Mining of novel drug/vaccine targets from the proteome of Burkholderiacepaciausing computational tools through reverse vaccinology approach

Aim : The present study anticipates prediction of novel drug/vaccine candidates from the group of uncharacterized proteins of Burkholderiacepaciausing a series of computational tools. B.cepacia is an emerging pulmonary pathogen in immunocompromised patients and in patients with cystic fibrosis (CS). Infections caused by these bacteria are difficult to treat due to antibiotic resistance. So far there are no drugs/vaccines against B.Cepacia.Materials and Methods: A total of 50 hypothetical proteins were retrieved from NCBI and studied using computational tools for studying their localization, membrane helices, physicochemical properties, virulence factors, signal peptides, antigenicity, and epitopes. These proteins were then subjected to BLAST to find they are matching with any human homologs to avoid autoimmune reactions. Results: Out of 50, 3 were found to be highly virulent proteins that possess antigenic properties and they are not human homologs. Conclusion: Hence, these proteins could be putative drug targets against Burkholderiacepaciainfections. Nevertheless, they require further in-vitro and in-vivo experiments for validation.