Estudo in silico de alcalóides derivados da Catharantus roseus em sítio ativo do Trypanossoma cruzi via ancoragem molecular

Autores

DOI:

https://doi.org/10.33448/rsd-v11i5.28114

Palavras-chave:

Trypanosoma cruzi; Catharanthus roseus; Ancoragem molecular.

Resumo

A Doença de Chagas é uma doença tropical negligenciada causada pelo protozoário Trypanosoma cruzi. Atualmente apenas os fármacos benznidazol e nifurtimox são utilizados no tratamento da doença, porém, além dos efeitos adversos, estes fármacos possuem eficácia reduzida principalmente para casos crônicos da doença. Uma alternativa viável consiste na investigação de novos fármacos a partir de produtos naturais. A Catharanthus roseus é uma planta comum em regiões tropicais e possui mais de 130 alcaloides de relevante interesse científico. O presente trabalho teve por objetivo investigar produtos naturais na prospecção de novos fármacos antichagásicos. Estudos in silico de ancoragem molecular foram realizados para 21 terpenoides derivados da Catharanthus roseus no sítio ativo da cruzaína, principal cisteíno protease do Trypanosoma cruzi. Os principais resultados demonstraram a formação de complexos enzimáticos de considerável estabilidade para os compostos estrictosidina (ΔG = -11,23 Kcal.mol-1), ajmalicina (ΔG = -9,59 Kcal.mol-1) e serpentina (ΔG = -9,28 Kcal.mol-1). Tais resultados demonstraram uma boa atividade inibidora enzimática da cruzaína. Previsões via ADMET e PASS apresentaram resultados promissores para taxas de absorção e biodisponibilidade. Assim sendo, as moléculas investigadas foram consideradas como promissoras na prospecção de novos fármacos antichagásicos.

Referências

Alvarez, V. E., Iribarren, P. A., Niemirowicz, G. T., & Cazzulo, J. J. (2021). Update on relevant trypanosome peptidases: Validated targets and future challenges. Biochimica et Biophysica Acta. Proteins and Proteomics, 1869(2), 140577.

Asai, T., Adachi, N., Moriya, T., Oki, H., Maru, T., Kawasaki, M., Suzuki, K., Chen, S., Ishii, R., Yonemori, K., Igaki, S., Yasuda, S., Ogasawara, S., Senda, T., & Murata, T. (2021). Cryo-EM Structure of K+-Bound hERG Channel Complexed with the Blocker Astemizole. Structure (London, England: 1993), 29(3), 203-212.e4.

Berenstein, A. J., Falk, N., Moscatelli, G., Moroni, S., González, N., Garcia-Bournissen, F., Ballering, G., Freilij, H., & Altcheh, J. (2021). Adverse Events Associated with Nifurtimox Treatment for Chagas Disease in Children and Adults. Antimicrobial Agents and Chemotherapy, 65(2), e01135-20.

Berman, H. M. (2000). The Protein Data Bank. Nucleic Acids Research, 28(1), 235–242.

Brasil. (2019). Ministério da Saúde. Secretária de Vigilância em Saúde. Fortalecimento das ações de prevenção, controle e eliminação da malária e ações de vigilância da leishmaniose visceral e doença de Chagas. Boletim Epidemiológico, v. 50(40), 10-15.

BROWN, R. D.; HASSAN, M.; WALDMAN, M.. (2001). Tools for Designing Diverse, Druglike, Cost-Effective. In: GHOSE, A.; VISWANADHAN, V.. Combinatorial Library Design and Evaluation: Principles, Software, Tools, and Applications in Drug Discovery. Boca Raton: CRC Press. 321-356.

Caldas, I. S., Santos, E. G., & Novaes, R. D. (2019). An evaluation of benznidazole as a Chagas disease therapeutic. Expert Opinion on Pharmacotherapy, 20(15), 1797–1807.

Chao, C., Leone, J. L., & Vigliano, C. A. (2020). Chagas disease: Historic perspective. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, 1866(5), 165689.

Chen, Y. T., Brinen, L. S., Kerr, I. D., Hansell, E., Doyle, P. S., McKerrow, J. H., & Roush, W. R. (2010). In Vitro and In Vivo Studies of the Trypanocidal Properties of WRR-483 against Trypanosoma cruzi. PLoS Neglected Tropical Diseases, 4(9), e825.

