Three-dimensional models of antigens with serodiagnostic potential for leprosy: An in silico study

Abstract

BACKGROUND

Leprosy is a disease caused by Mycobacterium leprae (M. leprae), an intracellular pathogen that has tropism and affects skin and nervous system cells. The disease has two forms of presentation: Paucibacillary and multibacillary, with different clinical and immunological manifestations. Unlike what occurs in the multibacillary form , the diagnostic tests for the paucibacillary form are nonspecific and not very sensitive, allowing the existence of infected individuals without treatment, which contributes to the spread of the pathogen in the population. To mitigate this contamination, more sensitive diagnostic tests capable of detecting paucibacillary patients are needed.

AIM

To predict the three-dimensional structure models of M. leprae antigens with serodiagnostic potential for leprosy.

METHODS

In this in silico study, satisfactory templates were selected in the Protein Data Bank (PDB) using Basic Local Alignment Search Tool to predict the structural templates of ML2038, ML0286, ML0050, and 85B antigens by comparative modeling. The templates were selected according to general criteria such as sequence identity, coverage, X-ray resolution, Global Model Quality Estimate value and phylogenetic relationship; Clustal X 2.1 software was used in this analysis. Molecular modeling was completed using the software Modeller 9v13. Visualization of the models was made using ViewerLite 4.2 and PyMol software, and analysis of the quality of the predicted models was performed using the QMEAN score and Z-score. Finally, the three-dimensional moels were validated using the MolProbity and Verify 3D platforms.

RESULTS

The three-dimensional structure models of ML2038, ML0286, ML0050, and 85B antigens of M. leprae were predicted using the templates PDB: 3UOI (90.51% identity), PDB: 3EKL (87.46% identity), PDB: 3FAV (40.00% identity), and PDB: 1F0N (85.21% identity), respectively. The QMEAN and Z-score values indicated the good quality of the structure models. These data refer to the monomeric units of antigens, since some of these antigens have quaternary structure. The validation of the models was performed with the final three-dimensional structure - monomer (ML0050 and 85B antigens) and quaternary structures (ML2038 and ML0286). The majority of amino acid residues were observed in favorable and allowed regions in the Ramachandran plot, indicating correct positioning of the side chain and absence of steric impediment. The MolProbity score value and Verify 3D results of all models indicated a satisfactory prediction.

CONCLUSION

The polarized immune response against M. leprae creates a problem in leprosy detection. The selection of immunodominant epitopes is essential for the development of more sensitive serodiagnostic tests, for this it is important to know the three-dimensional structure of the antigens, which can be predicted with bioinformatics tools.

Keywords: Antigens; Leprosy diagnosis; Mycobacterium leprae; Molecular modelling; Serological test; In silico study

Core Tip: Leprosy is a disease with high clinical and epidemiological impact, because it causes irreversible and disfiguring sequelae and has a high incidence in endemic countries. Its variability of manifestations, with different immune responses and the difficulty of cultivating Mycobacterium leprae (M. leprae) in the laboratory, makes it difficult to develop sensitive and specific tests for the diagnosis of the disease, thus emphasizing the importance of in silico studies to solve this problem. In this sense, this study aimed to obtain three-dimensional models of M. leprae antigens, which have stood out in previous studies as candidates for the serological diagnosis of leprosy.