Virulent proteins play an essential role for the parasite survival within the host and are therefore the target of the host's immune system. Hence these represent promising vaccine/immunotherapeutic candidates. To develop vaccines it becomes essential to recognise the potent B-cell or MHC-binding peptides within the protein. An umpteen number of resources and tools have been developed for the purpose. We provide a comprehensive list for the same.
Title Description
Antigenicity plot Given a sequence of amino acids, this program computes and plots the antigenicity along the polypeptide chain, as predicted by the algorithm of Hopp & Woods (1981). 
Antigenicity prediction find antigenic sequences and also reviews them from the point of hydrophobicity, aggregation, and steric hindrance. 
IEDB-AR The Immune Epitope Database Analysis Resource is a repository of web-based tools for the prediction and analysis of immune epitopes. 
Immunoinformatics Server at UAMS This server provides mirrors of a number of T and B cell epitope prediction tools and databases from the Raghava group. 
BIMAS BIMAS ranks potential 8-mer, 9-mer, or 10-mer peptides based on a predicted half-time of dissociation to HLA class I molecules. The analysis is based on coefficient tables deduced from the published literature by Dr. Kenneth Parker, Applied Biosystems. 
EPIMHC EPIMHC is a database of peptides that bind to MHC molecules. 
PREDEP Structure based algorithm for MHC Class I epitope prediction. 
MIF Antigenicity This tool predicts antigenic sites in proteins. 
EPIPREDICT This software to predicts HLA-class II restricted T cell epitopes and ligands. By means of synthetic combinatorial peptide libraries new concepts to describe peptide-HLA class II interaction in a quantitative way were developed. The binding contribution of every amino acid side chain in a class II-ligand is described by allele-specific two-dimensional databases. 
ABCPred This tool is an artificial neural network based B-cell epitope prediction server. 
BcePred This tool predicts continuous B-cell epitopes in antigenic sequences using physico-chemical properties. 
MHCBN (MHC Binding and Non-Binding Peptides) MHCBN is a curated database consisting of detailed information about major histocompatibility complex (MHC) binding, non-binding peptides, and T-cell epitopes. Version 4.0 provides information about peptides interacting with TAP and MHC-linked autoimmune diseases. 
ProPred The aim of ProPred is to predict MHC Class-II binding regions in an antigen sequence, using quantitative matrices derived from published literature by Sturniolo et. al., 1999. The server will assist in locating promiscuous binding regions that are useful in selecting vaccine candidates. 
PEPVAC A web server for multi-epitope vaccine development based on the prediction of supertypic MHC ligands.  
JenPep JenPep is a database of quantitative binding data for immunological protein-peptide interactions, which allows speedy access to binding data through simple on-line interfaces and effective search mechanisms.  
Antijen AntiJen v2.0, is a database containing quantitative binding data for peptides binding to MHC ligands, TCR-MHC complexes, T cell epitopes, TAP, B cell epitope molecules, and immunological protein-protein interactions. AntiJen includes a peptide library, copy numbers, and diffusion coefficient data. All entries are from published experimentally determined data. The database currently holds over 24,000 entries. No data in AntiJen is from prediction experiments. 
Macaque MHC Prediction of peptide binding to Macaque MHC class-I molecules 
MAPPP MAPPP will predict possible antigenic peptides to be processed and finally presented on cell surfaces. This database aids in the prediction of immunodominant T-cell epitopes and is able to predict the proteasomal cleavage of proteins into smaller fragments, and the binding of peptide sequences to MHC class I molecules. 
SYFPEITHI SYFPEITI is based on the T-cell epitope and MHC ligand publications, Rammensee et. al., 1995 and Rammensee et. al., 1997. This database facilitates the search for peptides and allows prediction of T-cell epitopes based on published motifs (pool sequencing, natural ligands). Amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids are taken into consideration. A score is calculated according to the following rules: amino acids are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6, and preferred residues 1-4 points. Amino acids regarded as having a negative effect on the binding ability are given values between -1 and -3. 

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