Article Sidebar

Submitted
Aug 17, 2022
Accepted
Aug 22, 2022
Published
Dec 30, 2022
Download
pdf
Statistic
Read Counter : 380 Download : 173

Downloads

Download data is not yet available.

Main Article Content

Abstract

This study was conducted to analyze the quantitative relationship between structure and net atomic charge modeling activity of 21 5-aminopyrazole derivatives as antioxidants. This study aims to determine the value of the net atomic charge and obtain the best HKSA equation. The method used in this study is the semi-empirical method of Austin Model 1 with geometry optimization. The selection of the best equation model is done by statistical analysis using the method of correlation analysis and multiple regression with Backward to the calculated descriptor data. From the results of the study, it was found that model 1 as the HKSA equation model was chosen with the equation Log IC50 = Log IC50 = 1.648+(0.914*qN1)-(3.662*qN2)-(1.99*qC3)+( 0.004*qC4)+(1.052* qC5 )+(1.226*qN6) where n = 6 ; R = 0.724 ; R2 = 0.524 ; SE = 0.1462 ; Sig = 0.068 ; PRESS = 0.2994. This study shows that atomic charge plays an important role in enhancing antioxidant activity.

Keywords

Free radicals, QSAR, antioxidant, AM1, statistic analysis

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
1.
Toni NPD, Azra F, Maahury MF. Modeling the Relationship of Net Atomic Charge with the Activity of 5-Aminopyrazole Derivative Compounds as Antioxidants with AM1 Method. EKSAKTA [Internet]. 2022Dec.30 [cited 2024Apr.27];23(04):242-54. Available from: https://eksakta.ppj.unp.ac.id/index.php/eksakta/article/view/334

