An increase in expansion of antibiotic-resistant bacterial pathogens alarms the world's population and creating a wave of the antibiotic apocalypse. The inclination of the death rate due to these antibiotic-resistant superbugs signifies urgency towards a new drug discovery to combat against these bacterial pathogens. The last class of antibiotics developed leaves a huge gap in the antibiotic timeline as the antibiotic development progress failed to kill the bacteria. Current antibiotic targets the central dogma of the bacteria hence finding a new potential drug target could eliminate the superbugs. It is, therefore, crucial to understand the underlying mechanism to identify the root cause of the resistant characteristic by understanding the biological cellular processes. Hypothetical proteins are an uncharacterized protein that is not known for its function which could provide a deeper understanding of the metabolic pathway of the bacterial proteome. This paper will generally provide a guideline for non-bioinformatician to mine potential drug targets from hypothetical proteins of bacterial proteome using a fast and less-cost bioinformatics approach.

Klebsiella pneumoniae is a gram-negative bacterium that is known for causing infection in nosocomial settings. As reported by the World Health Organization, carbapenem-resistant Enterobacteriaceae, a category that includes K. pneumoniae, are classified as an urgent threat, and the greatest concern is that these bacterial pathogens may acquire 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 antibiotic-resistant strains. Most antibiotics target essential pathways of bacterial cells; however, these targets are no longer susceptible to antibiotics. Hence, in our study, we focused on a hypothetical protein in K. pneumoniae that contains a DNA methylation protein domain, suggesting a new potential site as a drug target. DNA methylation regulates the attenuation of bacterial virulence. We integrated computational-aided drug design by using a bioinformatics approach to perform subtractive genomics, virtual screening, and fingerprint similarity search. We identified a new potential drug, koenimbine, which could be a novel antibiotic.

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Neisseria gonorrhoeae is a Gram-negative aerobic diplococcus bacterium that primarily causes sexually transmitted infections through direct human sexual contact. It is a major public health threat due to its impact on reproductive health, the widespread presence of antimicrobial resistance, and the lack of a vaccine. In this study, we used a bioinformatics approach and performed subtractive genomic methods to identify potential drug targets against the core proteome of N. gonorrhoeae (12 strains). In total, 12,300 protein sequences were retrieved, and paralogous proteins were removed using CD-HIT. The remaining sequences were analyzed for non-homology against the human proteome and gut microbiota, and screened for broad-spectrum analysis, druggability, and anti-target analysis. The proteins were also characterized for unique interactions between the host and pathogen through metabolic pathway analysis. Based on the subtractive genomic approach and subcellular localization, we identified one cytoplasmic protein, 2Fe-2S iron-sulfur cluster binding domain-containing protein (NGFG RS03485), as a potential drug target. This protein could be further exploited for drug development to create new medications and therapeutic agents for the treatment of N. gonorrhoeae infections.

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