In silico evaluation of twenty-five amino derivatives as potential nitric oxide synthase inhibitors

Authors

  • Regina Cauich-Carrillo Universidad Vizcaya de las Americas, Av. Boulevard Bahia, 422, Col. Zona de Granjas, Chetumal Quintana Roo, C.P. 77079, Mexico https://orcid.org/0000-0002-7166-5048
  • Marcela Rosas Nexticapa Nutrition Laboratory, Faculty of Nutrition, University of Veracruz, Medicos y s/n Odontologos 910210, Unidad del Bosque, Xalapa, Mexico https://orcid.org/0000-0001-7119-4728
  • Magdalena Alvarez-Ramirez Nutrition Laboratory, Faculty of Nutrition, University of Veracruz, Medicos y s/n Odontologos 910210, Unidad del Bosque, Xalapa, Mexico https://orcid.org/0000-0003-0046-4342
  • Maria Virginia Mateu-Armad Nutrition Laboratory, Faculty of Nutrition, University of Veracruz, Medicos y s/n Odontologos 910210, Unidad del Bosque, Xalapa, Mexico https://orcid.org/0000-0003-3283-0001
  • Emilio Aguilar-Sanchez Nutrition Laboratory, Faculty of Nutrition, University of Veracruz, Medicos y s/n Odontologos 910210, Unidad del Bosque, Xalapa, Mexico https://orcid.org/0009-0003-9873-7253
  • Lauro Figueroa-Valverde Laboratory of Pharmaco-Chemistry, Faculty of Chemical Biological Sciences, University Autonomous of Campeche, Av. Agustín Melgar s/n, Col Buenavista C.P. 24039, Campeche, Camp., México https://orcid.org/0000-0001-8056-9069

DOI:

https://doi.org/10.14295/bjs.v4i8.751

Keywords:

amino derivatives, nitric oxide synthase, cancer

Abstract

There are studies indicating that nitric oxide synthase can be involved in cancer cell growth. It is important to mention that some inhibitors of nitric oxide synthase can produce changes in cancer cell growth. However, there is little information on the interaction of some amino derivatives with nitric oxide synthase surface.  The aim of this research was to determine the theoretical interaction of amino derivatives (compounds 1-25) with nitric oxide synthase using the 4d1o protein as a tool. Besides, L-NAME, ONO1714, and N-(3-(aminomethyl)benzyl)acetamidine drugs were used as controls in the DockingServer program. The results showed differences in the number of aminoacid residues and energy levels involved in the interaction of amino derivatives with the 4d1o protein surface compared with the controls. Furthermore, the inhibition constants for amino derivatives 4, 15, 20, 24, and 25 were lower compared to L-NAME and ONO1714 drugs. In conclusion, these theoretical results indicate that compounds 4, 15, 20, 24, and 25 have a higher affinity for the 4d1o protein surface. This data indicates that amino derivatives 4, 15, 20, 24, and 25 can exert changes in the biological activity of nitric oxide synthase. This phenomenon could translate into a decrease in cancer cell growth; however, to validate this hypothesis, it is necessary to perform different experiments in a biological model.

References

Aminian, A., Wilson, R., Al-Kurd, A., Tu, C., Milinovich, A., & Kroh, M. (2022). Association of bariatric surgery with cancer risk and mortality in adults with obesity. Journal of American Medical Asocciation, 327(24), 2423-33. https://doi.org/10.1001/jama.2022.9009

Askerova, U. F. (2023). Prediction of acute toxicity for (Z)-3-(2-phenylhydrazinylidene) benzofuran-2 (3H)-one and its derivatives for rats using GUSAR program. New Materials, Compounds and Applications, 7(1), 50-56.

Bakchi, B., Krishna, A. D., Sreecharan, E., Ganesh, V. B. J., Niharika, M., Maharshi, S., & Shaik, A. B. (2022). An overview on applications of SwissADME web tool in the design and development of anticancer, antitubercular and antimicrobial agents: a medicinal chemist's perspective. Journal of Molecular Structure, 1259, 132712. https://doi.org/10.1016/j.molstruc.2022.132712

Banerjee, P., Eckert, A. O., Schrey, A. K., & Preissner, R. (2018). ProTox-II: a webserver for the prediction of toxicity of chemicals. Nucleic acids research, 46(W1), W257-W263. https://doi.org/10.1093/nar/gky318

Bikadi, Z., Hazai, E. (2009). Application of the PM6 semi-empirical method to modeling proteins enhances docking accuracy of AutoDock. Journal of Cheminformatics, 1, 15.

