Genome annotation server structure prediction server Functional annotation server vaccine design server databases Miscellaneous


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Genome annotation

Structure prediction

Functional annotation

vaccine design

Databases

Miscellaneous

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Servers for Identification of Subunit Vaccine Candidates

PROPRED1

nHLApred

MMBpred

Pcleavage

TAPpred

CTLpred

PROPRED

HLADR4pred

MHC2pred

MHC

MHCbench

AbAg

BCEpred

ABCpred

BCIPep

HLApred

 MHCBN

HaptenDB

HLA_affi

AFDR4

 

Server

Description

ProPred1:

The aim of this server is to predict MHC Class-I binding regions in an antigen sequence (Singh, H. and Raghava, G.P.S. (2003) Bioinformatics, 19: 1009)

ProPred:

The aim of this server is to predict MHC Class-II binding regions in an antigen sequence (Singh, H. and Raghava, G. P. S. (2001) Bioinformatics 17: 1236)

BcePred:

The BcePred server predict B cell epitope based on physio-chemical properties of amino acids. (Saha,S and Raghava GP (2004) ICARIS, LNCS 3239,197-204)

nHLAPred:

This server allow to predict binding peptide for 67 MHC Class I alleles. This also allow to predict the proteasome cleavage site and binding peptide that have cleavage site at C terminus (potential T cell epitopes). This uses the hybrid approach for prediction (Neural Network + Quantitative Matrix)

HLADR4Pred:

SVM and ANN based methods for predicting HLA-DRB1*0401 binding peptides in an Antigen Sequence (Bhasin, M. and Raghava, G.P.S. (2003) Bioinformatics 20:421).

ABCpred:

ABCpred server is to predict linear B cell epitope regions in an antigen sequence, using artificial neural network. This server will assist in locating epitope regions that are useful in selecting synthetic vaccine candidates, disease diagonosis and also in allergy research. ( Saha, S. and Raghava, G. P. S. (2006) PROTEINS:Structure, Function, and Bioinformatics (In Press) )

MMBPred

Prediction of of MHC class I binders which can bind to wide range of MHC alleles with high affinity. This server has potential to develop sub-unit vaccine for large population (Bhasin, M., and Raghava, G.P.S. (2003) Hybridoma and Hybridomics 22: 229)

MHC2Pred:

Prediction of binders for MHC class II alleles. This allows to predict  promiscuous class binders, which can bind to large number of MHC Class II alleles.

Bcipep:

Bcipep is a collection of the peptides having the role in Humoral immunity. The peptides in the database has varying measure of immunogenicity.This database can assist in the development of method for predicting B cell epitopes, desigining synthetic vaccines and in disease diagnosis. This databse is also launched by European Bioinformatics Institute (EBI) Hinxton, Cambridge, UK. (Saha S, Bhasin M, Raghava GP. (2005) BMC Genomics. 6(1):79)

Pcleavage:

This server allows server to predict  proten (Immuno and standard) (Bhasin M, Raghava GP. (2005) Nucleic Acids Res.33(Web Server issue):W202-7)

MHC

Matrix Optimization Technique for Predicting MHC binding Core (Singh, H. and Raghava, G. P. S. (2002) Biotech Software and Internet Report, 3:146)

 

HLAPRED:

A server for predicting binders for MHC class I and II alleles. It also search these predicted binders in various genomes.

TAPPred:

TAPPred is an on-line service for predicting binding affinity of peptides toward the TAP transporter. The Prediction is based on cascade SVM, using sequence and properties of the the amino acids (Bhasin, M. and Raghava, G. P. S. (2004) Protein Science 13:596-607).

MHCBench :

It is an interface developed for evaluating the Major Histocompatibility Complex (MHC) binding peptide prediction algorithms.

MHCBN:

The MHCBN is a curated database consisting of detailed information about Major Histocompatibility Complex (MHC) Binding,Non-binding peptides and T-cell epitopes.The version 3.1 of database provides information about peptides interacting with TAP and MHC linked autoimmune diseases This databse is also launched by European Bioinformatics Institute (EBI) Hinxton, Cambridge, UK. (Bhasin, M., Singh, H. and Raghava, G. P. S. (2003) Bioinformatics 19: 665).

CTLPred:

Direct method of prediction of CTL Epitopes in an antigen sequence. This server utlize the machine learning techniques Support Vector Machine(SVM) and Aritificial Neural Network (ANN) for prediction (Bhasin, M. and Raghava, G. P. S. (2004) Vaccine 22:3195-204 )

Ab/Ag concentartion

This web-server allow to compute the endpoint titer and concentration of Antibody(Ab) or Antigen(Ag) from ELISA data(Raghava, G. P. S. and Agrewala, J. N. (2001) Biotech Software and Internet Report, 2:196). This server is based on graphical method developed for calculating Ab/Ag concentration (Raghava, G.P.S., Joshi, A.K. and Agrewala, J.N. (1992) J. Immunol. Methods 153, 263-264).

HaptenDB:

A database of hapten  molecules which can not activate immune system but can stimulate immune response if attach with the carrier  proteins. (Singh, M.K., Srivastava, S.,Raghava, G. P. S. and Varshney, G.C. (2006) Bioinformatics 22:253-5.)

HLA_affi:

This is a SVM based server developed for predicting the binding affinity of peptides binding to HLA-A2 allele

FDR4:

This server predicts the binding core and binding affinity of peptides binding to HLA-DRB1*0401 allele

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