Molecular insights on binding interactions of cyclooxygenase and lipoxygenase activities on malondialdehyde in naphthalene-exposed Wistar rats

Authors

  • I. Olaoye Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author
  • A. Akhigbe Department of Chemical Sciences, McPherson University – Seriki Sotayo, Nigeria Author
  • A. Awotula Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author
  • B. Oso Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author
  • O. Agboola Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author
  • A. Adebayo Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author
  • R. Banwo Department of Biochemistry and Molecular Biology, McPherson University-Seriki Sotayo, Nigeria Author

DOI:

https://doi.org/10.2478/AMB-2024-0062

Keywords:

naphthalene, malondialdehyde, cyclooxygenase, lipoxygenase, 1-nitronaphthalene

Abstract

Background. Naphthalene (NA), a polycyclic aromatic hydrocarbon, is an environmental pollutant from different sources exhibiting toxicities via free radical generation. However, NA has been used in the industry as surfactants, solvents, resins, and in 
medicine – as an anti-viral, anti-bacterial, and antiinflammatory drug. Malondialdehyde (MDA), a by-product in lipid peroxidation and prostaglandin synthesis, is a biomarker in lipid peroxidation evaluation and cyclooxygenase (COX) and lipoxygenase (LOX) activities 
assessment via inhibition. Results. The twenty-four adult male Wistar rats were randomly divided into six groups of four rats each. The animals in the control groups were given food and water only while the NA-exposed groups: group 3 (N1) rats exposed to NA at 0.75 mg/m3 for 2 hours, group 4 (N2) rats exposed to NA at 1.5 mg/m3 for 2 hours, group 5 (N3) rats exposed to NA at 0.75 mg/m3 for 4 hours and group 6 (N4) rats exposed to NA at 1.5 mg/m3 for 4 hours. In addition, in silico work was carried out on the homologs of COX and LOX with NA and its selected metabolites. The in vivo result revealed a significant increase (7.50 ± 0.29) in MDA synthesis at the lower dose (0.75 g/m3) during the 2 hrs exposure time compared to the control while the higher dose (1.50 g/m3) showed a significant reduction in MDA level (1.00 ± 0.01) compared to the control. Furthermore, docking result depicted highest binding score for 1-nitronaphthalene towards COX and LOX. Conclusions. This study suggested that NA could reduce the synthesis of MDA in the in vivo work, and 1-nitronaphthalene showed the highest binding affinity in the in silico work.

References

Jing M, Han G, Wan J et al. Catalase and superoxide dismutase response and the underlying molecular mechanism for naphthalene. Science of the Total Environment 736: 2020,139567. https://doi.org/10.1016/j.scitotenv.2020.139567

Stohs SJ, Ohia S, Bagchi D. Naphthalene toxicity and antioxidant nutrients. Toxicology 2002;180,(1):97-105. https://doi.org/10.1016/S0300-483X(02)00384-0

Yost EE, Galizia A, Kapraun DF Health Effects of Naphthalene Exposure: A Systematic Evidence Map and Analysis of Potential Considerations for Dose – Response Evaluation, 2021;129.

Abozeid MA, El-sawi AA, Abdelmoteleb M et al. Hybrids with potent antitumor, antiinflammatory, 2020,42998-43009. https://doi.org/10.1039/d0ra08526j

Pandya AB, Prajapati DG, Pandya SS. Synthesis of novel Naphthalene COX inhibitors for antiinflammatory activity. Journal of Applied Pharmaceutical Science 2012;2(8):226–232. https://doi.org/10.7324/JAPS.2012.2840

Sharma S, Singh T. A study of novel antiinflammatory derivatives of novel α-amino naphthalene and β-amino naphthalene. Archive de Pharmazie 2006;339,135-152.

Mohammed, MS, Osman WJA, Garelnabi EA et al. Secondary metabolites as antiinflammatory agents. The Journal of Phytopharmacology 2014;3(4): 275-285.