References

  1. S. Di Meo and P. Venditti. (2020). Evolution of the Knowledge of Free Radicals and Other Oxidants. Oxidative Medicine and Cellular Longevity, vol. 2020. Hindawi Limited.
  2. Tsuneda, T., Sumitomo, H., Hasebe, M., Tsutsumi, T., & Taketsugu, T. (2022). Reactive orbital energy theory serving a theoretical foundation for the electronic theory of organic chemistry. Journal of Computational Chemistry.
  3. Singh, M., Nguyen, T. T., Balamurugan, J., Kim, N. H., & Lee, J. H. (2022). Rational manipulation of 3D hierarchical oxygenated nickel tungsten selenide nanosheet as the efficient bifunctional electrocatalyst for overall water splitting. Chemical Engineering Journal, 430, 132888.
  4. Z. Rui and J. Liu. (2020). Understanding of free radical scavengers used in highly durable proton exchange membranes. Prog. Nat. Sci. Mater. Int., vol. 30, no. 6, pp. 732–742.
  5. Li, W., Li, B., Wu, B., Tian, B., Chen, X., Wang, C., ... & Peng, J. (2022). Free-Radical Cascade Generated by AIPH/Fe3O4-Coloaded Nanoparticles Enhances MRI-Guided Chemo/Thermodynamic Hypoxic Tumor Therapy. ACS Applied Materials & Interfaces, 14(26), 29563-29576.
  6. H. Y. Leong, C. W. Ooi, C. L. Law, A. L. Julkifle, T. C. Ling, and P. L. Show. (2018). Application of liquid biphasic flotation for betacyanins extraction from peel and flesh of Hylocereus polyrhizus and antioxidant activity evaluation. Sep. Purif. Technol., vol. 201, pp. 156–166.
  7. Cao, G., Yang, S., Cao, J., Tan, Z., Wu, L., Dong, F., ... & Zhang, F. (2022). The role of oxidative stress in intervertebral disc degeneration. Oxidative Medicine and Cellular Longevity, 2022.
  8. Zhang, Y., Zhang, J., Wang, J., Chen, H., Ouyang, L., & Wang, Y. (2022). Targeting GRK2 and GRK5 for treating chronic degenerative diseases: Advances and future perspectives. European Journal of Medicinal Chemistry, 114668.
  9. Datta, S., Cano, M., Satyanarayana, G., Liu, T., Wang, L., Wang, J., ... & Handa, J. T. (2022). Mitophagy initiates retrograde mitochondrial-nuclear signaling to guide retinal pigment cell heterogeneity. Autophagy, 1-18.
  10. V. Fasiku (Oluwaseun), C. A. Omolo, and T. Govender. (2019). Free radical-releasing systems for targeting biofilms. J. Control. Release, vol. 322, pp. 248–273.
  11. Hu, Y., Zhao, G., Yin, F., Liu, Z., Wang, J., Qin, L., ... & Zhu, B. (2022). Effects of roasting temperature and time on aldehyde formation derived from lipid oxidation in scallop (Patinopecten yessoensis) and the deterrent effect by antioxidants of bamboo leaves. Food Chemistry, 369, 130936.
  12. A. Fekri, E. M. Keshk, A. G. M. Khalil, and I. Taha. (2021). Synthesis of novel antioxidant and antitumor 5-aminopyrazole derivatives, 2D/3D QSAR, and molecular docking. Mol. Divers., no. 0123456789.
  13. Salem, I. M., Salem, I. M., El Sabbagh, O. I., Salama, I., & Ibrahim, T. S. (2022). A review on Synthesis and Biological Evaluations of Pyrazolo [3, 4-d] pyrimidine Schaffold. Records of Pharmaceutical and Biomedical Sciences, 6(1), 28-50.
  14. A. V. Bobrova et al. (2021). Facile synthesis and sulfonylation of 4-aminopyrazoles. J. Mol. Struct., vol. 1230, pp. 1–7.
  15. Chang, K. C., Liu, P. F., Chang, C. H., Lin, Y. C., Chen, Y. J., & Shu, C. W. (2022). The interplay of autophagy and oxidative stress in the pathogenesis and therapy of retinal degenerative diseases. Cell & Bioscience, 12(1), 1-20.
  16. Y. Kaddouri, F. Abrigach, E. B. Yousfi, M. El Kodadi, and R. Touzani. (2020). New thiazole, pyridine and pyrazole derivatives as antioxidant candidates: synthesis, DFT calculations and molecular docking study. Heliyon, vol. 6, no. 1.
  17. Zhang, S., Wei, Y., Metz, J., He, S., Alvarez, P. J., & Long, M. (2022). Persistent free radicals in biochar enhance superoxide-mediated Fe (III)/Fe (II) cycling and the efficacy of CaO2 Fenton-like treatment. Journal of Hazardous Materials, 421, 126805.
  18. V. L. M. Silva, J. Elguero, and A. M. S. Silva. (2018). Current progress on antioxidants incorporating the pyrazole core. Eur. J. Med. Chem., vol. 156, pp. 394–429.
