Metabolic pathway analysis approach: Identification of novel therapeutic target against methicillin resistant Staphylococcus aureus Reaz Uddin a, ⁎, Kiran Saeed a , Waqasuddin Khan a,b , Syed Sikander Azam c , Abdul Wadood d a Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi-75270, Pakistan b Jamil-ur-Rahman Center for Genome Research, PCMD Ext., International Center for Chemical and Biological Sciences, University of Karachi, Karachi-75270, Pakistan c National Centre for Bioinformatics, Quaid-i-Azam University, Islamabad, Pakistan d Department of Biochemistry, Abdul Wali Khan University, Mardan, Pakistan abstract article info Article history: Received 13 August 2014 Received in revised form 18 November 2014 Accepted 25 November 2014 Available online 28 November 2014 Keywords: Comparative metabolic pathways Subtractive genomics Infection MRSA Homology modeling Multiple Drug Resistant (MDR) bacteria are no more inhibited by the front line antibiotics due to extreme resis- tance. Methicillin Resistant Staphylococcus aureus (MRSA) is one of the MDR pathogens notorious for its wide- spread 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 com- paring 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 ac- tive 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 compar- ative metabolic in silico analysis together with structure-based methods provides an effective approach for the identification of novel antibiotic targets against MRSA. © 2014 Elsevier B.V. All rights reserved. 1. Introduction Since existing antibiotics are ineffective against Methicillin Resistant Staphylococcus aureus strain 252 (MRSA252), the discovery of novel an- tibiotics is of prime need. Unfortunately, the fast growing resistance among MRSA is a major obstacle for bringing new regimens. Contrary to that the recent developments in complete genome analysis with the combination of bioinformatics exemplify a simple method for searching the unique therapeutic targets (Butt et al., 2012a). In silico comparative metabolic pathway analysis is a well-established method having the following applications: 1 Cross species metabolic pathway comparison (Ebenhoh et al., 2005). 2 Identification of unique metabolic pathways and related enzyme data (Amir et al., 2014). 3 Identification of common pathways between host and pathogen (Smith et al., 2012). The availability of full metabolic pathways and its related enzymes opens up higher order possibilities for comparison analysis (Bork Gene 556 (2015) 213–226 Abbreviations: MRSA, Methicillin Resistant S. aureus; KEGG, Kyoto Encyclopedia of Genes and Genomes; PDB, Protein Databank; BLAST, Basic Local Alignment Search Tool; NCBI-GI, NCBI Gene Identification Number; MDR, Multiple Drug Resistant; TB, Tuberculosis; MTB, Mycobacterium tuberculosis. ⁎ Corresponding author at: Lab No. 103, PCMD Ext., Dr. Panjwani Center for Molecular Medicine and Drug Research, International Center for Chemical and Biological Sciences, University of Karachi, Karachi 75270, Pakistan. E-mail address: mriazuddin@iccs.edu (R. Uddin). http://dx.doi.org/10.1016/j.gene.2014.11.056 0378-1119/© 2014 Elsevier B.V. All rights reserved. Contents lists available at ScienceDirect Gene journal homepage: www.elsevier.com/locate/gene