El haimeur B, Bouhallaoui M, Zbiry M et al. Use of biomarkers to evaluate the effects of environmental stressors on Mytilus

galloprovincialis sampled along the Moroccan coasts: Integrating biological and chemical data. Marine Environmental Research 2017;130,60-68. https://doi.org/10.1016/j.marenvres.2017.05.010

Zhang F, Zhang Y, Wang K et al. Protective effect of diallyl trisulfide against naphthalene-induced oxidative stress and inflammatory damage in mice. International Journal of Immunopathology and Pharmacology 2016;29(2):205–216. https://doi.org/10.1177/0394632015627160

Buege JA, Aust SD. Microsomal lipid peroxidation. Methods Enzymol. 1978;52:302-10. doi: 10.1016/s0076-6879(78)52032-6

Trott O, Olson AJ. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization and multithreading. Journal of Computational Chemistry, 2010;31(2): 455-461. https://doi.org/10.1002/jcc.21334

Kim S, Chen J, Cheng T et al. PubChem 2019 update: improved access to chemical data. Nucleic Acids Research. 2019;47 (D1): D1102–D1109. doi: 10.1093/nar/gky1033

The UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Research, 2021;49(D1): D480-D489. https://doi.org/10.1093/nar/gkaa1100

Waterhouse A, Bertoni M, Bienert S et al. () SWISS-MODEL: homology modelling of protein structures and complexes.

Nucleic Acids Res. 2018;46(W1): W296-W303. https://doi.org/10.1093/nar/gky427

Laskowski RA, MacArthur MW, Moss DS, Thornton JM () PROCHECK: a program to check the stereochemical quality of protein structures. J. Appl Crystal 1993;26(2):283-291. https://doi.org/10.1107/S0021889892009944

Laskowski RA, Rullmannn JA, MacArthur MW et al. AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 1996;8(4): 477-486. https://doi.org/10.1 007/BF00228148

Schüttelkopf AW, van Aalten DMF. PRODRG: a tool for highthroughput crystallography of protein-ligand complexes. Acta Crystallogr 2004,D60, 1355-1363.

Bekker H, Berendsen HJC, Dijkstra EJ et al. Gromacs: A parallel computer for molecular dynamics simulations” 252–256

in Physics computing 92. Edited by R.A. de Groot and J. Nadrchal. World Scientific, Singapore, 1993.

Abraham MJ, Murtola T, Schulz R et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers, SoftwareX, 2015, 1-2 19-25.

Singh P, Mittal A. Current status of COX-2 inhibitors. Mini Rev Med Chem. 2008;8(1):73-90

Rouzer CA, Marnett LJ. Cyclooxygenases: structural and functional insights. J Lipid Res. 2009;50,S29-34. 10.1194/jlr.R800042-JLR200

Chakraborti AK, Garg SK, Kumar R et al. Progress in COX-2 inhibitors: a journey so far. Curr Med Chem. 2010;17(15):1563-1593.

Baldwin RM, Jewell WT, Fanucchi MV et al, Comparison of pulmonary/nasal CYP2F expression levels in rodents and rhesus macaque. J Pharmacol Exp Therapy 2004;309,127-136

Kushwah DS, Salman MT, Singh P et al. Protective effects of ethanolic extract of Nigella sativa seed in paracetamol induced acute hepatotoxicity in vivo Pak J Biol Sci 2014;17(4):517-22. doi: 10.3923/pjbs.2014.517.522.

Olaoye I, Awotula A, Oso B et al. Naphthalene exposure decreases reduced glutathione in male Wistar rats. Biotecnol Apl. 2022;39(1):1201-10.

West JA, Pakehham G, Morin D et al. Inhaled naphthalene causes dose dependent Clara cell cytotoxicity in mice but not in rats. Toxicol Appl Pharmacol 2001;173(2):114-9. doi: 10.1006/taap.2001.9151

West JA, Buckpitt AR, Plopper CG. Elevated airway GSH resynthesis confers protection to Clara cells from naphthalene injury in mice made tolerant by repeated exposures. Journal of Pharmacology and Experimental Therapeutics 2000;294,516-523.

