Invertis Journal of Renewable Energy
  • Year: 2021
  • Volume: 11
  • Issue: 1

Machine Learning and Computational Vaccine-A Novel approach to Vaccine Design against Hepatitis C Virus

  • Author:
  • Amit Joshi1, Pankaj K. Rai1,*, Shashank Upadhyay1
  • Total Page Count: 9
  • Published Online: Jun 4, 2021
  • Page Number: 1 to 9

1Department of Biotechnology, Invertis University, Bareilly-243123, Uttar Pradesh, India

*Corresponding author email id: pankaj.r@invertis.org, pankajraibhu@gmail.com

Abstract

Vaccines are molecular entities that are used to invigorate defensive immune system contrary to microbial systems and ailments they produce. Defensive immunity is definitive against pathogens which augment adaptive immune reaction to ensuing re-contagion or, epidemic by accompanying organisms. Such reinforced immunity is interceding by the immune remembrance that imitates counters to the impacts of infectious microorganisms. Designing drug against Hep C virus is not adequate in patients because of delay in gathering information related to disease that finally becomes calamitous due to development of immedicable hepatic cirrhosis. This dilemma can be resolved by crafting peptidal or epitope vaccines, as they have enhanced activity and specificity. The determination of epitopes in non-structural flavivirus 3 protein or P70 provides a suitable primary immune symptomatic antigen for the detection of the HEP C VIRUS. Non-Structural protein epitopes would be predicted in this research work, which could be used as suitable vaccine candidate against Hepatitis C virus infections.

Keywords

Hepatitis C virus, Machine Learning, Epitope, Immunity and Microorganisms