Abstract
Autoimmune diseases develop when the immune system targets healthy cells and tissues of an individual. In developing countries, S. typhi (a gram-negative pathogenic bacteria) remains a major public health issue. This study aimed to employ bioinformatics analyses to determine the 3D structural-based molecular mimicry and sequence of S. typhi and human host proteins. In addition, to classify possible antigenic microbial peptides homologous to human peptides and comprehend the molecular basis of S. typhi-related autoimmune disorders. Protein sequences were obtained from the NCBI database, and redundancy was removed using the CD-HIT tool. The BLASTp comparative sequence analysis was followed for molecular mimicry identification of human and S. typhi protein sequences. The PathDIP database was utilized to simulate essential physical relationships between proteins and curated pathways for metabolic processes. Subsequently, the IEDB database was used to find cross-reactive MHC class-II binding epitopes that could trigger an autoimmune reaction. SPARKS-X computational biology resource was also used to determine the structural homology between human and S. typhi peptides. The BLASTp study showed that S. typhi and the human host have several proteins holding considerable sequence similarities based on a set threshold of e ≤ 10-6 and bit score ≥100. The PathDIP putatively identified that these proteins enriched in a total of 68 metabolic pathways by a significant P-value (P < 0.005). The PSORTb analysis predicted that 26 out of these proteins are cytosolic, 1 predicted to be periplasmic protein, and 1 predicted to be localized in the cytoplasmic membrane. IEDB data analysis predicted many S.typhi and human homologs epitopes as a good binder of human HLA, i.e. DRB1*01:01, DPA1*03:01/DPB1*04:02, and DQA1*01:02/DQB1*06:02 with IC50 < 50 nM. Finally, the docking data demonstrated that homolog lead epitopes promisingly interact with HLA and immune TLR4 receptors by exhibiting the best docking scores and molecular interactions. The analyses ultimately identified several potential candidate proteins and peptides that could cause S.typhi infection-mediated autoimmune diseases in humans.
•Prediction of Salmonella typhi Associated Autoimmunity peptides.•Protein sequence and 3D structural-based molecular mimicry of host and S. typhi.•Classification of possible antigenic microbial peptides homologous to human peptides.•Understanding the molecular basis of S. typhi-related autoimmune disorders.•Identification of cross-reactive epitopes that could trigger an autoimmune reaction.