Annotation of Potential Vaccine Targets and Designing of mRNA-Based Multi-Epitope Vaccine against Lumpy Skin Disease Virus via Reverse Vaccinology and Agent-Based Modeling.

Lumpy skin disease is a fatal emerging disease of cattle, which has started to gain extensive attention due to its rapid incursions across the globe. The disease epidemic causes economic loss and cattle morbidity. Currently, there are no specific treatments and safe vaccines against the lumpy skin disease virus (LSDV) to halt the spread of the disease. The current study uses genome-scan vaccinomics analyses to prioritize promiscuous vaccine candidate proteins of the LSDV. These proteins were subjected to top-ranked B- and T-cell epitope prediction based on their antigenicity, allergenicity, and toxicity values. The shortlisted epitopes were connected using appropriate linkers and adjuvant sequences to design multi-epitope vaccine constructs. Three vaccine constructs were prioritized based on their immunological and physicochemical properties. The model constructs were back-translated to nucleotide sequences and codons were optimized. The Kozak sequence with a start codon along with MITD, tPA, Goblin 5', 3' UTRs, and a poly(A) tail sequences were added to design a stable and highly immunogenic mRNA vaccine. Molecular docking followed by MD simulation analysis predicted significant binding affinity and stability of LSDV-V2 construct within bovine immune receptors and predicted it to be the top-ranked candidate to stimulate the humeral and cellular immunogenic responses. Furthermore, in silico restriction cloning predicted feasible gene expression of the LSDV-V2 construct in a bacterial expression vector. It could prove worthwhile to validate the predicted vaccine models experimentally and clinically against LSDV.

Molecular Mimicry Analyses Unveiled the Human Herpes Simplex and Poxvirus Epitopes as Possible Candidates to Incite Autoimmunity.

Clinical epidemiological studies have reported that viral infections cause autoimmune pathology in humans. Host-pathogen protein sequences and structure-based molecular mimicry cause autoreactive T cells to cross-activate. The aim of the current study was to implement immunoinformatics approaches to infer sequence- and structure-based molecular mimicry between viral and human proteomic datasets. The protein sequences of all the so far known human-infecting viruses were obtained from the VIPR database, and complete human proteome data were retrieved from the NCBI repository. Based on a predefined, stringent threshold of comparative sequence analyses, 24 viral proteins were identified with significant sequence similarity to human proteins. PathDIP identified the enrichment of these homologous proteins in nine metabolic pathways with a p-value < 0.0001. Several viral and human mimic epitopes from these homologous proteins were predicted as strong binders of human HLA alleles, with IC50 < 50 nM. Downstream molecular docking analyses identified that lead virus-human homologous epitopes feasibly interact with HLA and TLR4 types of immune receptors. The vast majority of these top-hit homolog epitopic peptides belong to the herpes simplex and poxvirus families. These lead epitope biological sequences and 3D structural-based molecular mimicry may be promising for interpreting herpes simplex virus and poxvirus infection-mediated autoimmune disorders in humans.

An insight in Salmonella typhi associated autoimmunity candidates' prediction by molecular mimicry.

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.