Proteína LIC10494 de Leptospira interrogans serovar Copenhageni: modelo estructural y regiones funcionales asociadas

• Main Authors: Orlando Emilio Acevedo, George Emílio Barreto, Janneth González-Santos
• Format: Article
• Language: English
• Published: Pontificia Universidad Javeriana 2012-04-01
• Series: Universitas Scientiarum
• Subjects: antigen; bacteria leptospirosis; LIC10494; outer membrane protein.
• Online Access: http://revistas.javeriana.edu.co/index.php/scientarium/article/view/2478/1757
• ISSN: 0122-7483; 2027-1352

Protein LIC10494 of Leptospira interrogans serovar Copenhageni: structural model and associated functional regions. Objective.Predict by computational means the 3D structure of the antigenic protein LIC10494 and report associated important functional regionsfor its pathogenicity and immunogenicity. Materials and methods. We performed a computational analysis of the primary structure ofLIC10494 using the servers BLAST, PROTPARAM, PROTSCALE, DAS, SOSUI, TOPPRED, TMAP, TMpred, SPLIT4, PHDHTM,TMHMM2, HMMTOP2, GLOBPLOT and PROSITE. The secondary structure was obtained by consensus of the algorithms SOPM,PREDATOR GOR4, DPM and DSC. The approach to the tertiary structure was obtained using the algorithm MUSTER. The energyminimization was done using the AMBER94 force field of the Schrodinger suite of molecular analysis, and the stereochemistry andenergy model validation was performed by the RAMPAGE server. The final model was visualized using PyMol V.0,98. Results. Thisstudy proposes a computational model that describes the 3D structure of the hypothetical lipoprotein LIC10494 and agrees with previousexperimental reports; thus, our study demonstrates the existence of patterns that could play an important role in the pathogenicity andprotection of the bacteria against the host immune system; the presence of a disorganized region between amino acids 80 and 140, andof a transmembrane segment between amino acids 8 and 22. Conclusion. The coincidence between structural and functional segments suggests that our model can be used to predict certain aspects of the biological behaviour of the protein according to the pathogenic andimmunogenic characteristics of the bacteria.