  Characterization of B-cell protein epitope and developing critical parameters
for its identification is one of the long standing interests. Using Layers
algorithm, we introduced the concept of anchor residues to identify epitope. We
have shown that majority of the epitope is composed of anchor residues and have
significant bias in epitope for these residues. We optimized the search space
reduction for epitope identification. We used Layers to non-randomly sample the
antigen surface reducing the molecular surface to an average of 75 residues
while preserving 50% of the epitope in the sample surface. To facilitate the
comparison of favorite methods of researchers we compared the popular
techniques used to identify epitope with their sampling performance and
evaluation. We proposed an optimum Sr of 16 {\AA} to sample the antigen
molecules to reduce the search space, in which epitope is identified using
buried surface area method. We used the combinations of molecular surface
sampling, anchor residue intensity in surface, secondary structure and sequence
information to predict epitope at an accuracy of 89%. A web application is made
available at
http://www.csb.iitkgp.ernet.in/applications/b_cell_epitope_pred/main.
