Abstract
Background: For design of a subunit vaccine for tuberculosis, identification of antigenic Tcell epitope is of utmost importance. Several MHC prediction server are available that can accurately predict antigenic peptide of variable lengths. However, peptides predicted from one server not necessarily are predicted form another server, thus creating a confusing situation for scientists to choose a best epitope.
Method: Keeping the above problem in mind, we developed a comprehensive database of peptides of Mycobacterial proteins. Each protein was taken from PubMed and was run through different MHC prediction servers, with the results being compiled into one database.
Results: For each protein, PeMtb generates a set of three different mers of variable lengths (12 mer or 13-mer) based on their ranking; with each mer being predicted for a plethora of MHC alleles. Researcher can choose the peptide (mers) that gives best binding affinity from most of the servers.
Conclusion: The database relieves the investigators of the painstaking task of searching various MHC prediction servers for the right epitope (T-cell epitope) for a particular Mycobacterial antigen. We trust and anticipate that PeMtb will be a practical platform for trial and computational analyses of antigenic peptides for Mycobacterium tuberculosis. All the resources and information can be accessed by PeMtb home page www.pemtb-amu.org.
Keywords: MHC alleles, PeMtb, T cell epitope, database, MHC prediction server, Mycobacterium tuberculosis.
Current Pharmaceutical Biotechnology
Title:PeMtb: A Database of MHC Antigenic Peptide of Mycobacterium tuberculosis
Volume: 18 Issue: 8
Author(s): Qamar Zia, Asim Azhar, Shadab Ahmad, Mohammad Afsar, Ziaul Hasan, Mohammad Owais, Mahfooz Alam, Shabab Akbar, Magdah Ganash, Ghulam Md Ashraf , Swaleha Zubair*Gjumrakch Aliev*
Affiliation:
- Women's College, Aligarh Muslim University, Aligarh,India
- “GALLY” International Biomedical Research Consulting LLC San Antonio, TX,United States
Keywords: MHC alleles, PeMtb, T cell epitope, database, MHC prediction server, Mycobacterium tuberculosis.
Abstract: Background: For design of a subunit vaccine for tuberculosis, identification of antigenic Tcell epitope is of utmost importance. Several MHC prediction server are available that can accurately predict antigenic peptide of variable lengths. However, peptides predicted from one server not necessarily are predicted form another server, thus creating a confusing situation for scientists to choose a best epitope.
Method: Keeping the above problem in mind, we developed a comprehensive database of peptides of Mycobacterial proteins. Each protein was taken from PubMed and was run through different MHC prediction servers, with the results being compiled into one database.
Results: For each protein, PeMtb generates a set of three different mers of variable lengths (12 mer or 13-mer) based on their ranking; with each mer being predicted for a plethora of MHC alleles. Researcher can choose the peptide (mers) that gives best binding affinity from most of the servers.
Conclusion: The database relieves the investigators of the painstaking task of searching various MHC prediction servers for the right epitope (T-cell epitope) for a particular Mycobacterial antigen. We trust and anticipate that PeMtb will be a practical platform for trial and computational analyses of antigenic peptides for Mycobacterium tuberculosis. All the resources and information can be accessed by PeMtb home page www.pemtb-amu.org.
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Zia Qamar, Azhar Asim , Ahmad Shadab , Afsar Mohammad , Hasan Ziaul , Owais Mohammad , Alam Mahfooz , Akbar Shabab , Ganash Magdah , Ashraf Md Ghulam , Zubair Swaleha *, Aliev Gjumrakch*, PeMtb: A Database of MHC Antigenic Peptide of Mycobacterium tuberculosis, Current Pharmaceutical Biotechnology 2017; 18 (8) . https://dx.doi.org/10.2174/1389201018666170914150115
DOI https://dx.doi.org/10.2174/1389201018666170914150115 |
Print ISSN 1389-2010 |
Publisher Name Bentham Science Publisher |
Online ISSN 1873-4316 |
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