Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach. (February 2018) - Vakili, Bahareh; Nezafat, Navid; Hatam, Gholam Reza; Zare, Bijan; Erfani, Nasrollah; Ghasemi, Younes
Highlights: To predict novel antigenic peptides for vaccine design against visceral leishmaniasis, we utilized a pipeline of algorithms. The whole proteome of Leishmania infantum was analyzed using bioinformatics tools. Ten antigenic proteins were predicted as novel targets for vaccine design against visceral leishmaniasis. Abstract: Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.