Identification of potential candidates for drug designing against Klebsiella Pneumoniae among hypothetical proteins of DNA Adenine Methyltransferase through subtractive genomics approach

Klebsiella Pneumoniae is a gram-negative bacterium that is known for causing infection in nosocomial settings. As reported by WHO, this bacterial pathogen is classified as an urgent threat our most concern is that these bacterial pathogens acquired genetic traits that make them resistant towards antibiotics. The last class of antibiotics; carbapenems are not able to combat these bacterial pathogens allowing them to clonally expand their antibiotic-resistant strain. Most antibiotics target the essential pathways of the bacteria cell however these targets are no longer susceptible to the antibiotic. Hence in our study, we focus on Klebsiella Pneumoniae bacterial strains that contain DNA Adenine Methyltransferase domain which suggests a new potential site for a drug target. DNA methylation is seen to regulate the attenuation of bacterial virulence. In this study, all hypothetical proteins of Klebsiella Pneumoniae containing N6 DNA Adenine Methyltransferase domain were analysed for a potential drug target. About 32 hypothetical proteins were retrieved from Uniprot. 19 proteins were selected through a step-wise subtractive genomics approach like a selection of non-homologus proteins against the human host, selection of bacterial proteins contains an essential gene, broad-spectrum analysis, druggability analysis, Non-homology analysis against gut microbiota. Through drug target prioritization like sub-cellular analysis, drug property analysis, anti-target non-homology analysis, virulence factor analysis and protein-protein interaction analysis one drug target protein (Uniprot ID: A0A2U0NNR3) was prioritized. Identified drug target docked with potential inhibitors like are mahanine (PubChem ID: 375151), curcumin (PubChem ID: 969516), EGCG (PubChem ID: 65064), nanaomycin A (PubChem ID: 40586), parthenolide (PubChem ID: 7251185), quercetin (PubChem ID: 5280343) and trimethylaurintricarboxylic acid. Based on the moelcular docking analysis, mahanine has the highest binding affinity. In order to identify novel natural inhibitor based on mahanine fingerprint search is performed against NPASS (Natural Product Activity and Species Source databases) and Koenimbine was identified as a novel natural inhibitor based on virtual screening.