Bugnon, M., Röhrig, U. F., Goullieux, M., Perez, M. A., Daina, A., Michielin, O., & Zoete, V. (2024). SwissDock 2024: major enhancements for small-molecule docking with Attracting Cavities and AutoDock Vina. Nucleic acids research, 52(W1), W324-W332. https://doi.org/10.1093/nar/gkae300

Cahlin, C., Gelin, J., Delbro, D., Lönnroth, C., Doi, C., & Lundholm, K. (2000). Effect of cyclooxygenase and nitric oxide synthase inhibitors on tumor growth in mouse tumor models with and without cancer cachexia related to prostanoids. Cancer Research, 60(6), 1742-1749.

Chiarelli, L. R., Mori, M., Barlocco, D., Beretta, G., Gelain, A., Pini, E., & Meneghetti, F. (2018). Discovery and development of novel salicylate synthase (MbtI) furanic inhibitors as antitubercular agents. European Journal of Medicinal Chemistry, 155, 754-763. https://doi.org/10.1016/j.ejmech.2018.06.033

Figueroa-Valverde, L., Rosas-Nexticapa, M., Alvarez-Ramirez, M., Aguilar-Sanchez, E., Mateu-Armad, M. V., & Bonilla-Zavaleta, E. (2024). Interaction of some chalcone derivatives with calcium channels using a theoretical model. Brazilian Journal of Science, 3(11), 1-15. https://doi.org/10.14295/bjs.v3i11.658

Fujimoto, H., Ando, Y., Yamashita, T., Terazaki, H., Tanaka, Y., Sasaki, J., & Ando, M. (1997). Nitric oxide synthase activity in human lung cancer. Japanese Journal of Cancer Research, 88(12), 1190-1198. https://doi.org/10.1111/j.1349-7006.1997.tb00348.x

Gao, Y., Zhou, S., Xu, Y., Sheng, S., Qian, S. Y., & Huo, X. (2019). Nitric oxide synthase inhibitors 1400W and L-NIO inhibit angiogenesis pathway of colorectal cancer. Nitric Oxide, 83, 33-39. https://doi.org/10.1016/j.niox.2018.12.008

Halgren. (1998). Merck molecular force field. I. Basis, form, scope, parametrization, and performance of MMFF94. Journal of Computational Chemistry, 17(5-6), 490-519.

Hazai, E., Kovács, S., Demkó, L., & Bikádi, Z. (2009). DockingServer: molecular docking calculations online. Acta pharmaceutica Hungarica, 79(1), 17-21.

Hecht, S., & Hatsukami, D. (2022). Smokeless tobacco and cigarette smoking: chemical mechanisms and cancer prevention. Nature Reviews Cancer, 22(3), 143-155.

Huang, F., & Yu, S. (2018). Esophageal cancer: risk factors, genetic association, and treatment. Asian Journal Surgery, 41(3), 210-215. https://doi.org/10.1016/j.asjsur.2016.10.005

Im, P., Yang, L., Kartsonaki, C., Chen, Y., Guo, Y., & Du, H. (2022). Alcohol metabolism genes and risks of site‐specific cancers in Chinese adults: An 11‐year prospective study. International Journal of Cancer 150(10),1627-39. https://doi.org/10.1002/ijc.33917

Kampa, M., Hatzoglou, A., Notas, G., Niniraki, M., Kouroumalis, E., & Castanas, E. (2001). Opioids are non-competitive inhibitors of nitric oxide synthase in T47D human breast cancer cells. Cell Death & Differentiation, 8(9), 943-952.

Khrapova, M. V., Khrapov, S. E., Chechushkov, A. V., Kozhin, P. M., Romakh, L. P., Serykh, A. E., & Menshchikova, E. B. (2023). The toxicity of a new monophenolic synthetic inducer of Keap1/Nrf2/ARE redox-sensitive signaling system in vitro and in vivo. Cell and Tissue Biology, 17(3), 299-305.

