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Trends in Bioinformatics
  Year: 2012 | Volume: 5 | Issue: 1 | Page No.: 14-24
DOI: 10.3923/tb.2012.14.24
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In-silico: Screening and Modeling of CTL Binding Epitopes of Crimean Congo Hemorrhagic Fever Virus
Chandra Shekhar, Kapil Dev, Sitansu Kumar Verma and Ajay Kumar

Crimean-Congo Hemorrhagic Fever (CCHF) is a zoonotic viral disease that is asymptomatic in infected livestock but a serious threat to humans. This study is aimed at conducting the modeling of putative peptides which are suggested for vaccine development that is meant for evaluating epidemiological, clinical and laboratory characteristics of the patients diagnosed with Crimean-Congo hemorrhagic fever. In the present study, more reliable prediction of Major Histocompatibility Complex (MHC) peptide binding is based on the accurate determination of T-cell epitopes and hence the successful design of peptide and protein based vaccines. The importance of existing computational tools was used for prediction of peptide binding to Major Histocompatibility Complex (MHC) Class-I and Major Histocompatibility Complex (MHC) Class-II. With the availability of large sequence databases and computer aided design of peptide based vaccine, screening among billions of possible immune active peptides to find those likely to provoke an immune response was done. These peptides were selected by using different algorithms as Artificial Neuronal Network (ANN) and Support Vector Machine (SVM) for the T-cell epitope prediction and further characterized on the basis of binding affinity of peptide to HLA-alleles which can be finally used for the potential vaccine candidate development. A vaccine with specificity for a target population i.e., peptide based vaccine, in which small peptides derived from target proteins are used to provoke an immune reaction. Two nonameric epitopes (LRFGMLAGL) and (LLGIKCSFV) which exhibit good binding with MHC molecules and low energy minimization values providing stability to the peptide-MHC complex are reported here. These predicted peptides don’t have similarity with human proteome. These peptide could be used in designing a chimeric/subunit vaccine, however, these will further be tested by wet lab studies for a targeted vaccine design against Crimean-Congo hemorrhagic fever.
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  •    Screening and Structure-based Modeling of T-Cell Epitopes of Marburg Virus NP, GP and VP40: An Immunoinformatic Approach for Designing Peptide-based Vaccine
  •    In silico Molecular Docking of Influenza Virus (PB2) Protein to Check the Drug Efficacy
  •    Use of RB51 Vaccine for Small Ruminants Brucellosis Prevention, in Veracruz, Mexico
  •    Computational Comparison of T-cell Epitopes of gp120 of Iranian HIV-1 with Different Subtypes of the Virus
  •    Database of in silico Predicted Potential Drug Target Proteins in Common Bacterial Human Pathogens
How to cite this article:

Chandra Shekhar, Kapil Dev, Sitansu Kumar Verma and Ajay Kumar, 2012. In-silico: Screening and Modeling of CTL Binding Epitopes of Crimean Congo Hemorrhagic Fever Virus. Trends in Bioinformatics, 5: 14-24.

DOI: 10.3923/tb.2012.14.24








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