Secreted Aspartyl Proteinases Targeted Multi-Epitope Vaccine Design for <i>Candida dubliniensis</i> 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
Affiliations
Nahid Akhtar
Department of Research and Innovation, STEMskills Research and Education Lab Private Limited, Faridabad 121002, India
Jorge Samuel Leon Magdaleno
Physical Sciences and Engineering Division, Kaust Catalysis Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Suryakant Ranjan
School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Phagwara 144411, India
Atif Khurshid Wani
School of Bio-Engineering and Bio-Sciences, Lovely Professional University, Phagwara 144411, India
Ravneet Kaur Grewal
Department of Research and Innovation, STEMskills Research and Education Lab Private Limited, Faridabad 121002, India
Romina Oliva
Department of Sciences and Technologies, University Parthenope of Naples, Centro Direzionale Isola C4, 80143 Naples, Italy
Abdul Rajjak Shaikh
Department of Research and Innovation, STEMskills Research and Education Lab Private Limited, Faridabad 121002, India
Luigi Cavallo
Physical Sciences and Engineering Division, Kaust Catalysis Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
Mohit Chawla
Physical Sciences and Engineering Division, Kaust Catalysis Center, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia
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.