  19. Eze, F. N., Jayeoye, T. J., & Singh, S. (2022). Fabrication of intelligent pH-sensing films with antioxidant potential for monitoring shrimp freshness via the fortification of chitosan matrix with broken Riceberry phenolic extract. Food Chemistry, 366, 130574.
  20. R. Abeynayake, S. Zhang, W. Yang, and L. Chen. (2021). Development of antioxidant peptides from brewers’ spent grain proteins. Lwt, vol. 158.
  21. Meng, L., Wang, Z., Ji, H. F., & Shen, L. (2022). Causal association evaluation of diabetes with Alzheimer's disease and genetic analysis of antidiabetic drugs against Alzheimer's disease. Cell & Bioscience, 12(1), 1-16.
  22. Lam, H. Y. I., Guan, J. S., & Mu, Y. (2022). In silico repurposed drugs against monkeypox virus. Molecules, 27(16), 5277.
  23. S. Slavov and R. D. Beger. (2020). Quantitative structure–toxicity relationships in translational toxicology. Curr. Opin. Toxicol., vol. 23–24, pp. 46–49.
  24. Staszak, M., Staszak, K., Wieszczycka, K., Bajek, A., Roszkowski, K., & Tylkowski, B. (2022). Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship. Wiley Interdisciplinary Reviews: Computational Molecular Science, 12(2), e1568.
  25. Eno, E. A., Louis, H., Ekoja, P., Benjamin, I., Adalikwu, S. A., Orosun, M. M., ... & Agwamba, E. C. (2022). Experimental and computational modeling of the biological activity of benzaldehyde sulphur trioxide as a potential drug for the treatment of Alzheimer disease. Journal of the Indian Chemical Society, 99(7), 100532.
  26. R. S. of N. D. as A. A. Hadanu, L. Adelin, and I. W. Sutapa. (2018). QSAR Studies of Nitrobenzothiazole Derivatives as Antimalarial Agents. Makara J. Sci., vol. 22, no. 1, pp. 35–41.
  27. Mehmood, R., Mughal, E. U., Elkaeed, E. B., Obaid, R. J., Nazir, Y., Al-Ghulikah, H. A., ... & Sadiq, A. (2022). Synthesis of novel 2, 3-dihydro-1, 5-benzothiazepines as α-glucosidase inhibitors: In vitro, in vivo, kinetic, SAR, molecular docking, and QSAR studies. ACS omega, 7(34), 30215-30232.
  28. R. J. Boyd. (2019). Theoretical and Computational Chemistry. Elsevier Inc. Canada.
  29. Melnyk, N., Iribarren, I., Mates‐Torres, E., & Trujillo, C. (2022). Theoretical perspectives in organocatalysis. Chemistry–A European Journal, 28(58), e202201570.
  30. V. Moreira de Olivera, M. Machado Marinho, and E. Silva Marinho. (2019) Semi-Empirical Quantum Characterization of the Drug Selexipag: HOMO and LUMO and Reactivity Descriptors. Int. J. Recent Res. Rev., vol. 12, no. 2, pp. 15–20.
  31. Cong, Y., Zhai, Y., Chen, X., & Li, H. (2022). The Accuracy of Semi-Empirical Quantum Chemistry Methods on Soot Formation Simulation. International Journal of Molecular Sciences, 23(21), 13371.
  32. V. Bastikar, A. Bastikar, and P. Gupta. (2022) Quantitative structure-activity relationship-based computational approaches. Elsevier Inc. India.
  33. Cai, Z., Zafferani, M., Akande, O. M., & Hargrove, A. E. (2022). Quantitative structure–activity relationship (qsar) study predicts small-molecule binding to rna structure. Journal of medicinal chemistry, 65(10), 7262-7277.
  34. S. P. W. Zahra. (2021). Simulasi Dinamika Molekul Pada Efektivitas Proses Ekstraksi Minyak Atsiri Dari Kulit Jeruk Manis Laporan Tugas Akhir. Universitas Pertamina. Indonesia.
  35. Wang, L., Wang, J., Zhang, A., Huang, X. A., & Lei, H. (2022). Two binding epitopes modulating specificity of immunoassay for α-agonist detection: Quantitative structure–activity relationship. Food Chemistry, 371, 131071.
  36. F. Suhud, S. Siswandono, and T. Budiati. (2017). Sintesis dan Uji Aktivitas Senyawa 1-Benzil-3-benzoilurea Tersubstitusi Bromo, Kloro, Floro dan Triflorometil pada posisi para sebagai Agen Antiproliferatif, MPI (Media Pharm. Indones), vol. 1, no. 3, pp. 154–163.
  37. Bunmahotama, W., Vijver, M. G., & Peijnenburg, W. (2022). Development of a Quasi–Quantitative Structure–Activity Relationship Model for Prediction of the Immobilization Response of Daphnia magna Exposed to Metal‐Based Nanomaterials. Environmental Toxicology and Chemistry, 41(6), 1439-1450.
  38. A. La Kilo, L. O. Aman, I. Sabihi, and J. La Kilo. (2019). Studi Potensi Pirazolin Tersubstitusi 1-N dari Thiosemicarbazone sebagai Agen Antiamuba melalui Uji In Silico. Indo. J. Chem. Res., vol. 7, no. 1, pp. 9–24.
