The Peptiope server can be used to computationally predict epitopes based on peptides extracted from a phage display library, or to align a linear peptide sequence onto a three dimensional protein structure.Epitope mapping using phage display libraries
The interaction between an antibody and its antigen is at the heart of the humoral immune response. An antibody's immunological activity depends upon its specific binding to a discrete site on its target antigen known as the epitope. Epitope mapping is the process of identifying the molecular determinants of the antigen that are recognized by the antibody. One strategy for epitope mapping involves the use of a phage display library. This technology is used to select from a large set of random peptides, those with a high binding affinity to an antibody of interest. This set of peptides is regarded as mimicking the genuine epitope of the antibody's cognate antigen, and can be used to define it using computational methods. The methodology is a general technique that can also be used for detecting interfaces of various types of interacting proteins outside the immunological context.
A phage display library is a heterogeneous mixture of phage clones each carrying a different foreign DNA that is inserted into the reading frame of the phage surface protein. As such, each phage displays a different peptide on its surface. This technology is used to select from a large set of random peptides those with a high binding affinity to an antibody of interest. This selection process, termed biopanning, can be used to characterize the interacting interface of the antigen in the following manner. Let us assume that we are investigating an antibody and an antigen which are known to interact. A random peptide library is scanned against the antibody. The selected peptides are assumed to mimic the epitope in terms of physico-chemical properties and spatial organization. The algorithmic task is thus to utilize the information contained in the set of peptides, selected by the antibody, for correctly predicting the corresponding epitope on the surface of the antigen.
For epitope mapping, the standard input to Pepitope is a Protein Data Bank file of the antigen and a set of peptides selected by the antibody in a biopanning experiment. In the more general case, any protein with a solved 3D structure can be used as input and any peptide(s) can be aligned to this structure. The first output of the program is the alignment of each peptide to the 3D structure. When several peptides are aligned, the server implements a clustering algorithm to detect one or more patches of residues on the surface of the 3D structure. Thus, the second output is the predicted patches. For antigens, such a patch corresponds to a putative epitope site, and in general, a patch is a predicted interacting surface region.
Pepitope assumes that the peptides mimic surface residues (i.e., solvent exposed residues). Thus, buried residues are eliminated from the search. The exposed residues of the given structure are extracted using the Surface Racer program (Tsodikov et al. 2002).
The server implements three epitope mapping algorithms: PepSurf, Mapitope, and a combination of the two. The algorithms are shortly described below. A full description of the algorithms is given in the corresponding papers.
PepSurf aligns each peptide to a graph which represents the surface of the input 3D structure. The surface is represented as an undirected graph, in which vertices represent exposed residues, and two residues are connected by an edge if they are close to one another on the protein's surface. Each of the input peptides is aligned to the graph. Amino-acid similarities are scored using a substitution matrix. Further, unmatched peptide residues are allowed by combining gap-costs in the alignment scores. The substitution matrix and the gap costs can be adjusted by the user. Each aligned peptide corresponds to a path of residues on the 3D structure that exhibits a high similarity to the input peptide. The resulting paths are clustered and the epitope location is inferred.
Epitope mapping using Mapitope
Epitope mapping using the Combined algorithm
Peptide to structure alignment using PepSurf
Three-dimensional structures of biological macromolecules are available in the Protein Data Bank (Berman et al. 2000). The user can specify either a PDB identifier or browse for a local PDB file.
In each run, Pepitope produces an output file called "Pepiope Job Status Page". This file is automatically updated every 30 seconds, showing messages regarding the different stages of the server activity. When the calculation finishes, an email is sent to the user and several links appear in the Pepitope Job Status Page:
View Pepitope results with FirstGlance in Jmol
This link leads to a graphic visualization of the predicted clusters through FirstGlance in Jmol visualization tool. The target protein chain is represented as a space-filling model colored in grey. All other chains in the PDB file are displayed in backbone representation and ligands are presented in a ball-and-stick representation. The user can further control the modes of representation, using the Jmol visualization capabilities. Each predicted cluster is given a different color. The alignment between a specific peptide and the 3D structure can be viewed by clicking on the checkbox next to the peptide sequence on the left hand side of the page.
This link includes a list of up to three clusters predicted by the server. The highest scoring cluster is cluster 1. By clicking on each cluster the user can receive the list of residues that the cluster contains and the peptides that are aligned to this cluster.
Resulting alignments for each peptide
This link provides a textual display of the top scoring alignments between each peptide and the surface residues. More than one alignment for each peptide can be viewed. It is noted that in the predicted clusters, only the highest scoring alignment for each peptide is considered.
