Structural characterization of the abc molybdate and oligopeptide transporters in mycobacterium tuberculosis using bioinformatics

Authors

DOI:

https://doi.org/10.24933/e-usf.v8i1.382

Keywords:

Multiresistance, Bioinformatics, Rational drug design, Structural Biology

Abstract

Mycobacterium tuberculosis, the tuberculosis pathogen, poses a significant challenge to public health due to antibiotic resistance and associated high mortality, necessitating the constant search for new antimicrobials. One potential therapeutic target is the ABC transporters of molybdate and oligopeptides, as they play a crucial role in the bacterium's survival by importing these essential nutrients into its cell interior. Thus, the aim of this study is to identify and characterize these transporters in M. tuberculosis through in silico analyses. A complete system of ABC transporters was identified for each of the studied nutrients, comprising SBP, permeases, and ATPases, organized in unique operons in the genome. Structurally, SBP exhibited signal peptide regions indicating extracellular functions, while permeases showed six transmembrane regions, suggesting membrane localization. ATPases were identified by the presence of the characteristic AAA domain. The SBP, ModA and OppA, displayed conserved three-dimensional structures, classified as type II SBPs, and sequence analysis identified conserved amino acids in the binding pockets of SBP, suggesting interactions with substrates. These results highlight potential targets for antimicrobial therapies, providing insights for future investigations into the interaction mechanism between SBPs and their transported substrates. 

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Author Biography

Aline Sampaio Cremonesi, Universidade São Francisco

Graduada em Ciências Biológicas pela Pontifícia Universidade Católica de Campinas (PUCCAMP), possui Mestrado em Biologia Funcional e Molecular com ênfase em Bioquímica pela Universidade Estadual de Campinas (UNICAMP) e doutorado em Biotecnologia pela Universidade de São Paulo (USP), desenvolvendo todos os projetos no Laboratório Nacional de Biociências (LNBio) operado pelo Centro Nacional de Pesquisa em Energia e Materiais (CNPEM). Tem experiência em cultura e metabolismo microbiano, engenharia genética, expressão de proteínas em diferentes tipos celulares e análises biofísicas e estruturais de proteínas e peptídeos. Atualmente é professora com certificação Google for Education, de disciplinas na graduação e pós-graduação em diferentes cursos da área da saúde, com projetos voltados para a análises estruturais de transportadores do tipo ABC relacionados a resistência bacteriana e de organismos de interesse veterinário. É membro da equipe científica da empresa Aplasys, atuante na área de engenharia genética e solubilidade de proteínas.

References

ALTSCHUL, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, v. 25, p. 3389-3402, 1997. DOI: https://doi.org/10.1093/nar/25.17.3389

ARMENTEROS, J. J. A.; TSIRIGOS, K.; SONDERBY, C. K.; PETERSEN, T. N.; WINTHER, O.; BRUNA K., S.; HEIJNE, G. v.; NIELSEN, H. SignalP 5.0 improves signal peptide predictions using deep neural networks. Nature Biotechnology, v. 37, n. 4, p.420-423, 2019. DOI: https://doi.org/10.1038/s41587-019-0036-z

BARREIRO, E J.; FRAGA, C. A. M. Química Medicinal: As bases moleculares da ação dos fármacos. Artmed Editora, 2014.

BUCHAN, D. W. A., JONES, D. T. The PSIPRED Protein Analysis Workbench: 20 years on. Nucleic acids research, v.2, n. 47, 2019. (W1), W402–W407. DOI: https://doi.org/10.1093/nar/gkz297

CAMINERO, L. JA. Challenges and Outlooks in Multi-drug Resistant Tuberculosis. Arch Bronconeumol. 2017 Aug. v.53, n. 8, p.417-418. English, Spanish. DOI: https://doi.org/10.1016/j.arbres.2017.01.018

CHAI, H.; KIM, Y.; HAM, J.; KIM, T.; LIM, D. Identifying ligand-binding specificity of the oligopeptide receptor OppA from Bifidobacterium longum KACC91563 by Structure-based molecular modeling. Research Square; 2020. DOI: https://doi.org/10.1016/j.arabjc.2022.104198