  39. Parrilha, G. L., dos Santos, R. G., & Beraldo, H. (2022). Applications of radiocomplexes with thiosemicarbazones and bis (thiosemicarbazones) in diagnostic and therapeutic nuclear medicine. Coordination Chemistry Reviews, 458, 214418.
  40. Y. T. Male and I. W. Sutapa. (2018). Xanthon Menggunakan Hubungan Kuantitatif, vol. 11, no. 1.
  41. Kong, L., Deng, Z., & You, D. (2022). Chemistry and biosynthesis of bacterial polycyclic xanthone natural products. Natural Product Reports, 39(11), 2057-2095.
  42. Muh. Taufiq. (2021). Analisis Hubungan Kuantitatif Struktur Dan Aktivitas Senyawa Turunan Aminoalkanol Xanton Sebagai Antikanker Menggunakan Metode Semiempiris Austin Model 1. UIN Alauddin Makassar. Indonesia.
  43. Khattab, A. R., & Farag, M. A. (2022). Marine and terrestrial endophytic fungi: A mine of bioactive xanthone compounds, recent progress, limitations, and novel applications. Critical Reviews in Biotechnology, 42(3), 403-430.
  44. K. A. Rakhman, N. A. Limatahu, H. B. Karim, and M. I. Abdjan. (2019). Kajian Senyawa Turunan Benzopirazin sebagai Antimalaria Menggunakan Metode HKSA dan MLR, EduChemia (Jurnal Kim. dan Pendidikan), vol. 4, no. 2, p. 112.
  45. Abate, M., Pagano, C., Masullo, M., Citro, M., Pisanti, S., Piacente, S., & Bifulco, M. (2022). Mangostanin, a xanthone derived from Garcinia mangostana fruit, exerts protective and reparative effects on oxidative damage in human keratinocytes. Pharmaceuticals, 15(1), 84.
  46. K. B. Wiberg and P. R. Rablen. (2018). Atomic Charges. J. Org. Chem, vol. 83, no. 24, pp. 15463–15469.
  47. Liu, S., & Luan, B. (2022). Benchmarking Various Types of Partial Atomic Charges for Classical All-Atom Simulations of Metal-Organic Frameworks. Nanoscale.
  48. E. Yuanita, Sudirman, N. K. T. Dharmayani, M. Ulfa, and J. Syahri. (2020). Quantitative structure–activity relationship (QSAR) and molecular docking of xanthone derivatives as anti-tuberculosis agents,” J. Clin. Tuberc. Other Mycobact. Dis., vol. 21, p. 100203.
  49. Hadrup, N., Frederiksen, M., Wedebye, E. B., Nikolov, N. G., Carøe, T. K., Sørli, J. B., ... & Hougaard, K. S. (2022). Asthma‐inducing potential of 28 substances in spray cleaning products—Assessed by quantitative structure activity relationship (QSAR) testing and literature review. Journal of Applied Toxicology, 42(1), 130-153.
  50. N. R. Trindade et al. (2018). The newly synthesized pyrazole derivative 5-(1-(3 fluorophenyl)-1H-pyrazol-4-yl)-2H-tetrazole reduces blood pressure of spontaneously hypertensive rats via NO/cGMO pathway. Front. Physiol., vol. 9, 3–12.
  51. Liu, Y., Tan, Y., Cheng, Z., Liu, S., Ren, Y., Chen, X., ... & Shen, Z. (2022). Quantitative structure-activity relationship (QSAR) guides the development of dye removal by coagulation. Journal of Hazardous Materials, 438, 129448.
  52. M. N. Kasmui and S. B. W. Kusuma. (2016). Analisis Hubungan Kuantitatif Struktur Dan Aktivitas Antimalaria Senyawa Turunan Quinoxalin, vol. 39, no. 2, pp. 98–106.
  53. Wang, L., Wang, J., Zhang, A., Huang, X. A., & Lei, H. (2022). Two binding epitopes modulating specificity of immunoassay for α-agonist detection: Quantitative structure–activity relationship. Food Chemistry, 371, 131071.
  54. S. Boudergua, M. Alloui, S. Belaidi, M. M. Al Mogren, U. A. A. Ellatif Ibrahim, and M. Hochlaf. (2019). QSAR Modeling and Drug-Likeness Screening for Antioxidant Activity of Benzofuran Derivatives. J. Mol. Struct., vol. 1189, pp. 307–314.
  55. Hirpara, K. S., & Patel, U. D. (2022). Quantitative structure–activity relationship (QSAR) models for color and COD removal for some dyes subjected to electrochemical oxidation. Environmental Technology, 1-12.
  56. G. C. Soares Rodrigues, M. Dos Santos Maia, E. N. Muratov, L. Scotti, and M. T. Scotti,. (2020). Quantitative Structure-Activity Relationship Modeling and Docking of Monoterpenes with Insecticidal Activity against Reticulitermes chinensis Snyder and Drosophila melanogaster. J. Agric. Food Chem., vol. 68, no. 16, pp. 4687–4698.

Most read articles by the same author(s)