Immunoinformatics Driven Prediction of Multiepitopic Vaccine Against Klebsiella pneumoniae and Mycobacterium tuberculosis Coinfection and Its Validation via In Silico Expression

Klebsiella pneumoniae and Mycobacterium tuberculosis coinfection is one of the most lethal combinations that has been becoming frequent yet, not diagnosed and reported properly. Due to the simultaneous occurrence of both infections, diagnosis is delayed leading to inadequate treatments and mortality. With the rise of MDR Klebsiella and Mycobacterium, a prophylactic and an immunotherapeutic vaccine has to be entailed for preemptive and adroit therapeutic approach. In this study, we aim to implement reverse vaccinology approach that encompasses a comprehensive evaluation of vital aspects of the pathogens to explore immunogenic epitopes against Omp A of Klebsiella and Rv1698, Rv1973 of Mtb that may help in vaccine development. The designed multi-epitopic vaccine was assessed for antigenicity, allergenicity and various physiochemical parameters. Molecular docking and simulations were executed to assess the immunogenicity and complex stability of the vaccine. The final multi-epitopic vaccine is validated to be highly immunogenic and can serve as a valuable proactive remedy for subject pathogens.