CHEN, Ping et al. A highly efficient Ziehl-Neelsen stain: identifying de novo intracellular Mycobacterium tuberculosis and improving detection of extracellular M. tuberculosis in cerebrospinal fluid. Journal of clinical microbiology, v. 50, n. 4, p. 1166-1170, 2012. DOI: https://doi.org/10.1128/jcm.05756-11

CREMONESI, A.S.; DE LA TORRE, L.I.; DEGENHARDT, M.F.S.; MUNIZ,G.S.V.; LAMY, V.T.; OLIVEIRA, C.L.P. BALAN, A. The citrus plant pathogen Xanthomonas citri has a dual polyamine-binding protein. Archives of Biochemistry and Biophysics, v. 28, p. 1-12, 2021. DOI: https://doi.org/10.1016/j.bbrep.2021.101171

DELANO, W. L. The PyMol Molecular Graphics System DeLano Scientific, 2002. http://www.pymol.org/

DEVLIN, T. M. Manual de bioquímica: com correlações clínicas. Editora Blucher, 2011.

FILHO, O. A. S.; ALENCASTRO, R. B. Modelagem de proteínas por homologia. Química Nova, v. 26, p. 253-259, 2003. DOI: https://doi.org/10.1590/S0100-40422003000200019

GUNA, A.; HEDGE, R. S. Transmembrane Domain Recognition during Membrane Protein Biogenesis and Quality Control. Current Biology Review, v.28, 2018. DOI: https://doi.org/10.1016/j.cub.2018.02.004

HU, Y., RECH, S., GUNSALUS, R. et al. Crystal structure of the molybdate binding protein ModA. Nat Struct Mol Biol, v.4, p.703–707, 1997. DOI: https://doi.org/10.1038/nsb0997-703

KANEHISA, M. et al. KEGG for linking genomes to life and the environment. Nucleic acids research, v. 36, n. suppl_1, 2007, p. D480-D484. DOI: https://doi.org/10.1093/nar/gkm882

KROGH, A. et al. Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes. Journal of Molecular Biology, v. 305, n. 3, p. 567-580, 2001. DOI: https://doi.org/10.1006/jmbi.2000.4315

LARKIN, M. A. et al. Clustal W and Clustal X version 2.0. bioinformatics, v. 23, n. 21, p. 2947-2948, 2007. DOI: https://doi.org/10.1093/bioinformatics/btm404

LIMA, R. N. S.; COSTA, S. O. P. D.; FERREIRA, R. C. C. O Transporte de Oligopeptídeos na fisiologia e patogênese de bactérias do gênero Streptococcus. Revista de Microbiologia, Janeiro, 2014.

LOCHER, K. P. Mechanistic diversity in ATP-binding cassette (ABC) transporters. Nat Struct Mol Biol, v.23, p. 487-493, 2016. DOI: https://doi.org/10.1038/nsmb.3216

MCGUFFIN, L. J.; BRYSON, K.; JONES, D. T. The PSIPRED protein structure prediction server. Bioinformatics Applications Note, v. 16, p. 404-405, 2000. DOI: https://doi.org/10.1093/bioinformatics/16.4.404

MENON, S.; PIRAMANAYAKAM, S.; AGARWAL, G. Computational identification of promoter regions in prokaryotes and Eukaryotes. EPRA International Journal of Agriculture and Rural Economic Research (ARER), v. 9, n. 7, p. 21-28, 2021. DOI: https://doi.org/10.36713/epra7667

MIRDITA, M., SCHUTZE, K., MORIWAKI, Y. et al. ColabFold: making protein folding accessible to all. Nat Methods,v.19, p.679–682, 2022. DOI: https://doi.org/10.1038/s41592-022-01488-1

MOUTRAN, A. Modelagem molecular das proteínas captadoras de Molibdato (ModA) e Oligopeptídeo (OppA) de Xanthomonas axonopodis pv. citri. 2009. Tese (Doutorado em Microbiologia) – Universidade de São Paulo, São Paulo, 2009. DOI: https://doi.org/10.11606/T.42.2009.tde-16072009-100344

OLIVEIRA, M. C. B.; BALAN, A. The ATP-Binding Cassette (ABC) transport systems in Mycobacterium tuberculosis: Structure, function, and possible targets for therapeutics. Biology, v. 9, n. 12, p. 443, 2020. DOI: https://doi.org/10.3390/biology9120443

