B-Cell Epitope Mapping from Eight Antigens of Candida albicans to Design a Novel Diagnostic Kit: An Immunoinformatics Approach

Abstract

Invasive candidiasis is an emerging fungal infection and a leading cause of morbidity in health care facilities. Despite advances in antifungal therapy, increased antifungal drug resistance in Candida albicans has enhanced patient fatality. The most common method for Candida albicans diagnosing is blood culture, which has low sensitivity. Therefore, there is an urgent need to establish a valid diagnostic method. Our study aimed to use the bioinformatics approach to design a diagnostic kit for detecting Candida albicans with high sensitivity and specificity. Eight antigenic proteins of Candida albicans (HYR1, HWP1, ECE1, ALS, EAP1, SAP1, BGL2, and MET6) were selected. Next, a construct containing different immunodominant B-cell epitopes was derived from the antigens and connected using a suitable linker. Different properties of the final construct, such as physicochemical properties, were evaluated. Moreover, the designed construct underwent 3D modeling, reverse translation, and codon optimization. The results confirmed that the designed construct could identify Candida albicans with high sensitivity and specificity in serum samples of patients with invasive candidiasis. However, experimental studies are needed for final confirmation.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10989-022-10413-1.