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Research Articles

Hypoglycemic and hepatoprotective effects in adult zebrafish (Danio rerio) of fisetinidol isolated from Bauhinia pentandra: In vivo and in silico assays

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Pages 2274-2288 | Received 07 Oct 2021, Accepted 08 Jan 2022, Published online: 22 Jan 2022

References

  • Ahangarpour, A., Sayahi, M., & Sayahi, M. (2019). The antidiabetic and antioxidant properties of some phenolic phytochemicals: A review study. Diabetes & Metabolic Syndrome, 13(1), 854–857. https://doi.org/10.1016/j.dsx.2018.11.051
  • Allouche, A. R. (2011). Gabedit—A graphical user interface for computational chemistry softwares. Journal of Computational Chemistry, 32(1), 174–182. https://doi.org/10.1002/jcc.21600
  • Arellano-Aguilar, O., Solis-Angeles, S., Serrano-García, L., Morales-Sierra, E., Mendez-Serrano, A., & Montero-Montoya, R. (2015). Use of the zebrafish embryo toxicity test for risk assessment purpose: Case study. Journal of Fisheriessciences. Com, 9(4), 052–062.
  • Arfken, G. B., Weber, H. J., & Harris, F. E. (2013). Mathematical preliminaries. In Mathematical methods for physicists (7th ed). Academic Press.
  • Baell, J. B., & Holloway, G. A. (2010). New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. Journal of Medicinal Chemistry, 53(7), 2719–2740. https://doi.org/10.1021/jm901137j
  • Becke, A. D. (1992). Density-functional thermochemistry. I. The effect of the exchange-only gradient correction. The Journal of Chemical Physics, 96(3), 2155–2160. https://doi.org/10.1063/1.462066
  • Biovia, D. S. (2016). Discovery studio modeling environment, release 2017. Dassault Systèmes.
  • Bussi, G., Donadio, D., & Parrinello, M. (2007). Canonical sampling through velocity rescaling. The Journal of Chemical Physics, 126(1), 014101. https://doi.org/10.1063/1.2408420
  • Capiotti, K. M., Antonioli, R., Kist, L. W., Bogo, M. R., Bonan, C. D., & Da Silva, R. S. (2014). Persistent impaired glucose metabolism in a zebrafish hyperglycemia model. Comparative Biochemistry and Physiology. Part B, Biochemistry & Molecular Biology, 171(1), 58–65. https://doi.org/10.1016/j.cbpb.2014.03.005
  • Csizmadia, P. (1999). MarvinSketch and MarvinView: Molecule applets for the World Wide Web. https://doi.org/10.3390/ecsoc-3-01775
  • da Silva, H. C., Pinto, F., das, C. L., de Sousa, A. F., Pessoa, O. D. L., Trevisan, M. T. S., & Santiago, G. M. P. (2021). Chemical constituents and acetylcholinesterase inhibitory activity from the stems of Bauhinia pentandra. Natural Product Research, 35(23), 5277–5281. https://doi.org/10.1080/14786419.2020.1752206
  • Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7, 42717. https://doi.org/10.1038/srep42717
  • de Oliveira Monteiro, A., de Carvalho, J. L., da Silva, H. C., do Nascimento, G. O., Silva, A. M. A., Trevisan, M. T. S., & Santiago, G. M. P. (2021). Bauhinia pulchella: Chemical constituents, antioxidant and alpha-glucosidase inhibitory activities. Natural Product Research, 36(11), 1–6. https://doi.org/10.1080/14786419.2021.1887176
  • de Sousa, L. M., de Carvalho, J. L., da Silva, H. C., Lemos, T. L. G., Arriaga, A. M. C., Braz-Filho, R., Militão, G. C. G., Silva, T. D. S., Ribeiro, P. R. V., & Santiago, G. M. P. (2016). New cytotoxic bibenzyl and other constituents from Bauhinia ungulata L. (Fabaceae). Chemistry & Biodiversity, 13(12), 1630–1635. https://doi.org/10.1002/cbdv.201600058
  • DeLano, W. L. (2020). The PyMOL molecular graphics system, version 2.3. Schrödinger LLC.
