TY - JOUR
T1 - Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for Candida dubliniensis Using Immunoinformatics
AU - Akhtar, Nahid
AU - Magdaleno, Jorge Samuel Leon
AU - Ranjan, Suryakant
AU - Wani, Atif Khurshid
AU - Grewal, Ravneet Kaur
AU - Oliva, Romina
AU - Shaikh, Abdul Rajjak
AU - Cavallo, Luigi
AU - Chawla, Mohit
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has been designed using an immunoinformatics approach by targeting C. dubliniensis secreted aspartyl proteinases (SAP) proteins. In silico tools have been utilized to predict epitopes and determine their allergic potential, antigenic potential, toxicity, and potential to elicit interleukin-2 (IL2), interleukin-4 (IL4), and IFN-γ. Using the computational tools, eight epitopes have been predicted that were then linked with adjuvants for final vaccine candidate development. Computational immune simulation has depicted that the immunogen designed emerges as a strong immunogenic candidate for a vaccine. Further, molecular docking and molecular dynamics simulation analyses revealed stable interactions between the vaccine candidate and the human toll-like receptor 5 (TLR5). Finally, immune simulations corroborated the promising candidature of the designed vaccine, thus calling for further in vivo investigation.
AB - Candida dubliniensis is an opportunistic pathogen associated with oral and invasive fungal infections in immune-compromised individuals. Furthermore, the emergence of C. dubliniensis antifungal drug resistance could exacerbate its treatment. Hence, in this study a multi-epitope vaccine candidate has been designed using an immunoinformatics approach by targeting C. dubliniensis secreted aspartyl proteinases (SAP) proteins. In silico tools have been utilized to predict epitopes and determine their allergic potential, antigenic potential, toxicity, and potential to elicit interleukin-2 (IL2), interleukin-4 (IL4), and IFN-γ. Using the computational tools, eight epitopes have been predicted that were then linked with adjuvants for final vaccine candidate development. Computational immune simulation has depicted that the immunogen designed emerges as a strong immunogenic candidate for a vaccine. Further, molecular docking and molecular dynamics simulation analyses revealed stable interactions between the vaccine candidate and the human toll-like receptor 5 (TLR5). Finally, immune simulations corroborated the promising candidature of the designed vaccine, thus calling for further in vivo investigation.
KW - Candida dubliniensis
KW - candidiasis
KW - immunoinformatics
KW - molecular docking
KW - molecular dynamic simulations
KW - multi-epitope vaccine
UR - http://www.scopus.com/inward/record.url?scp=85149249728&partnerID=8YFLogxK
U2 - 10.3390/vaccines11020364
DO - 10.3390/vaccines11020364
M3 - Article
C2 - 36851241
AN - SCOPUS:85149249728
SN - 2076-393X
VL - 11
JO - Vaccines
JF - Vaccines
IS - 2
M1 - 364
ER -