PolyCTLDesigner: a computational tool for constructing polyepitope T-cell antigens

BMC Research Notes

Sergei I Bazhan¹  Denis V Antonets¹ 

[1] State Research Center of Virology and Biotechnology “Vector”, Koltsovo, Novosibirsk Region, Russian Federation

关键词: Travelling salesman problem;    Directed weighted graph;    Proteasome;    Transporters associated with antigen processing;    Cytotoxic T cell;    Polyepitope;    T-cell epitope;   

Others  :  1141430
DOI  :  10.1186/1756-0500-6-407

 received in 2013-02-14, accepted in 2013-09-24,  发布年份 2013

【 摘 要 】

Background

Construction of artificial polyepitope antigens is one of the most promising strategies for developing more efficient and safer vaccines evoking T-cell immune responses. Epitope rearrangements and utilization of certain spacer sequences have been proven to greatly influence the immunogenicity of polyepitope constructs. However, despite numerous efforts towards constructing and evaluating artificial polyepitope immunogens as well as despite numerous computational methods elaborated to date for predicting T-cell epitopes, peptides binding to TAP and for antigen processing prediction, only a few computational tools were currently developed for rational design of polyepitope antigens.

Findings

Here we present a PolyCTLDesigner program that is intended for constructing polyepitope immunogens. Given a set of either known or predicted T-cell epitopes the program selects N-terminal flanking sequences for each epitope to optimize its binding to TAP (if necessary) and joins resulting oligopeptides into a polyepitope in a way providing efficient liberation of potential epitopes by proteasomal and/or immunoproteasomal processing. And it also tries to minimize the number of non-target junctional epitopes resulting from artificial juxtaposition of target epitopes within the polyepitope. For constructing polyepitopes, PolyCTLDesigner utilizes known amino acid patterns of TAP-binding and proteasomal/immunoproteasomal cleavage specificity together with genetic algorithm and graph theory approaches. The program was implemented using Python programming language and it can be used either interactively or through scripting, which allows users familiar with Python to create custom pipelines.

Conclusions

The developed software realizes a rational approach to designing poly-CTL-epitope antigens and can be used to develop new candidate polyepitope vaccines. The current version of PolyCTLDesigner is integrated with our TEpredict program for predicting T-cell epitopes, and thus it can be used not only for constructing the polyepitope antigens based on preselected sets of T-cell epitopes, but also for predicting cytotoxic and helper T-cell epitopes within selected protein antigens. PolyCTLDesigner is freely available from the project’s web site: http://tepredict.sourceforge.net/PolyCTLDesigner.html webcite.

【 授权许可】

   
2013 Antonets and Bazhan; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

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