  • Diabetes, D. O. F. (2012). Diagnosis and classification of diabetes mellitus. Diabetes Care, 35(SUPPL. 1), S64–S71. https://doi.org/10.2337/dc12-s064
  • Ditchfield, R., Hehre, W. J., & Pople, J. A. (1971). Self-consistent molecular-orbital methods. IX. An extended Gaussian-type basis for molecular-orbital studies of organic molecules. The Journal of Chemical Physics, 54(2), 724–728. https://doi.org/10.1063/1.1674902
  • Dong, J., & Davis, A. P. (2021). Molecular recognition mediated by hydrogen bonding in aqueous media. Angewandte Chemie (International ed. in English), 60(15), 8035–8048. https://doi.org/10.1002/anie.202012315
  • Duong, T. H., Paramita Devi, A., Tran, N. M. A., Phan, H. V. T., Huynh, N. V., Sichaem, J., Tran, H. D., Alam, M., Nguyen, T. P., Nguyen, H. H., Chavasiri, W., & Nguyen, T. C. (2020). Synthesis, α-glucosidase inhibition, and molecular docking studies of novel N-substituted hydrazide derivatives of atranorin as antidiabetic agents. Bioorganic & Medicinal Chemistry Letters, 30(17), 127359. https://doi.org/10.1016/j.bmcl.2020.127359
  • Farag, M. A., Sakna, S. T., El-Fiky, N. M., Shabana, M. M., & Wessjohann, L. A. (2015). Phytochemical, antioxidant and antidiabetic evaluation of eight Bauhinia L. species from Egypt using UHPLC-PDA-qTOF-MS and chemometrics . Phytochemistry, 119, 41–50. https://doi.org/10.1016/j.phytochem.2015.09.004
  • Filho, V. C. (2009). Chemical composition and biological potential of plants from the genus Bauhinia. Phytotherapy Research, 23(10), 1347–1354. https://doi.org/10.1002/ptr.2756
  • Franco, R. R., Mota Alves, V. H., Ribeiro Zabisky, L. F., Justino, A. B., Martins, M. M., Saraiva, A. L., Goulart, L. R., & Espindola, F. S. (2020). Antidiabetic potential of Bauhinia forficata Link leaves: a non-cytotoxic source of lipase and glycoside hydrolases inhibitors and molecules with antioxidant and antiglycation properties. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 123, 109798. https://doi.org/10.1016/j.biopha.2019.109798
  • Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., Scalmani, G., Barone, V., Petersson, G. A., Nakatsuji, H., Li, X., Caricato, M., Marenich, A., Bloino, J., Janesko, B. G., Gomperts, R., Mennucci, B., Hratchian, H. P., & Ortiz, J. V., J. F. (2009). Gaussian 09., Gaussian, Inc.
  • Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., Scalmani, G., Barone, V., & Petersson, G. A. (2016). Gaussian 16, Rev. C.01. Gaussian, Inc.
  • Garcia, G. R., Noyes, P. D., & Tanguay, R. L. (2016). Advancements in zebrafish applications for 21st century toxicology. Pharmacology & Therapeutics, 161, 11–21. https://doi.org/10.1016/j.pharmthera.2016.03.009
  • Ghorbani, A. (2017). Mechanisms of antidiabetic effects of flavonoid rutin. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie, 96, 305–312. https://doi.org/10.1016/j.biopha.2017.10.001
  • Góis, R. W. S., Sousa, L. M., de, Silva, H. C., da, Silva, F. E. F., da, Pimenta, A. T. A., Lima, M. A. S., Arriaga, A. M. C., Lemos, T. L. G., Braz-Filho, R., Militão, G. C. G., Silva, P. B. N., da, Gonçalves, F. J. T., & Santiago, G. M. P. (2017). Chemical constituents from Bauhinia acuruana and their cytotoxicity. Revista Brasileira de Farmacognosia, 27(6), 711–715. https://doi.org/10.1016/j.bjp.2017.09.002
  • Hago, S., Mahrous, E. A., Moawad, M., Abdel-Wahab, S., & Abdel-Sattar, E. (2021). Evaluation of antidiabetic activity of Morus nigra L. and Bauhinia variegata L. leaves as Egyptian remedies used for the treatment of diabetes. Natural Product Research, 35(5), 829–835. https://doi.org/10.1080/14786419.2019.1601094
