predict epitopes with 58.7% accuracy using Flexibility, Hydrophilicity, Polarity, and Surface properties combined at a threshold of 2.38.

If you use this web server, please cite:
Saha.S and Raghava G.P.S. BcePred:Prediction of Continuous B-Cell Epitopes in Antigenic Sequences Using Physico-chemical Properties. In G.Nicosia, V.Cutello, P.J. Bentley and J.Timis (Eds.) ICARIS 2004, LNCS 3239, 197-204, Springer,2004.

contact:   G.P.S.Raghava                                                                  Department of Computational Biology                                                                 IMTECH