Abstract

Pseudomonas aeruginosa is an opportunistic, non-fermentative, gram-negative rod which is an important causes of nosocomial infection leading to septicemia and death. The mortality rate is higher than bacteremia�s caused byother gram-negative opportunistic pathogens. One of the most important features of the bacterium is its resistance to various antibacterial agents, and even newly developed antibiotics have failed to reduce the mortalityrate associated with this organism. There is increasing interest in bacterial virulence factors as a basis for effective vaccines and immune therapies. Extracellular products and cell structures of P. aeruginosa contain numerous antigens with different specificity. These antigens have different roles for the formation of host protective immunity against P.aeruginosa. Due to the accessibility on the bacterial surface, LPS and OM proteins of P. aeruginosa are particularly important targets for vaccine studies. Thus identification of epitopes and functional sites on the surface of this protein is important for vaccine design against Pseudomonas aeruginosa. We predict OprL 3D structure with homology modeling approach. In this regard ElliPro predicts linear and discontinuous antibody epitopes based on a protein antigen's 3D structure. ElliPro associates each predicted epitope with a score, defined as a PI (Protrusion Index) value averaged over epitope residues. For each residue, a PI value is defined as percentage of the protein atoms enclosed in the ellipsoid, which approximates the protein surface, at which the residue first becomes lying outside the ellipsoid. © 2016, International Journal of Pharmacy and Technology. All rights reserved.