  • Hanwell, M. D., Curtis, D. E., Lonie, D. C., Vandermeersch, T., Zurek, E., & Hutchison, G. R. (2012). Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics, 4(1), 17. https://doi.org/10.1186/1758-2946-4-17[PMC]
  • Huey, R., Morris, G. M., & Forli, S. (2012). Using AutoDock 4 and AutoDock vina with AutoDockTools: A tutorial. autodock.scripps.edu
  • Ikarashi, N., Toda, T., Okaniwa, T., Ito, K., Ochiai, W., & Sugiyama, K. (2011). Anti-obesity and anti-diabetic effects of acacia polyphenol in obese diabetic KKAy mice fed high-fat diet. Evidence-Based Complementary and Alternative Medicine: eCAM, 2011, 952031. https://doi.org/10.1093/ecam/nep241
  • Imberty, A., Hardman, K. D., Carver, J. P., & Perez, S. (1991). Molecular modelling of protein-carbohydrate interactions. Docking of monosaccharides in the binding site of concanavalin A. Glycobiology, 1(6), 631–642. https://doi.org/10.1093/glycob/1.6.631
  • Jörgens, K., Hillebrands, J.-L., Hammes, H.-P., & Kroll, J. (2012). Zebrafish: A model for understanding diabetic complications. Experimental and Clinical Endocrinology & Diabetes: Official Journal, German Society of Endocrinology [and] German Diabetes Association, 120(4), 186–187. https://doi.org/10.1055/s-0032-1304565
  • Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2), 926–935. https://doi.org/10.1063/1.445869
  • Kadela-Tomanek, M., Jastrzębska, M., Marciniec, K., Chrobak, E., Bębenek, E., & Boryczka, S. (2021). Lipophilicity, pharmacokinetic properties, and molecular docking study on SARS-CoV-2 target for betulin triazole derivatives with attached 1,4-quinone. Pharmaceutics, 13(6), 781. https://doi.org/10.3390/pharmaceutics13060781
  • Kashiwada, M., Nakaishi, S., Usuda, A., Miyahara, Y., Katsumoto, K., Katsura, K., Terakado, I., Jindo, M., Nakajima, S., Ogawa, S., Sugiyama, K., & Ochiai, W. (2021). Analysis of anti-obesity and anti-diabetic effects of acacia bark-derived proanthocyanidins in type 2 diabetes model KKAy mice. Journal of Natural Medicines, 75(4), 893–906. https://doi.org/10.1007/s11418-021-01537-7
  • Lee, C., Yang, W., & Parr, R. G. (1988). Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Physical Review. B, Condensed Matter, 37(2), 785–789. https://doi.org/10.1103/physrevb.37.785
  • Lipinski, C. A. (2004). Lead- and drug-like compounds: The rule-of-five revolution. Drug Discovery Today. Technologies, 1(4), 337–341. https://doi.org/10.1016/j.ddtec.2004.11.007
  • Lipinski, C. A. (2016). Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions. Advanced Drug Delivery Reviews, 101, 34–41. https://doi.org/10.1016/j.addr.2016.04.029
  • Loetchutinat, C., Kothan, S., Dechsupa, S., Meesungnoen, J., Jay-Gerin, J. P., & Mankhetkorn, S. (2005). Spectrofluorometric determination of intracellular levels of reactive oxygen species in drug-sensitive and drug-resistant cancer cells using the 2′,7′-dichlorofluorescein diacetate assay. Radiation Physics and Chemistry, 72(2-3), 323–331. https://doi.org/10.1016/j.radphyschem.2004.06.011
  • Mackerell, A. D., Banavali, N., & Foloppe, N. (2000). Development and Current Status of the CHARMM force field for nucleic acids. Biopolymers, 56(4), 257–265. https://doi.org/10.1002/1097-0282(2000)56:4<257::AID-BIP10029>3.0.CO;2-W
  • Magalhães, F. E. A., de Sousa, C. Á. P. B., Santos, S. A. A. R., Menezes, R. B., Batista, F. L. A., Abreu, Â. O., de Oliveira, M. V., Moura, L. F. W. G., Raposo, R., da, S., & Campos, A. R. (2017). Adult zebrafish (Danio rerio): An alternative behavioral model of formalin-induced nociception. Zebrafish, 14(5), 422–429. https://doi.org/10.1089/zeb.2017.1436
