In silico Design of a Multivalent Vaccine Against Candida albicans

利用计算机模拟设计抗白色念珠菌多价疫苗

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Abstract

Invasive candidiasis (IC) is the most common nosocomial infection and a leading cause of mycoses-related deaths. High-systemic toxicity and emergence of antifungal-resistant species warrant the development of newer preventive approaches against IC. Here, we have adopted an immunotherapeutic peptide vaccine-based approach, to enhance the body's immune response against invasive candida infections. Using computational tools, we screened the entire candida proteome (6030 proteins) and identified the most immunodominant HLA class I, HLA class II and B- cell epitopes. By further immunoinformatic analyses for enhanced vaccine efficacy, we selected the 18- most promising epitopes, which were joined together using molecular linkers to create a multivalent recombinant protein against Candida albicans (mvPC). To increase mvPC's immunogenicity, we added a synthetic adjuvant (RS09) to the mvPC design. The selected mvPC epitopes are homologous against all currently available annotated reference sequences of 22 C. albicans strains, thus offering a higher coverage and greater protective response. A major advantage of the current vaccine approach is mvPC's multivalent nature (recognizing multiple-epitopes), which is likely to provide enhanced protection against complex candida antigens. Here, we describe the computational analyses leading to mvPC design.

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