Kong, R., Yang, G., Xue, R., Liu, M., Wang, F., Hu, J., & Chang, S. (2020). COVID-19 Docking Server: a meta server for docking small molecules, peptides and antibodies against potential targets of COVID-19. Bioinformatics, 36(20), 5109-5111. https://doi.org/10.1093/bioinformatics/btaa645

Krishnamoorthy, P. K., Balaraman, A. D., Priyadharshini, A., Shanmugam, D. A., Muthukumaran, S., Kesavamurthy, A., & Revanasiddappa, P. D. (2023). Molecular docking and simulation binding analysis of boeravinone B with caspase-3 and EGFR of hepatocellular carcinoma. Letters in Drug Design & Discovery, 20(2), 238-244. https://doi.org/10.2174/1570180819666220805163725

Lazarus, E., & Bays, H. (2022). Cancer and obesity: an obesity medicine association (OMA) clinical practice statement (CPS). Obesity Pill, 3,100026. https://doi.org/10.1016/j.obpill.2022.100026

Lazarus, E., & Bays, H. (2022). Cancer and obesity: an obesity medicine association (OMA) clinical practice statement (CPS) 2022. Obesity Pillarys, 3, 100026. https://doi.org/10.1016/j.obpill.2022.100026

Lee, A., Yang, X., Tyrer, J., Gentry-Maharaj, A., Ryan, A., Mavadda, N., & Antoniou, A. Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors. Journal of Medical Genetics, 2022; 59(7), 632-643.

Liu, C. Y., Wang, C. H., Chen, T. C., Lin, H. C., Yu, C. T., & Kuo, H. P. (1998). Increased level of exhaled nitric oxide and up-regulation of inducible nitric oxide synthase in patients with primary lung cancer. British Journal of Cancer, 78(4), 534-541.

Lohachova, K. O., Sviatenko, A. S., Kyrychenko, A., Ivanov, V. V., Langer, T., Kovalenko, S. M., & Kalugin, O. N. (2024). Computer-aided drug design of novel nirmatrelvir analogs inhibiting main protease of Coronavirus SARS-CoV-2. Journal of Applied Pharmaceutical Science, 14(5), 232-239. https://dx.doi.org/10.7324/JAPS.2024.158114

Loibl, S., Buck, A., Strank, C., von Minckwitz, G., Roller, M., Sinn, H. P., & Kaufmann, M. (2005). The role of early expression of inducible nitric oxide synthase in human breast cancer. European Journal of Cancer, 41(2), 265-271. https://doi.org/10.1016/j.ejca.2004.07.010

Loibl, S., Von Minckwitz, G., Weber, S., Sinn, H. P., Schini‐Kerth, V. B., Lobysheva, I., & Kaufmann, M. (2002). Expression of endothelial and inducible nitric oxide synthase in benign and malignant lesions of the breast and measurement of nitric oxide using electron paramagnetic resonance spectroscopy. Cancer, 95(6), 1191-1198. https://doi.org/10.1002/cncr.10817

Minhas, R., Bansal, Y., & Bansal, G. (2020). Inducible nitric oxide synthase inhibitors: A comprehensive update. Medicinal Research Reviews, 40(3), 823-855. https://doi.org/10.1002/med.21636

Morris, M., Goodsell, D., Hallyday, R., Huey, R., hart, W., Belew, R., & Olson, A. (1998). Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry, 19(14), 1639-1662. https://doi.org/10.1002/(SICI)1096-987X(19981115)19:14%3C1639:AID-JCC 10%3E3.0.CO;2-B

O’Sullivan, D., Sutherland, R., Town, S., Chow, K., Fan, J., Forbes, N., & Brenner, D. (2022). Risk factors for early-onset colorectal cancer: a systematic review and meta-analysis. Clinical Gastroenterology and Hepatology, 20(6), 1229-1240. https://doi.org/10.1016/j.cgh.2021.01.037

Phua, Z., MacInnis, R., % Jayasekara, H. (2022). Cigarette smoking and risk of second primary cancer: a systematic review and meta-analysis. Cancer Epidemiology, 78, 102160. https://doi.org/10.1016/j.canep.2022.102160

Qing, X., Yin Lee, X., De Raeymaeker, J., RH Tame, J., YJ Zhang, K., De Maeyer, M., & RD Voet, A. (2014). Pharmacophore modeling: advances, limitations, and current utility in drug discovery. Journal of Receptor, Ligand and Channel Research, 81-92.

