Comparative modeling and molecular refinement of the enzyme Phosphoglucosamine mutase from Mycobacterium tuberculosis
Resumo
Tuberculosis (TB) is the leading cause of death from an infectious agent in the world according to the World Health Organization (WHO) and the epidemic is being strengthened by the emergence of Multi and eXtensively Drug Resistant strains (MDR-TB and XDR-TB), decreasing the treatment options that have been used for decades. The GlmM catalyzes the interconversion of glucosamine-6-phosphate (GlcN6P) to glucosamine-1-phosphate (GlcN1P), catalyzing the second step of the biosynthesis process of UDPGlcNAc (uridine diphospho-N-acetylglucosamine) which is essential for the life cycle of Mycobacterium Tuberculosis (MTB). In the present study, comparative modeling and molecular refinement techniques were used to generate a three-dimensional model of MTB GlmM enzyme.
Referências
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Sippl, M. J. (1993). Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Bioinformatics, 17(4):355–362.
Tosi, T., Hoshiga, F., Millership, C., Singh, R., Eldrid, C., Patin, D., Mengin-Lecreulx, D., Thalassinos, K., Freemont, P., and Gründling, A. (2019). Inhibition of the staphylococcus aureus c-di-amp cyclase daca by direct interaction with the phosphoglucosamine mutase glmm. PLoS pathogens, 15(1):e1007537.
WHO et al. (2018). Global tuberculosis report 2018. World Health Organization.
Colovos, C. and Yeates, T. O. (1993). Verification of protein structures: patterns of non-bonded atomic interactions. Protein science, 2(9):1511–1519.
Doreleijers, J. F., Rullmann, J. A., and Kaptein, R. (1998). Quality assessment of nmr structures: a statistical survey. Journal of molecular biology, 281(1):149–164.
Ekins, S., Mestres, J., and Testa, B. (2007). In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling. British journal of pharmacology, 152(1):9–20.
Eswar, N., Eramian, D., Webb, B., Shen, M.-Y., and Sali, A. (2008). Protein structure modeling with modeller. In Structural proteomics, pages 145–159. Springer.
Koul, A., Arnoult, E., Lounis, N., Guillemont, J., and Andries, K. (2011). The challenge of new drug discovery for tuberculosis. Nature, 469(7331):483.
Laskowski, R. A., MacArthur, M. W., Moss, D. S., and Thornton, J. M. (1993). Procheck: a program to check the stereochemical quality of protein structures. Journal of applied crystallography, 26(2):283–291.
Moraes, G. L., Gomes, G. C., De Sousa, P. R. M., Alves, C. N., Govender, T., Kruger, H. G., Maguire, G. E., Lamichhane, G., and Lameira, J. (2015). Structural and functional features of enzymes of mycobacterium tuberculosis peptidoglycan biosynthesis as targets for drug development. Tuberculosis, 95(2):95–111.
Morris, G. M. and Lim-Wilby, M. (2008). Molecular docking. In Molecular modeling of proteins, pages 365–382. Springer.
Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., and Ferrin, T. E. (2004). Ucsf chimera—a visualization system for exploratory research and analysis. Journal of computational chemistry, 25(13):1605–1612.
Plácido, A., Coelho, A., Abreu Nascimento, L., Gomes Vasconcelos, A., Fátima Barroso, M., Ramos-Jesus, J., Costa, V., das Chagas Alves Lima, F., Delerue-Matos, C., Martins Ramos, R., et al. (2017). Cry1a (b) 16 toxin from bacillus thuringiensis: Theoretical refinement of three-dimensional structure and prediction of peptides as molecular markers for detection of genetically modified organisms. Proteins: Structure, Function, and Bioinformatics, 85(7):1248–1257.
Rani, C. and Khan, I. A. (2016). Udp-glcnac pathway: Potential target for inhibitor discovery against m. tuberculosis. European Journal of Pharmaceutical Sciences, 83:62–70.
Rani, C., Mehra, R., Sharma, R., Chib, R., Wazir, P., Nargotra, A., and Khan, I. A. (2015). High-throughput screen identifies small molecule inhibitors targeting acetyltransferase activity of mycobacterium tuberculosis glmu. Tuberculosis, 95(6):664–677.
Sayers, E. W., Barrett, T., Benson, D. A., Bolton, E., Bryant, S. H., Canese, K., Chetvernin, V., Church, D. M., DiCuccio, M., Federhen, S., et al. (2009). Database resources of the national center for biotechnology information. Nucleic acids research, 38(suppl 1):D5–D16.
Shin, W.-H., Lee, G. R., Heo, L., Lee, H., and Seok, C. (2014). Prediction of protein structure and interaction by galaxy protein modeling programs. Bio Design, 2(1):1–11.
Sippl, M. J. (1993). Recognition of errors in three-dimensional structures of proteins. Proteins: Structure, Function, and Bioinformatics, 17(4):355–362.
Tosi, T., Hoshiga, F., Millership, C., Singh, R., Eldrid, C., Patin, D., Mengin-Lecreulx, D., Thalassinos, K., Freemont, P., and Gründling, A. (2019). Inhibition of the staphylococcus aureus c-di-amp cyclase daca by direct interaction with the phosphoglucosamine mutase glmm. PLoS pathogens, 15(1):e1007537.
WHO et al. (2018). Global tuberculosis report 2018. World Health Organization.
Publicado
26/12/2019
Como Citar
COSTA, Jhonatan; PEREIRA, Wildrimak ; BARROS, Romulo ; MENDES, Diego ; CARDOSO JÚNIOR, Fábio ; RAMOS, Ricardo .
Comparative modeling and molecular refinement of the enzyme Phosphoglucosamine mutase from Mycobacterium tuberculosis. In: ESCOLA REGIONAL DE COMPUTAÇÃO APLICADA À SAÚDE (ERCAS), 7. , 2019, Teresina.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 31-36.
