Subtractive proteomics assisted therapeutic targets mining and designing ensemble vaccine against Candida auris for immune response induction. (June 2022)

• Record Type: Journal Article
• Authors: Khan, Taimoor; Suleman, Muhammad; Ali, Syed Shujait; Sarwar, Muhammad Farhan; Ali, Imtiaz; Ali, Liaqat; Khan, Abbas; Rokhan, Bakht; Wang, Yanjing; Zhao, Ruili; Wei, Dong-Qing
• Is Part Of: Computers in biology and medicine. Volume 145(2022)
• Publication Date: 2022-06
• Subjects: Candida auris -- COVID-19 -- Subtractive proteomics -- Vaccines -- Immune simulation; Medicine -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; 610.285
• DOI: 10.1016/j.compbiomed.2022.105462
• Languages: English
• ISSNs: 0010-4825

Abstract

Abstract: The emergence of variants and the reports of co-infection caused by Candida auris in COVID-19 patients adds a further complication to the global pandemic situation. To date, no effective therapy is available for C. auris infections. Thus, characterization of therapeutic targets and designing effective vaccine candidates using subtractive proteomics and immune-informatics approaches is useful tool in controlling the emerging infections associated with SARS-CoV-2. In the current study, subtractive proteomics-assisted annotation of the vaccine targets was performed, which revealed seven vaccine targets. An immunoinformatic-driven approach was then employed to map protein-specific and proteome-wide immunogenic peptides (CTL, B cell, and HTL) for the design of multi-epitope vaccine candidates (MEVCs). The results demonstrated that the vaccine candidates possess strong antigenic features (>0.4 threshold score) and are classified as non-allergenic. Validation of the designed MEVCs through molecular docking, in-silico cloning, and immune simulation further demonstrated the efficacy of the vaccines by producing immune factor titers (ranging from 2500 to 16000 au/mL) i.e., IgM, IgG, IL-6, and Interferon-α. In conclusion, the current study provides a strong impetus in designing anti-fungal strategies against Candida auris . Key Points: The co-infection caused by Candida Auris in COVID-19 patients further aggravated the pandemic situation. In this study, annotation of the whole proteome of Candida Auris revealed putative vaccine targets. Protein-specific and proteome-wide immunogenic peptides were utilized to design multi-epitopes vaccine candidates (MEVCs). MEVCs validations through molecular docking, in silico cloning, and immune simulation demonstrated potency of the vaccines. In conclusion, the current study provides strong impetus in designing anti-fungal strategies against Candida Auris.