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In Silico Designing of Vaccines: Methods, Tools, and Their Limitations

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Computer-Aided Drug Design

Abstract

In the post genomic era, the finding of new therapeutic targets has hugely been accelerated by the use of bioinformatics tools. The availability of genome sequences of pathogenic microbes has led to an increased finding of genes and proteins that could be potential targets for drug or vaccine design. The tools made available by bioinformatics have played a central role in the analysis of the genome and protein sequences for finding immunogenic proteins among the repertoire possessed by the organisms. The methods for prediction of immunogenicity are automated, and the whole proteome can be analyzed to find the top candidates that could have immunity inducing properties. Not only finding of immunogenic proteins has been achieved, but the mapping of the individual epitopes is also being done. The availability of methods for finding T and B cell epitopes can lead to the design of epitope-based vaccines. The description of different bioinformatics tools that are available for determining the immunogenic properties, finding of T and B cell epitopes, and in silico tools that are used in vaccine design is given in here. An account of epitope-based vaccine design employing bioinformatics methods reported in the literature is discussed. There are many shortcomings associated with these methods, which are discussed in the chapter. As is the case with other bioinformatics methods, there exist issues of prediction accuracy. Achievement of higher accuracy in predictions and their translation into in vivo/in vitro conditions still requires improvement. The chapter intends to provide the list of freely accessible software for epitope prediction and vaccine design with their merits/demerits and also throwing light on their applicability in vaccine research.

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Slathia, P.S., Sharma, P. (2020). In Silico Designing of Vaccines: Methods, Tools, and Their Limitations. In: Singh, D.B. (eds) Computer-Aided Drug Design. Springer, Singapore. https://doi.org/10.1007/978-981-15-6815-2_11

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