West JA, Williams KJ, Toskala E et al. Induction of tolerance to naphthalene in Clara cells is dependent on a stable phenotypic adaptation favoring maintenance of the glutathione pool. Am J Pathol 2002;160(3):1115-27. doi: 10.1016/S0002-9440(10)64932-2

Kikuno S, Taguchi K, Iwamoto N et al. 1,2-Naphthoquinone activates vanilloid receptor 1 through increased protein tyrosine phosphorylation, leading to contraction of guinea pig trachea. Toxicol Appl Pharmacol 2006;210,47-54.

Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models, Bioinformatics 2011;27(3):343-350. https://doi.org/10.1093/bioinformatics/btq662

Cardoso JM, Fonseca L, Egas C, Abrantes I. Cysteine proteases secreted by the pinewood nematode, Bursaphelenchus xylophilus: in silico analysis. Comput Biol Chem. 2018;77,291-296

Patel B, Singh V, Patel D. Structural Bioinformatics. In: Shaik NA, Hakeem, KR, Banaganapalli, B, Elango, R. editors. Essentials of Bioinformatics, vol. I. Cham, Switzerland: Springer 2019,169-199. https://doi.org/10.1007/978-3-030-02634-9

Brylinski M. Aromatic interactions at the ligand-protein interface: Implications for the development of docking scoring functions. Chem Biol Drug Des 2018;91(2):380- 90.

Olaoye I, Oso B, Aberuagba A. Molecular Mechanisms of Anti-Inflammatory Activities of the Extracts of Ocimum gratissimum and Thymus vulgaris. Avicenna Journal of Medical Biotechnology 2021;13(4):207-216 http://dx.doi.org/10.18502/ajmb.v13i4.7206

Elokely KM, Doerksen RJ. Docking challenge: protein sampling and molecular docking performance. J Chem Inf Model 2013;53(8):1934-5

Tanner JJ. Empirical power laws for the radii of gyration of protein oligomers. Acta Cryst D72:2016,1119-1129. http://dx.doi.org/10.1107/S2059798316013218

Shukla R, Shukla H, Kalita P, Tripathi T. Structural insights into natural compounds as inhibitors of Fasciola gigantica thioredoxin glutathione reductase. J Cell Biochem. 2017,1-32. 10.1002/jcb.26444

Adewole K, Adebayo I, Olaoye I. In silico profiling of histone deacetylase inhibitory activity of compounds isolated from Cajanus cajan. Beni-Suef Univ J Basic Appl Sci 2022;11,9. https://doi.org/10.1186/s43088-021-00191-y

Maiorov VN, Crippen GM. Significance of root mean-square deviation in comparing three-dimensional structures of globular proteins. Journal of Molecular Biology 1994;235,625-634. doi:10.1006/jmbi.1994.1017

Martinez L. Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis. PLoS ONE 2015;10(3):e0119264. https://doi.org/10.1371/journal. pone.0119264

Sargsyan K, Grauffel C, Lim C. How molecular size impacts RMSD applications in molecular dynamics simulations. J Chem Theory Comput. 2017;13(4):1518-1524. https://doi.org/10.1021/acs.jctc.7b00028

Mattea C, Qvist J, Halle B. Dynamics at the protein-water interface from 17O spin relaxation in deeply supercooled solutions. Biophys J. 2008;95(6):2951-63.

Damjanović A, Brooks BR, Garcia-Moreno ́ BE. Conformational relaxation and water penetration coupled to ionization of internal groups in proteins. J Phys Chem 2011;115(16):4042-5

Downloads

Published

04.10.2024

How to Cite

Olaoye, I., Akhigbe, A., Awotula, A., Oso, B., Agboola, O., Adebayo, A., & Banwo, R. (2024). Molecular insights on binding interactions of cyclooxygenase and lipoxygenase activities on malondialdehyde in naphthalene-exposed Wistar rats. Acta Medica Bulgarica, 51(Suppl 2), 120-142. https://doi.org/10.2478/AMB-2024-0062