  • Marinho, E. M., Batista de Andrade Neto, J., Silva, J., Rocha da Silva, C., Cavalcanti, B. C., Marinho, E. S., & Nobre Júnior, H. V. (2020). Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease. Microbial Pathogenesis, 148, 104365 https://doi.org/10.1016/j.micpath.2020.104365
  • Maurya, A., Mohan, S., & Verma, S. C. (2021). Antidiabetic potential of naturally occurring sesquiterpenes: A review. Current Topics in Medicinal Chemistry, 21(10), 851–862. https://doi.org/10.2174/1568026621666210305102500
  • Morris, G. M., Huey R Fau - Lindstrom, W., Lindstrom W Fau - Sanner, M. F., Sanner Mf Fau - Belew, R. K., Belew Rk Fau - Goodsell, D. S., Goodsell Ds Fau - Olson, A. J., Olson, A. J., & Chem, J. C. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
  • Nguyen, D. D., Xiao, T., Wang, M., & Wei, G. W. (2017). Rigidity strengthening: A mechanism for protein-ligand binding. Journal of Chemical Information and Modeling, 57(7), 1715–1721. https://doi.org/10.1021/acs.jcim.7b00226
  • Nosé, S., & Klein, M. L. (1983). Constant pressure molecular dynamics for molecular systems. Molecular Physics, 50(5), 1055–1076. https://doi.org/10.1080/00268978300102851
  • OECD. (1992). OECD guidelines for the testing of chemicals (p. No.203). https://doi.org/10.1787/9789264069961-en
  • Ogurtsova, K., da Rocha Fernandes, J. D., Huang, Y., Linnenkamp, U., Guariguata, L., Cho, N. H., Cavan, D., Shaw, J. E., & Makaroff, L. E. (2017). IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Research and Clinical Practice, 128, 40–50. https://doi.org/10.1016/j.diabres.2017.03.024
  • Oyelaja-Akinsipo, O. B., Dare, E. O., & Katare, D. P. (2020). Protective role of diosgenin against hyperglycaemia-mediated cerebral ischemic brain injury in zebrafish model of type II diabetes mellitus. Heliyon, 6(1), e03296. https://doi.org/10.1016/j.heliyon.2020.e03296
  • Özkaya, D., Naziroğlu, M., Armağan, A., Demirel, A., Köroglu, B. K., Çolakoğlu, N., Kükner, A., & Sönmez, T. T. (2011). Dietary vitamin C and E modulates oxidative stress induced-kidney and lens injury in diabetic aged male rats through modulating glucose homeostasis and antioxidant systems. Cell Biochemistry and Function, 29(4), 287–293. https://doi.org/10.1002/cbf.1749
  • Pandey, K. B., & Rizvi, S. I. (2009). Plant polyphenols as dietary antioxidants in human health and disease. Oxidative Medicine and Cellular Longevity, 2(5), 270–278. https://doi.org/10.4161/oxim.2.5.9498
  • Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera-a visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084
  • Ranjan, S., & Sharma, P. K. (2020). Study of learning and memory in type 2 diabetic model of zebrafish (Danio rerio). Endocrine and Metabolic Science, 1(3-4), 100058. https://doi.org/10.1016/j.endmts.2020.100058
  • Ren, L., Qin, X., Cao, X., Wang, L., Bai, F., Bai, G., & Shen, Y. (2011). Structural insight into substrate specificity of human intestinal maltase-glucoamylase. Protein & Cell, 2(10), 827–836. https://doi.org/10.1007/s13238-011-1105-3
  • Salentin, S., Schreiber, S., Haupt, V. J., Adasme, M. F., & Schroeder, M. (2015). PLIP: Fully automated protein-ligand interaction profiler. Nucleic Acids Research, 43(W1), W443–W447. https://doi.org/10.1093/nar/gkv315
  • Shirali, S., Zahra Bathaie, S., & Nakhjavani, M. (2013). Effect of crocin on the insulin resistance and lipid profile of streptozotocin-induced diabetic rats. Phytotherapy Research: PTR, 27(7), 1042–1047. https://doi.org/10.1002/ptr.4836
