RESUMEN
The Legionellaceae group comprises the Legionella, containing 58 species with 70 serotypes. For instance, Legionella pneumophila is the deadliest serotype to cause Legionnaires infectious and is responsible for 90% of the infections in humans. The bacterial pathogen is associated with a severe lung infection, known as legionaries' disease. It is resistant to multiple drugs, thus warranting novel vaccine candidates identification to immune the host against infections caused by the said pathogen. For this, we applied the subtractive proteomics and reverse vaccinology approaches to annotate the most essential genes suitable for vaccine designing. From the whole proteome, only five proteins (Q5ZVG4, Q5ZRZ1, Q5ZWE6, Q5ZT09, and Q5ZUZ8) as the best targets for further processing as they fulfill all the standard parameters set for in silico vaccine design. Immuno-informatics approaches were further applied to the selected protein sequences to prioritized antigenic epitopes for design a multi-epitope subunit vaccine. A multi-epitopes vaccine was designed by using suitable linkers to link the CTL (cytotoxic T lymphocytes), HTL (Helper T lymphocytes), B cell epitopes, and adjuvant to strengthen the vaccine's immunogenicity. The MEVC(multi-epitopes vaccine construct) was reported to interact with human immune receptor TLR-2 (toll-like receptor) robustly (docking score = -357.18 kcal/mol), and a higher expression was achieved in the Escherichia coli system (CAI = 0.88, and GC contents = 54.34%). Moreover, immune simulation revealed that on the 3rd day, the neutralization of the antigen started, while on the 5th day, the antigen was completely neutralized by the secreted immune factors. In conclusion, the designed vaccine candidate effectively triggered the immune response against eh pathogen; however, wet lab-based experimentations are highly recommended to prove the protective immunological proficiency of the vaccine against L. pneumophila.
RESUMEN
SARS-CoV-2, an RNA virus, has been prone to high mutations since its first emergence in Wuhan, China, and throughout its spread. Its genome has been sequenced continuously by many countries, including Pakistan, but the results vary. Understanding its genomic patterns and connecting them with phenotypic features will help in devising therapeutic strategies. Thus, in this study, we explored the mutation landscape of 250 Pakistani isolates of SARS-CoV-2 genomes to check the genome diversity and examine the impact of these mutations on protein stability and viral pathogenesis in comparison with a reference sequence (Wuhan NC 045512.2). Our results revealed that structural proteins mainly exhibit more mutations than others in the Pakistani isolates; in particular, the nucleocapsid protein is highly mutated. In comparison, the spike protein is the most mutated protein globally. Furthermore, nsp12 was found to be the most mutated NSP in the Pakistani isolates and worldwide. Regarding accessory proteins, ORF3A is the most mutated in the Pakistani isolates, whereas ORF8 is highly mutated in world isolates. These mutations decrease the structural stability of their proteins and alter different biological pathways. Molecular docking, the dissociation constant (KD), and MM/GBSA analysis showed that mutations in the S protein alter its binding with ACE2. The spike protein mutations D614G-S943T-V622F (-75.17 kcal/mol), D614G-Q677H (-75.78 kcal/mol), and N74K-D614G (-73.84 kcal/mol) exhibit stronger binding energy than the wild type (-66.34 kcal/mol), thus increasing infectivity. Furthermore, the simulation results strongly corroborated the predicted protein servers. Our analysis findings also showed that E, M, ORF6, ORF7A, ORF7B, and ORF10 are the most stable coding genes; they may be suitable targets for vaccine and drug development.
