vlcvirus

vlcvirus identifies and prioritizes epitope-based subunit vaccine candidates against lung cancer-associated oncogenic viruses using reverse vaccinology to support selection of epitopes that stimulate humoral and cell-mediated immunity while avoiding self-tolerance.


Key Features:

  • Reverse vaccinology approach: Systematic analysis of protein components from nine oncogenic virus species implicated in lung cancer.
  • Epitope identification: Identification of 125 antigenic epitopes with predicted B-cell, T-cell, and/or MHC-binding capabilities and vaccine adjuvant potential.
  • Cytokine induction profiling: Highlighting 32 epitopes with predicted IL-4 and IFN-gamma inducing potential and lack of IL-10 induction.
  • MHC binding breadth: Reported binding of selected epitopes to human MHC-type I (15 alleles) and MHC-type II (49 alleles).
  • Safety assessments: All 32 prioritized epitopes are non-allergenic and 31 are predicted non-toxic.
  • Conservancy and promiscuity: Identified epitopes show conservancy and promiscuous binding across a wide class of human HLA alleles and multiple viral strains/species.
  • Viral source emphasis: Many top antigenic epitopes derive from Human papillomavirus (HPV) and Epstein-Barr virus (EBV), notably from E1 and E6 genes.
  • Experimental validation cross-reference: Cross-referencing with the Immune Epitope Database and Analysis Resource (IEDB) indicates 38 epitopes with experimental validation.
  • Refined candidate set: A final shortlist of 29 epitopes is provided for highest immunogenic and immune-boosting potential and further experimental validation.

Scientific Applications:

  • Subunit vaccine design: Provides prioritized epitope sets for designing epitope-based subunit vaccines targeting lung cancer-associated viruses.
  • Experimental candidate selection: Enables selection of epitopes with predicted cytokine profiles, MHC-binding breadth, and safety profiles for downstream experimental validation.
  • Comparative viral antigen analysis: Facilitates comparison of antigenic epitopes across nine oncogenic virus species, including HPV and EBV.
  • Immunogenicity targeting: Supports selection of epitopes aimed at eliciting both humoral and cell-mediated immune responses while minimizing IL-10–associated tolerance.

Methodology:

Employed a reverse vaccinology framework with systematic protein analysis of nine oncogenic virus species, computational prediction of B-cell, T-cell, and MHC-binding epitopes, cytokine induction predictions (IL-4, IFN-gamma, IL-10), allergenicity and toxicity predictions, conservancy and promiscuous HLA-binding assessment, and cross-referencing with the Immune Epitope Database and Analysis Resource for experimental validation.

Topics

Details

Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
10/11/2022
Last Updated:
10/11/2022

Operations

Publications

Lathwal A, Kumar R, Raghava GP. In-silico identification of subunit vaccine candidates against lung cancer-associated oncogenic viruses. Computers in Biology and Medicine. 2021;130:104215. doi:10.1016/j.compbiomed.2021.104215. PMID:33465550.

Documentation

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