Saad, M., Mokrab, Y., Halabi, N., Shan, J, Razali R, Kunji K, & Chouchane L. Genetic predisposition to cancer across people of different ancestries in Qatar: A population-based, cohort study. The Lancet Oncology, 2022; 23(3), 341-352.

Schaller, D., Šribar, D., Noonan, T., Deng, L., Nguyen, T. N., Pach, S., & Wolber, G. (2020). Next generation 3D pharmacophore modeling. Wiley Interdisciplinary Reviews: Computational Molecular Science, 10(4), e1468. https://doi.org/10.1002/wcms.1468

Siegel, R., Miller, K., Fuchs, H., Jemal, A. (2022). Cancer statistics. CA Cancer Journal for Clinicians, 72(1), 7-33. https://doi.org/10.3322/caac.21708

Solis, F., & Wets, R. (1981). Minimization by Random Search Techniques. Mathematics of Operations Research, 6 (1), 19-30. https://doi.org/10.1287/moor.6.1.19

Sushko, I., Salmina, E., Potemkin, V. A., Poda, G., & Tetko, I. V. (2012). ToxAlerts: a web server of structural alerts for toxic chemicals and compounds with potential adverse reactions. Journal of Chemical Information and Modeling, 52(8), 2310-2316. https://doi.org/10.1021/ci300245q

Swan, J., Szabó, Z., Peters, J., Kummu, O., Kemppi, A., Rahtu-Korpela, L, Magga, J. (2024). Inhibition of activin receptor 2 signalling ameliorates metabolic dysfunction–associated steatotic liver disease in western diet/L-NAME induced cardiometabolic disease. Biomedicine & Pharmacotherapy, 175, 116683. https://doi.org/10.1016/j.biopha.2024.116683

Tu, K., Ma, T., Zhou, R., Xu, L., Fang, Y., & Zhang, C. (2022). Association between Dietary Fatty Acid Patterns and Colorectal Cancer Risk: A Large-Scale Case-Control Study in China. Nutrients, 14(20), 4375. https://doi.org/10.3390/nu14204375

Verdonk, M. L., Cole, J. C., Hartshorn, M. J., Murray, C. W., & Taylor, R. D. (2003). Improved protein–ligand docking using GOLD. Proteins: Structure, Function, and Bioinformatics, 52(4), 609-623. https://doi.org/10.1002/prot.10465

Wan, Y., Wu, K., Wang, L., Yin, K., & Song, M. (2022). Dietary fat and fatty acids in relation to risk of colorectal cancer. European Journal of Nutrition, 61(4), 1863-1873.

Wolber, G., & Kosara, R. (2006). Pharmacophores from macromolecular complexes with LigandScout. Pharmacophores and pharmacophore searches, 32, 131-150. https://doi.org/ 10.1002/3527609164

Wolber, G., & Langer, T. (2005). LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. Journal of chemical information and modeling, 45(1), 160-169. https://doi.org/10.1021/ci049885e

Xia, C., Dong, X., Li, H., Cao, M., Sun, D., He, S., & Chen, W. (2022). Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chinese Medical Journal, 135(5), 584-590.

Yagihashi, N., Kasajima, H., Sugai, S., Matsumoto, K., Ebina, Y., Morita, T., & Yagihashi, S. (2000). Increased in situ expression of nitric oxide synthase in human colorectal cancer. Virchows Archiv, 436, 109-114.

Yang, S. Y. (2010). Pharmacophore modeling and applications in drug discovery: challenges and recent advances. Drug Discovery Today, 15(11-12), 444-450. https://doi.org/10.1016/j.drudis.2010.03.013

Yoo, J., Han, K., Shin, D., Kim, D., Kim, B., & Chun, S. (2022). Association Between Changes in Alcohol Consumption and Cancer Risk. Journal of American Medical Association, 5(8), e2228544. https://doi.org/10.1001/jamanetworkopen.2022.28544

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Published

2025-06-19

How to Cite

Cauich-Carrillo, R., Rosas Nexticapa, M., Alvarez-Ramirez, M., Mateu-Armad, M. V., Aguilar-Sanchez, E., & Figueroa-Valverde, L. (2025). In silico evaluation of twenty-five amino derivatives as potential nitric oxide synthase inhibitors. Brazilian Journal of Science, 4(8), 17–34. https://doi.org/10.14295/bjs.v4i8.751