Published Jan 1, 2012


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Leidy Viviana Barreto

George Emílio Barreto

Ludis Morales

Orlando Emilio Acevedo

Janneth González Santos



Objective. Predict by computational means the 3D structure of the antigenic protein LIC10494 and report associated important functional regions for its pathogenicity and immunogenicity. Materials and methods. We performed a computational analysis of the primary structure of LIC10494 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 energy minimization was done using the AMBER94 force field of the Schrodinger suite of molecular analysis, and the stereochemistry and energy model validation was performed by the RAMPAGE server. The final model was visualized using PyMol V.0,98. Results. This study proposes a computational model that describes the 3D structure of the hypothetical lipoprotein LIC10494 and agrees with previous experimental reports; thus, our study demonstrates the existence of patterns that could play an  important role in the pathogenicity and protection of the bacteria against the host immune system; the presence of a disorganized region between amino acids 80 and 140, and of 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 and immunogenic characteristics of the bacteria.

Key words: Antigen, Bacteria Leptospirosis, LIC10494, Outer membrane protein.


How to Cite
Barreto, L. V., Barreto, G. E., Morales, L., Acevedo, O. E., & González Santos, J. (2012). Protein LIC10494 of Leptospira interrogans serovar Copenhageni: structural model and associated functional regions. Universitas Scientiarum, 17(1), 16–27.
Bioinformatics and modeling

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