Abstract
Designing a vaccine for a disease is one of the crucial tasks that involve millions and billions of dollars, several decades and yet there is no guarantee of successful results. Several pharmaceutical companies are investing their money and time in such activities. Computational biology could be of great help in these activities by proving a library of plausible candidates that might actually show some positive responses. MHC binding peptide prediction is one such area where the immense power of computers could be used to get a breakthrough. In this direction several databases and servers have been developed by many labs to predict the MHC binding peptides. These short peptides on the antigen surface are recognized by the MHC molecule and are presented to the receptors of T-cells for further immune response. Peptides that bind to a given MHC molecule share sequence similarity. Here we present a comparative study of servers that can predict the MHC binding peptides in a given protein sequence of the antigen. Based on this comparative analysis on HIV data, we are able to propose a library of putative vaccine candidates for the env GP-160 protein of HIV-1.
Highlights
With the progression and success rates of several genome projects, we are provided with exponentially increasing number of proteins
The protein sequences were fetched from the National Center for Biotechnology Information (NCBI) through their enterz search engine
We were able to analyze the selected sequence through various approaches viz, Artificial Neural Networks (ANNs), SVM, Position Specific Scoring Matrices (PSSMs), etc and against various database as well. This three tier scanning increases the chances of accuracy and reduces the false-positive hits if any
Summary
With the progression and success rates of several genome projects, we are provided with exponentially increasing number of proteins. This protein sequence data include vital hidden information of pathogenic response of an organism. The first step in the development of peptide vaccines is the identification of the immunodominant peptides along with proteins sequence. One could perform several computational analyses to screen and develop libraries of such peptides. Such libraries could help the research and development process of several pharmaceutical companies saving them money and time and will insure less hazardous situation to handle the pathogens
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