Costa, A. N., de Sá, É. R. A., Bezerra, R. D. S., Souza, J. L., & Lima, F. das C. A. (2021). Constituents of buriti oil (Mauritia flexuosa L.) like inhibitors of the SARS-Coronavirus main peptidase: an investigation by docking and molecular dynamics. Journal of Biomolecular Structure & Dynamics, 39(13), 4610–4617.

Coura, J. R., & Castro, S. L. de. (2002). A Critical Review on Chagas Disease Chemotherapy. Memórias Do Instituto Oswaldo Cruz, 97(1), 3–24.

Das, A., Sarkar, S., Bhattacharyya, S., & Gantait, S. (2020). Biotechnological advancements in Catharanthus roseus (L.) G. Don. Applied Microbiology and Biotechnology, 104(11), 4811–4835.

Das, S., & Sharangi, A. B. (2017). Madagascar periwinkle (Catharanthus roseus L.): Diverse medicinal and therapeutic benefits to humankind. Journal of Pharmacognosy and Phytochemistry, 6(5), 1695–1701.

Engels, D., & Zhou, X.-N. (2020). Neglected tropical diseases: an effective global response to local poverty-related disease priorities. Infectious Diseases of Poverty, 9(1).

Fan, J., Fu, A., & Zhang, L. (2019). Progress in molecular docking. Quantitative Biology, 7(2), 83–89.

Fedi, A., Vitale, C., Ponschin, G., Ayehunie, S., Fato, M., & Scaglione, S. (2021). In vitro models replicating the human intestinal epithelium for absorption and metabolism studies: A systematic review. Journal of Controlled Release: Official Journal of the Controlled Release Society, 335, 247–268.

Ferreira, E. T., Santos, E. S. dos, Monteiro, J. S., Gomes, M. do S. M., Menezes, R. A. de O., & Souza, M. J. C. de. (2019). A utilização de plantas medicinais e fitoterápicos: uma revisão integrativa sobre a atuação do enfermeiro / The use of medicinal and phytotherapy plants: an integrational review on the nurses 'performance. Brazilian Journal of Health Review, 2(3), 1511–1523.

Filimonov, D. A., Lagunin, A. A., Gloriozova, T. A., Rudik, A. V., Druzhilovskii, D. S., Pogodin, P. V., & Poroikov, V. V. (2014). Prediction of the Biological Activity Spectra of Organic Compounds Using the Pass Online Web Resource. Chemistry of Heterocyclic Compounds, 50(3), 444–457.

Gasteiger, J., & Marsili, M. (1980). Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges. Tetrahedron, 36(22), 3219–3228.

Ghose, A. K., Viswanadhan, V. N., & Wendoloski, J. J. (1999). A Knowledge-Based Approach in Designing Combinatorial or Medicinal Chemistry Libraries for Drug Discovery. 1. A Qualitative and Quantitative Characterization of Known Drug Databases. Journal of Combinatorial Chemistry, 1(1), 55–68.

Goodsell, D. S., Morris, G. M., & Olson, A. J. (1996). Automated docking of flexible ligands: Applications of autodock. Journal of Molecular Recognition, 9(1), 1–5.

Goodsell, D. S. (2009). Computational Docking of Biomolecular Complexes with AutoDock. Cold Spring Harbor Protocols, 2009(5).

Guarner, J. (2019). Chagas disease as example of a reemerging parasite. Seminars in Diagnostic Pathology, 36(3), 164–169.

Guerra, T. M. (2019) Estudos de docking molecular de derivados da tiazolidina como potenciais inibidores da enzima cruzaína de Trypanosoma cruzi, 59p. Trabalho de Conclusão de Curso (Licenciatura em Química)-Universidade Federal Rural de Pernambuco – UFRPE, Serra Talhada.

Gupta, M., Sharma, R., & Kumar, A. (2018). Docking techniques in pharmacology: How much promising? Computational Biology and Chemistry, 76, 210–217.

Heijden, R., Jacobs, D., Snoeijer, W., Hallard, D., & Verpoorte, R. (2004). The Catharanthus Alkaloids:Pharmacognosy and Biotechnology. Current Medicinal Chemistry, 11(5), 607–628.

