Vaccines 2023
Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics
Nahid Akhtar, Jorge Samuel Leon Magdaleno, Suryakant Ranjan, Atif Khurshid Wani, Ravneet Kaur Grewal, Romina Oliva, Abdul Rajjak Shaikh, Luigi Cavallo, Mohit Chawla
This study designs a multi-epitope vaccine against Candida dubliniensis, a fungus that causes oral and invasive infections in immunocompromised patients and is developing drug resistance. Using immunoinformatics, the team targeted the fungus’s secreted aspartyl proteinase proteins, predicting eight safe, immune-activating epitopes and linking them with adjuvants. Docking, molecular dynamics and immune-simulation results pointed to stable TLR5 binding and a strong predicted immune response, supporting future laboratory testing.
Methods you can learn
Cite this paper
Nahid Akhtar, Jorge Samuel Leon Magdaleno, Suryakant Ranjan, Atif Khurshid Wani, Ravneet Kaur Grewal, Romina Oliva, Abdul Rajjak Shaikh, Luigi Cavallo, Mohit Chawla (2023) Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics. Vaccines. https://doi.org/10.3390/vaccines11020364
No volume or page numbers are shown because the record does not carry them; the DOI resolves the full reference.
Related papers
- Immunoinformatics-Aided Design of a Peptide Based Multiepitope Vaccine Targeting Glycoproteins and Membrane Proteins against Monkeypox Virus
- Immunoinformatics Aided Design and In-Vivo Validation of a Cross-Reactive Peptide Based Multi-Epitope Vaccine Targeting Multiple Serotypes of Dengue Virus
- Immunoinformatics-Aided Design and In Vivo Validation of a Peptide-Based Multiepitope Vaccine Targeting Canine Circovirus
