Multiple Drug Resistant (MDR) bacteria are no more inhibited by the front line antibiotics due to extreme resistance. Methicillin Resistant Staphylococcus aureus (MRSA) is one of the MDR pathogens notorious for its widespread infection around the world. The high resistance acquired by MRSA needs a serious concern and efforts should be carried out for the discovery of better therapeutics. With this aim, we designed a comparison of the metabolic pathways of the pathogen, MRSA strain 252 (MRSA252) with the human host (i.e., Homo sapiens) by using well-established in silico methods. We identified several metabolic pathways unique to MRSA (i.e., absent in the human host). Furthermore, a subtractive genomics analysis approach was applied for retrieval of proteins only from the unique metabolic pathways. Subsequently, proteins of unique MRSA pathways were compared with the host proteins. As a result, we have shortlisted few unique and essential proteins that could act as drug targets against MRSA. We further assessed the druggability potential of the shortlisted targets by comparing them with the DrugBank Database (DBD). The identified drug targets could be useful for an effective drug discovery phase. We also searched the sequences of unique as well as essential enzymes from MRSA in Protein Data Bank (PDB). We shortlisted at least 12 enzymes for which there was no corresponding deposition in PDB, reflecting that their crystal structures are yet to be solved! We selected Glutamate synthase out of those 12 enzymes owing to its participation in significant metabolic pathways of the pathogen e.g., Alanine, Aspartate, Glutamate and Nitrogen metabolism and its evident suitability as drug target among other MDR bacteria e.g., Mycobacteria. Due to the unavailability of any crystal structure of Glutamate synthase in PDB, we generated the 3D structure by homology modeling. The modeled structure was validated by multiple analysis tools. The active site of Glutamate synthase was identified by not only superimposing the template structure (PDB ID: 1E0A) over each other but also by the Parallel-ProBiS algorithm. The identified active site was further validated by cross-docking the co-crystallized ligand (2-oxoglutaric acid; AKG) of PDB ID: 1LLW. It was concluded that the comparative metabolic in silico analysis together with structure-based methods provides an effective approach for the identification of novel antibiotic targets against MRSA.
- Comparative metabolic pathways
- Homology modeling
- Subtractive genomics