Novel Algorithms for In Silico Peptide Vaccine Design with Reference to Ebola Virus

摘要

Viral epidemics have posed a problem for quick development of drugs and vaccines to control the menace. A case in point is the Ebola viral disease with high fatality ratio in Africa. It is making a comeback in the Democratic Republic of Congo (DRC), after its rampage in West Africa in 2014-16 that has spawned fears of leading to a pandemic. Vaccines such as the experimental rVSV-ZEBOV has provided protection in 70-80% of the cases, but such vaccines are in short supply and doubts exist of its availability and sustainability in pandemic cases. Peptide vaccines promise to amend this lacuna as a chemical construct that can be scaled up to requirement in manufacturing set-up, are easy to produce in pure form and store as well as transport much more easily and economically than traditional vaccines. Although no peptide vaccines have been licensed yet for human use, the rapid growth of applications of in silico approaches to peptide vaccine design and application to a myriad of virus infections, and subsequent follow-up experimental work, have led to expectations of licensures in the near future. We have proposed a protocol to automate the search procedure using mathematical and computational modelling approaches to generate peptide libraries that promote long life of such vaccines even in the face of rapid mutational changes in the viral sequences. In this paper, we outline the mathematical model we have used and the recent improvements in the techniques to ensure the best recommendations for peptide vaccine libraries, especially against the Ebola virus that threatens to spill over the Congo border and cause epidemics and pandemics in a globalized world.