Honorato, N., da Silva, A., de Negreiros, C., Aguiar, L., Marliére, N. P., de Souza, R., Souza E Guimarães, R., Galvão, L., & da Câmara, A. (2021). Triatomine and Trypanosoma cruzi discrete typing units distribution in a semi-arid area of northeastern Brazil. Acta tropica, 220, 105950, 1-9.

Jia, C.-Y., Li, J.-Y., Hao, G.-F., & Yang, G.-F. (2019). A drug-likeness toolbox facilitates ADMET study in drug discovery. Drug Discovery Today.

Jiao, X., Jin, X., Ma, Y., Yang, Y., Li, J., Liang, L., Liu, R., & Li, Z. (2021). A comprehensive application: Molecular docking and network pharmacology for the prediction of bioactive constituents and elucidation of mechanisms of action in component-based Chinese medicine. Computational Biology and Chemistry, 90, 107402, 1-8.

Khaldan, A., Bouamrane, S., En-Nahli, F., El-Mernissi, R., El Khatabi, K., Hmamouchi, R., Maghat, H., Ajana, M. A., Sbai, A., Bouachrine, M., & Lakhlifi, T. (2021). Prediction of potential inhibitors of SARS-CoV-2 using 3D-QSAR, molecular docking modeling and ADMET properties. Heliyon, 7(3), e06603.

Kim, S., Chen, J., Cheng, T., Gindulyte, A., He, J., He, S., Li, Q., Shoemaker, B. A., Thiessen, P. A., Yu, B., Zaslavsky, L., Zhang, J., & Bolton, E. E. (2021). PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Research, 49(D1), 1388–1395.

Klein, M. D., Proaño, A., Noazin, S., Sciaudone, M., Gilman, R. H., & Bowman, N. M. (2021). Risk factors for vertical transmission of Chagas disease: A systematic review and meta-analysis. International journal of infectious diseases: IJID : official publication of the International Society for Infectious Diseases, 105, 357–373.

Laskowski, R. A., & Swindells, M. B. (2011). LigPlot+: multiple ligand-protein interaction diagrams for drug discovery. Journal of chemical information and modeling, 51(10), 2778–2786.

Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced drug delivery reviews, 46(1-3), 3–26.

Losada Galván, I., Alonso-Padilla, J., Cortés-Serra, N., Alonso-Vega, C., Gascón, J., & Pinazo, M. J. (2021). Benznidazole for the treatment of Chagas disease. Expert review of anti-infective therapy, 19(5), 547–556.

Ma, X. L., Chen, C., & Yang, J. (2005). Predictive model of blood-brain barrier penetration of organic compounds. Acta pharmacologica Sinica, 26(4), 500–512.

Matin, M. M., Uzzaman, M., Chowdhury, S. A., & Bhuiyan, M. (2020). In vitro antimicrobial, physicochemical, pharmacokinetics and molecular docking studies of benzoyl uridine esters against SARS-CoV-2 main protease. Journal of biomolecular structure & dynamics, 8(7), 1–13.

Monsalve-Lara, J., Lilioso, M., Valença-Barbosa, C., Thyssen, P. J., Miguel, D. C., Limeira, C., Gadelha, F. R., Fontes, F., Pires-Silva, D., Dornak, L. L., Lima, M. M., Donalisio, M. R., & Almeida, C. E. (2021). The risk of oral transmission in an area of a Chagas disease outbreak in the Brazilian northeast evaluated through entomological, socioeconomic and schooling indicators. Acta tropica, 215, 105803.

Morris, G. M., Huey, R., & Olson, A. J. (2008). Using AutoDock for Ligand‐Receptor Docking. Current Protocols in Bioinformatics, 24(1).

Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. E., Belew, R. K., & Olson, A. J. (1998). Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J. Comput. Chem, 19, 1639–1662.

Oprea T. I. (2000). Property distribution of drug-related chemical databases. Journal of computer-aided molecular design, 14(3), 251–264.

Pascolutti, M., & Quinn, R. J. (2014). Natural products as lead structures: chemical transformations to create lead-like libraries. Drug Discovery Today, 19(3), 215–221.

Pinzi, L., & Rastelli, G. (2019). Molecular Docking: Shifting Paradigms in Drug Discovery. International journal of molecular sciences, 20(18), 4331.

Potts, R. O., & Guy, R. H. (1992). Predicting skin permeability. Pharmaceutical research, 9(5), 663–669.