  • Shityakov, S., & Foerster, C. (2014). In silico predictive model to determine vector-mediated transport properties for the blood-brain barrier choline transporter. Advances and Applications in Bioinformatics and Chemistry, 2014(7), 23–36. https://doi.org/10.2147/AABC.S63749
  • Steed, J. W., Atwood, J. L., & Gale, P. A. (2012). Definition and emergence of supramolecular chemistry. In Supramolecular chemistry. Wiley Online Library. https://doi.org/10.1002/9780470661345.smc002
  • Tripathi, A. K., Gupta, P. S., & Singh, S. K. (2019). Antidiabetic, anti-hyperlipidemic and antioxidant activities of Bauhinia variegata flower extract. Biocatalysis and Agricultural Biotechnology, 19, 101142. https://doi.org/10.1016/j.bcab.2019.101142
  • Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
  • Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., & Berendsen, H. J. C. (2005). GROMACS: Fast, flexible, and free. Journal of Computational Chemistry, 26(16), 1701–1718. https://doi.org/10.1002/jcc.20291
  • Van Gunsteren, W. F., & Berendsen, H. J. C. (1988). A Leap-frog algorithm for stochastic dynamics. Molecular Simulation, 1(3), 173–185. https://doi.org/10.1080/08927028808080941
  • Veber, D. F., Johnson, S. R., Cheng, H. Y., Smith, B. R., Ward, K. W., & Kopple, K. D. (2002). Molecular properties that influence the oral bioavailability of drug candidates. Journal of Medicinal Chemistry, 45(12), 2615–2623. https://doi.org/10.1021/jm020017n
  • Vinayagam, R., & Xu, B. (2015). Antidiabetic properties of dietary flavonoids: A cellular mechanism review. Nutrition & Metabolism, 12, 60. https://doi.org/10.1186/s12986-015-0057-7
  • Wager, T. T., Chandrasekaran, R. Y., Hou, X., Troutman, M. D., Verhoest, P. R., Villalobos, A., & Will, Y. (2010a). Defining desirable central nervous system drug space through the alignment of molecular properties, in vitro ADME, and safety attributes. ACS Chemical Neuroscience, 1(6), 420–434. https://doi.org/10.1021/cn100007x
  • Wager, T. T., Hou, X., Verhoest, P. R., & Villalobos, A. (2010b). Moving beyond rules: The development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chemical Neuroscience, 1(6), 435–449. https://doi.org/10.1021/cn100008c
  • Wager, T. T., Hou, X., Verhoest, P. R., & Villalobos, A. (2016). Central nervous system multiparameter optimization desirability: Application in drug discovery. ACS Chemical Neuroscience, 7(6), 767–775. https://doi.org/10.1021/acschemneuro.6b00029
  • Yan, J., Zhang, G., Pan, J., & Wang, Y. (2014). α-Glucosidase inhibition by luteolin: Kinetics, interaction and molecular docking. International Journal of Biological Macromolecules, 64, 213–223. https://doi.org/10.1016/j.ijbiomac.2013.12.007
  • Yin, Z., Zhang, W., Feng, F., Zhang, Y., & Kang, W. (2014). α-Glucosidase inhibitors isolated from medicinal plants. Food Science and Human Wellness, 3(3–4), 136–174. https://doi.org/10.1016/j.fshw.2014.11.003
  • Yusuf, D., Davis, A. M., Kleywegt, G. J., & Schmitt, S. (2008). An alternative method for the evaluation of docking performance: RSR vs RMSD. Journal of Chemical Information and Modeling, 48(7), 1411–1422. https://doi.org/10.1021/ci800084x
  • Zhu, J., Chen, C., Zhang, B., & Huang, Q. (2020). The inhibitory effects of flavonoids on α-amylase and α-glucosidase. Critical Reviews in Food Science and Nutrition, 60(4), 695–708. https://doi.org/10.1080/10408398.2018.1548428

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