RasMol coloring script source
This link includes the commands script for coloring the PDB file according to the predicted clusters obtained by Pepitope. This file can be downloaded and used locally with RasMol (Sayle and Milner-White 1995) to produce the same color-coded CPK scheme generated by the server.
PDB file updated with Pepitope results in its header
This link provides a PDB file updated with Pepitope results in its header. This file can be uploaded to the FirstGlance in Jmol interface thus enabling users to save and view Pepitope results after they are removed from the server.
This section describes other available epitope-mapping computational tools that relay on affinity-selected peptides. For each tool a brief overview of the method is given followed by the features that distinguish Pepitope from it.
Schreiber et al. (2005)
Moreau et al. (2006)
Castrignano et al. (2007)
The performances of the different epitope-mapping programs were assessed using publicly available phage-library datasets that fulfill the following requirements: (1) a set of affinity-selected peptides were derived by scanning an antibody in a biopanning experiment, and (2) a 3D structure of the antibody-antigen complex is available. For each dataset, the prediction was compared to the "true" epitope which was inferred using the Contact Map Analysis server. For more details see Mayrose et al. (2007). As can be seen in the table below, on the datasets tested PepSurf outperforms the other algorithms yielding a statistically significant prediction in 8 out of 9 cases. The performance of the MEPS server could not be assessed since the results of different peptides are not combined into an individual predicted region.
*P-value is calculated based on the hyper-geometric distribution.
 Castrignano T, De Meo PD, Carrabino D, Orsini M, Floris M, Tramontano A. 2007. The MEPS server for identifying protein conformational epitopes. BMC Bioinformatics. 8 Suppl 1:S6. [abs]
 Chen Y, Wiesmann C, Fuh G, Li B, Christinger HW, McKay P, de Vos AM, Lowman HB. 1999. Selection and analysis of an optimized anti-VEGF antibody: crystal structure of an affinity-matured Fab in complex with antigen. J Mol Biol. 293:865-881. [abs]
 Enshell-Seijffers D, Denisov D, Groisman B, Smelyanski L, Meyuhas R, Gross G, Denisova G, Gershoni JM. 2003. The mapping and reconstitution of a conformational discontinuous B-cell epitope of HIV-1. J Mol Biol. 334:87-101. [abs]
 Lang S, Xu J, Stuart F, Thomas RM, Vrijbloed JW, Robinson JA. 2000. Analysis of antibody A6 binding to the extracellular interferon gamma receptor alpha-chain by alanine-scanning mutagenesis and random mutagenesis with phage display. Biochemistry. 39:15674-15685 [abs].
 Mayrose I, Shlomi T, Rubinstein ND, Gershoni JM, Ruppin E, Sharan R, Pupko T. 2007. A graph-based algorithm for epitope mapping using combinatorial phage-display libraries. Nucleic Acid Research. 35:69-78 [abs]
 Rickles RJ, Botfield MC, Weng Z, Taylor JA, Green OM, Brugge JS, Zoller MJ. 1994. Identification of Src, Fyn, Lyn, PI3K and Abl SH3 domain ligands using phage display libraries. Embo J. 13:5598-5604. [abs]
 Riemer AB, Kraml G, Scheiner O, Zielinski CC, Jensen-Jarolim E. 2005. Matching of trastuzumab (Herceptin) epitope mimics onto the surface of Her-2/neu--a new method of epitope definition. Mol Immunol. 42:1121-1124. [abs]
 Sayle RA, Milner-White EJ. 1995. RASMOL: biomolecular graphics for all. Trends Biochem Sci. 20:374. [abs]
 Schreiber A, Humbert M, Benz A, Dietrich U. 2005. 3D-Epitope-Explorer (3DEX): localization of conformational epitopes within three-dimensional structures of proteins. J Comput Chem. 26:879-887. [abs]
 Takenaka IM, Leung SM, McAndrew SJ, Brown JP, Hightower LE. 1995. Hsc70-binding peptides selected from a phage display peptide library that resemble organellar targeting sequences. J Biol Chem. 270:19839-19844. [abs]
 Tsodikov OV, Record MT, Sergeev YV. 2002. Novel computer program for fast exact calculation of accessible and molecular surface areas and average surface curvature. J Comput Chem. 23:600-609. [abs]
 Villard S, Lacroix-Desmazes S, Kieber-Emmons T, Piquer D, Grailly S, Benhida A, Kaveri SV, Saint-Remy JM, Granier C. 2003. Peptide decoys selected by phage display block in vitro and in vivo activity of a human anti-FVIII inhibitor. Blood, 102, 949-952.Tsodikov OV, Record MT, Sergeev YV. 2002. Novel computer program for fast exact calculation of accessible and molecular surface areas and average surface curvature. J Comput Chem. 23:600-609. [abs]