Ramos, R. M., Perez, J. M., Baptista, L. A., & de Amorim, H. L. (2012). Interaction of wild type, G68R and L125M isoforms of the arylamine-N-acetyltransferase from Mycobacterium tuberculosis with isoniazid: a computational study on a new possible mechanism of resistance. Journal of molecular modeling, 18(9), 4013–4024.

Rim, K.-T. (2020). In silico prediction of toxicity and its applications for chemicals at work. Toxicology and Environmental Health Sciences, 12(3), 191–202.

Sanner M. F. (1999). Python: a programming language for software integration and development. Journal of molecular graphics & modelling, 17(1), 57–61.

Smith, C. J., Perfetti, T. A., Berry, S. C., Brash, D. E., Bus, J., Calabrese, E., Clemens, R. A., Fowle, J., 3rd, Greim, H., MacGregor, J. T., Maronpot, R., Pressman, P., Zeiger, E., & Hayes, A. W. (2021). Bruce Nathan Ames - Paradigm shifts inside the cancer research revolution. Mutation research. Reviews in mutation research, 787, 108363.

Solis, F. J., & Wets, R. J.-B. . (1981). Minimization by Random Search Techniques. Mathematics of Operations Research, 6(1), 19–30.

Teague, S. J. , Davis, A. M. , And, P. , & Oprea, T. . (1999). The design of leadlike combinatorial libraries. Angewandte Chemie : International Edition, 38(24), 3743–3748.

Uspenskaya, E. V., Pleteneva, T. V., Kazimova, I. V., & Syroeshkin, A. V. (2021). Evaluation of Poorly Soluble Drugs' Dissolution Rate by Laser Scattering in Different Water Isotopologues. Molecules (Basel, Switzerland), 26(3), 601.

Vanderslott, S. (2019). Moving From Outsider to Insider Status Through Metrics: The Inclusion of “Neglected Tropical Diseases” Into the Sustainable Development Goals. Journal of Human Development and Capabilities, 20, 418 - 435.

Wadapurkar, R.M., Shilpa, M., Katti, A.K., & Sulochana, M.B. (2018). In silico drug design for Staphylococcus aureus and development of host-pathogen interaction network. Informatics in Medicine Unlocked, 10, 58-70.

Wang, B., Lu, Y., Wang, R., Liu, S., Hu, X., & Wang, H. (2020). Transport and metabolic profiling studies of amentoflavone in Caco-2 cells by UHPLC-ESI-MS/MS and UHPLC-ESI-Q-TOF-MS/MS. Journal of pharmaceutical and biomedical analysis, 189, 113441.

Williamson, E. J., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., Curtis, H. J., Mehrkar, A., Evans, D., Inglesby, P., Cockburn, J., McDonald, H. I., MacKenna, B., Tomlinson, L., Douglas, I. J., Rentsch, C. T., Mathur, R., Wong, A., Grieve, R., Harrison, D., … Goldacre, B. (2020). Factors associated with COVID-19-related death using OpenSAFELY. Nature, 584(7821), 430–436.

Yazdanian, M., Glynn, S. L., Wright, J. L., & Hawi, A. (1998). Correlating partitioning and caco-2 cell permeability of structurally diverse small molecular weight compounds. Pharmaceutical research, 15(9), 1490–1494.

Yee S. (1997). In vitro permeability across Caco-2 cells (colonic) can predict in vivo (small intestinal) absorption in man--fact or myth. Pharmaceutical research, 14(6), 763–766.

Yun, Y. E., Tornero-Velez, R., Purucker, S. T., Chang, D. T., & Edginton, A. N. (2021). Evaluation of Quantitative Structure Property Relationship Algorithms for Predicting Plasma Protein Binding in Humans. Computational toxicology (Amsterdam, Netherlands), 17, 100142.

Downloads

Publicado

04/04/2022

Como Citar

SOUZA, J. L.; LIMA, F. das C. A.; CRUZ, J. V. .; ALMEIDA, T. dos R. .; SILVA, C. B. B. da. Estudo in silico de alcalóides derivados da Catharantus roseus em sítio ativo do Trypanossoma cruzi via ancoragem molecular. Research, Society and Development, [S. l.], v. 11, n. 5, p. e23711528114, 2022. DOI: 10.33448/rsd-v11i5.28114. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/28114. Acesso em: 17 jul. 2024.

Edição

Seção

Ciências Exatas e da Terra