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 Online Journal of Bioinformatics ©

Volume 12(2):217-229, 2011

Homology modeling and active site analysis of MurB Reductase: A potential drug target of Legionella pneumophila


Vani Priyadarshini (MSc), Dibyabhaba Pradhan (MSc), Manne Munikumar (MSc) and Amineni Umamaheswari (PhD)*


SVIMS Bioinformatics Centre, Department of Bioinformatics, SVIMS University, Tirupati, PIN: 517507, India. Email:




Priyadarshini V, Pradhan D, Munikumar M, Umamaheswari A., Homology Modeling and Active Site Analysis of MurB Reductase: A Potential Drug Target of Legionella pneumophila, Onl J Bioinform., 12(2):217-229, 2011. Legionella pneumophila is increasingly recognized as a significant cause of Legionnairesí disease, pneumonia and life-threatening prosthetic valve endocarditis in ambulatory and hospitalized patients. The severe consequences of these disease demands the need to gain insight on novel drug targets of L. pneumophila for facilitating rational drug design.UDP-N- acetyl enolpyruvoyl glucosamine reductase (MurB) plays a vital role in peptidoglycan biosynthesis by catalyzing UDP-N-acetylglucosamine enolpyruvate to UDP-N-acetylmuramic acid. There is no alternative mechanism in L. pneumophila to substitute catalytic activity rendered by MurB and was selected as a potential molecular target against the pathogen. Homology modeling method was accomplished to construct MurB tertiary structure incorporating FAD using Modeller9v8. The predicted structure was validated through DOPE score correlation, superpose, PROCHECK and ProSA. The predicted structure being highly reliable was submitted to the protein model database (PMDB) that accepted the structure with less than 3% stereo chemical check failure. Ligand binding site residues were located from MurB model in complex with FAD using PyMOL, LIGPLOT and CASTp. Structural, functional and active site information on MurB of L. pneumophila would aid in rational drug design for novel drug discovery to combat the pathogen.


Keywords: Legionnairesí disease, Bronchopneumonia, MurB, Homology modeling