A Computational Search for Peptide Vaccines Using Novel Mathematical Descriptors of Sequences of Emerging Pathogens

Human civilization has always been combating different pathogens that have caused epidemics or pandemics at various points of time, which has ultimately taken away millions of lives worldwide. Among all the disease-causing pathogens, viruses are notably pathogenic. Their relatively smaller size and comparatively higher rate of mutation make them more problematic than others. Vaccines turn out to be the best tool against viruses, but designing efficient vaccines against them is a difficult and time-consuming task; moreover, the efficiency of a classical vaccine can deteriorate as the virus mutates to newer strains. In this situation, peptide vaccines may appear as the need of the hour since they can be designed and developed relatively easily and quickly with the help of novel computational tools and chemical technology. Peptide vaccines have the potential to be rapidly manufactured and deployed to confront sudden disease outbreaks. These alternative vaccines are now also being tested against tumors and hence it can be expected that in the near future they can provide a cure for or protection against cancer too. Designing peptide vaccines comprises a careful analysis of the protein sequences, identification of epitopes, screening out of autoimmune threats, and so on. To make researchers aware of these aspects, in this chapter we briefly discuss various novel techniques that are being developed to assist in this task.