ORGANIZAÇÃO MUNDIAL DA SAÚDE. Relatório Global sobre Tuberculose. Genebra: OMS, 2023. ISBN: 978-92-4-008385-1

PATRA, P. et al. Epitope-based vaccine designing of nocardia asteroides targeting the virulence factor mce-family protein by immunoinformatics approach. International Journal of Peptide Research and Therapeutics, v. 26, p. 1165-1176, 2020. DOI: https://doi.org/10.1007/s10989-019-09921-4

PRILUSKY, J., FELDER, C. E., ZEEV-BRN-MORDEHAI, T., RYDBERG, E. H., MAN, O., BECKMANN, J. S., SILMAN, I., SUSSMAN, J. L. FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics (Oxford, England), v. 21, n. 16, p. 3435–3438, 2005. DOI: https://doi.org/10.1093/bioinformatics/bti537

PUCHADES, C.; SANDATE, C. R.; LANDER, G. C. The molecular principles governing the activity and functional diversity of AAA+ proteins. Nature Reviews Molecular Cell Biology, v. 21, n. 1, p. 43-58, 2020. DOI: https://doi.org/10.1038/s41580-019-0183-6

RAHMAN, M. M.; MACHUCA, M. A.; ROUJEINIKOVA, A. Bioinformatics analysis and biochemical characterisation of ABC transporter-associated periplasmic substrate-binding proteins ModA and MetQ from Helicobacter pylori strain SS1. Biophysical Chemistry, v. 272, p. 106577, 2021. DOI: https://doi.org/10.1016/j.bpc.2021.106577

SALAMOV, V. S. A.; SOLOVYEVAND, A. Automatic annotation of microbial genomes and metagenomic sequences. Metagenomics and its applications in agriculture, biomedicine and environmental studies, p. 61-78, 2011.

SILVA, G. A. A. Caracterização do antígeno proteico ssaa de Staphylococcus saprophyticus utilizando estratégias in silico e modelo ex vivo de infecção. 2020. Tese (Mestrado em Genética e Biologia Molecular) - Universidade Federal de Goiás, Goiás 2020. http://repositorio.bc.ufg.br/tede/handle/tede/10597

SILVA, K.M.; FIGUEIREDO, N.G.; CREMONESI, A.S. Use of Bioinformatics Techniques in the Characterization of Genes and Proteins Involved in the Transport of Polyamines from Staphylococcus Genus. JSM Bioinformatics, Genomics and Proteomics, v. 6, n.1, 2023. DOI: https://doi.org/10.47739/2576-1102/1041

SOUZA, C. et al. Estratégia Algorítmica para a Reconstrução e Validação da Estrutura Molecular de Variantes do SARS-CoV-2. Anais do XV Brazilian e-Science Workshop. SBC, 2021. p. 65-72. DOI: https://doi.org/10.5753/bresci.2021.15790

SUBHASREE, C. R. et al. Review on comparative genomics for mycobacterium tuberculosis strains. International Journal of Pharmaceutical Sciences and Research, v. 8, n. 12, p. 5022-5042, 2017. DOI: https://doi.org/10.13040/IJPSR.0975-8232.8(12).5022-42

TEUFEL, F. et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nature biotechnology, v. 40, n. 7, p. 1023-1025, 2022. DOI: https://doi.org/10.1038/s41587-021-01156-3

WEBB, B.; SALI, A. Comparative protein structure modeling using MODELLER. Current protocols in bioinformatics, v. 54, n. 1, 2016. DOI: https://doi.org/10.1002/cpbi.3

YANG X, LIU H, ZHANG Y, SHEN X. Roles of Type VI Secretion System in Transport of Metal Ions. Front Microbiol., v.5, n.1, 2021. DOI: https://doi.org/10.3389/fmicb.2021.756136

ZAHA, A.; FERREIRA, H. B.; PASSAGLIA, L.M.P. Biologia Molecular Básica-5. Artmed Editora, 2014.

Published

2024-08-28

How to Cite

Évelyn Briotto Lima, B., Stênico Zanuni, L., & Sampaio Cremonesi, A. (2024). Structural characterization of the abc molybdate and oligopeptide transporters in mycobacterium tuberculosis using bioinformatics. Ensaios USF, 8(1). https://doi.org/10.24933/e-usf.v8i1.382

Issue

Section

Ciências Biológicas e da Saúde