Mycobacterium tuberculosis is considered one of the most successful pathogens in the history of mankind, having caused 1.7 million deaths in 2016. The amount of resistant and extensively resistant strains has increased; BCG has been the only vaccine to be produced in more than 100 years though it is still unable to prevent the disease's most disseminated form in adults; pulmonary tuberculosis. The search is thus still on-going for candidate antigens for an antituberculosis vaccine. This paper reports the use of a logical and rational methodology for finding such antigens, this time as peptides derived from the Rv3587c membrane protein. Bioinformatics tools were used for predicting mycobacterial surface location and Rv3587c protein structure whilst circular dichroism was used for determining its peptides' secondary structure. Receptor-ligand assays identified 4 high activity binding peptides (HABPs) binding specifically to A549 alveolar epithelial cells and U937 monocyte-derived macrophages, covering the region between amino acids 116 and 193. Their capability for inhibiting Mtb H37Rv invasion was evaluated. The recognition of antibodies from individuals suffering active and latent tuberculosis and from healthy individuals was observed in HABPs capable of avoiding mycobacterial entry to host cells. The results showed that 8 HABPs inhibited such invasion, two of them being common for both cell lines: 39265 (155VLAAYVYSLDNKRLWSNLDT173) and 39266 (174APSNETLVKTFSPGEQVTTY192). Peptide 39265 was the least recognised by antibodies from the individuals' sera evaluated in each group. According to the model proposed by FIDIC regarding synthetic vaccine development, peptide 39265 has become a candidate antigen for an antituberculosis vaccine.
Keywords: Bioinformatics; HABPs; Invasion assay; Mycobacterium tuberculosis; Rv3587c; Vaccine.
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