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image of Synergistic Structural Inhibition of MMP-9 by Natural Flavonoids: A Natural Combinatorial Therapy against Cancer

Abstract

Introduction

Cancer is the uncontrolled proliferation of cells leading to metastasis due to genetic alterations resulting in oncogenes activation and tumor suppressor genes deactivation. It is the 2nd leading cause of death across the world. MMP-9 or gelatinase B, plays an effective role in ECM degradation, normal tissue turnover, and tissue remodelling.

Methods

Overexpression of MMP-9 has been studied in almost all types of cancers proving the effective role of MMP-9 in accelerating malignant conditions. Thus, targeting MMP-9 to treat cancer seems to be a potential strategy to deal with adverse pathologies of cancer. Methods: Chemotherapy and radiotherapy are frequently utilized for the treatment of cancer but are associated with diverse side effects. Flavonoids are natural compounds frequently found in plants and have been analyzed for the structural inhibition potential against MMP-9 by several researchers to develop natural treatments against cancer, but none of the flavonoids have landed into clinical use. In the present study, in-depth analysis to investigate the synergistic effects of flavonoids for structural inhibition of MMP-9 was done. The ADMET and bioactive properties analysis revealed effective drug-like properties of the considered flavonoids. Principal component analysis of ADMET and bioactive properties revealed high similarity in the chemical nature of luteolin and quercetin. Molecular docking analysis of MMP-9 with the considered flavonoids individually revealed the highest effective binding energy of luteolin.

Results

Combination docking analysis of MMP-9 with different combinations of flavonoids led to the identification of two combinations including Quercetin with Genistein and Luteolin and Genistein revealing high negative binding energies of -15.48kcal/mol and -15.31kcal/mol which was significantly greater than the binding energies identified for respective ligands in individual dockings.

Conclusion

Thus, the present study put forward synergistic natural flavonoid combinations against cancer the MMP-9 inhibition approach that can be further evaluated to develop high-efficacy treatments.

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2024-10-02
2024-11-29

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References

  1. Mathur P. Sathishkumar K. Chaturvedi M. Das P. Stephen S. Cancer incidence estimates for 2022 & projection for 2025: Result from National Cancer Registry Programme, India. Indian J. Med. Res. 2022 156 4 598 607 10.4103/ijmr.ijmr_1821_22 36510887
    [Google Scholar]
  2. Kapoor C. Vaidya S. Wadhwan V. Hitesh Kaur G. Pathak A. Seesaw of matrix metalloproteinases (MMPs). J. Cancer Res. Ther. 2016 12 1 28 35 10.4103/0973‑1482.157337 27072206
    [Google Scholar]
  3. Mondal S. Adhikari N. Banerjee S. Amin S.A. Jha T. Matrix metalloproteinase-9 (MMP-9) and its inhibitors in cancer: A minireview. Eur. J. Med. Chem. 2020 194 112260 10.1016/j.ejmech.2020.112260 32224379
    [Google Scholar]
  4. Xiao J. Huang J. Yolken R. H. Elevated matrix Metalloproteinase-9 associated with reduced cerebellar perineuronal nets in female mice with toxoplasmosis. Brain Behav Immun Health 2024 36 100728 10.1016/j.bbih.2024.100728
    [Google Scholar]
  5. Rashid Z.A. Bardaweel S.K. Novel Matrix Metalloproteinase-9 (MMP-9) Inhibitors in Cancer Treatment. Int. J. Mol. Sci. 2023 24 15 12133 10.3390/ijms241512133 37569509
    [Google Scholar]
  6. Hsu C.C. Huang S.F. Wang J.S. Chu W.K. Nien J.E. Chen W.S. Chow S.E. Interplay of N-Cadherin and matrix metalloproteinase 9 enhances human nasopharyngeal carcinoma cell invasion. BMC Cancer 2016 16 1 800 10.1186/s12885‑016‑2846‑4 27737648
    [Google Scholar]
  7. Vafadari B. Salamian A. Kaczmarek L. MMP-9 in translation: From molecule to brain physiology, pathology, and therapy. J. Neurochem. 2016 139 S2 91 114 10.1111/jnc.13415 26525923
    [Google Scholar]
  8. Hannocks M.J. Zhang X. Gerwien H. Chashchina A. Burmeister M. Korpos E. Song J. Sorokin L. The gelatinases, MMP-2 and MMP-9, as fine tuners of neuroinflammatory processes. Matrix Biol. 2019 75-76 102 113 10.1016/j.matbio.2017.11.007 29158162
    [Google Scholar]
  9. Huang H. Matrix Metalloproteinase-9 (MMP-9) as a Cancer Biomarker and MMP-9 Biosensors: Recent Advances. Sensors (Basel) 2018 18 10 3249 10.3390/s18103249 30262739
    [Google Scholar]
  10. Li H. Qiu Z. Li F. Wang C. The relationship between MMP-2 and MMP-9 expression levels with breast cancer incidence and prognosis. Oncol. Lett. 2017 14 5 5865 5870 10.3892/ol.2017.6924 29113219
    [Google Scholar]
  11. Akter H. Park M. Kwon O.S. Song E.J. Park W.S. Kang M.J. Activation of matrix metalloproteinase-9 (MMP-9) by neurotensin promotes cell invasion and migration through ERK pathway in gastric cancer. Tumour Biol. 2015 36 8 6053 6062 10.1007/s13277‑015‑3282‑9 25724188
    [Google Scholar]
  12. Amin S.A. Adhikari N. Jha T. Is dual inhibition of metalloenzymes HDAC-8 and MMP-2 a potential pharmacological target to combat hematological malignancies? Pharmacol. Res. 2017 122 8 19 10.1016/j.phrs.2017.05.002 28501516
    [Google Scholar]
  13. Jabłońska-Trypuć A. Matejczyk M. Rosochacki S. Jabłon´ A.J. Trypuc´ J-T. Matrix metalloproteinases (MMPs), the main extracellular matrix (ECM) enzymes in collagen degradation, as a target for anticancer drugs. J. Enzyme Inhib. Med. Chem. 2016 31 sup1 177 183 10.3109/14756366.2016.1161620 27028474
    [Google Scholar]
  14. Hou H. Zhang G. Wang H. Gong H. Wang C. Zhang X. High matrix metalloproteinase-9 expression induces angiogenesis and basement membrane degradation in stroke-prone spontaneously hypertensive rats after cerebral infarction. Neural Regen Res 2014 9 11 1154 62 10.4103/1673‑5374.135318
    [Google Scholar]
  15. Misko A. Ferguson T. Notterpek L. Matrix metalloproteinase mediated degradation of basement membrane proteins in Trembler J neuropathy nerves. J. Neurochem. 2002 83 4 885 894 10.1046/j.1471‑4159.2002.01200.x 12421361
    [Google Scholar]
  16. Niu J. Gu X. Turton J. Meldrum C. Howard E.W. Agrez M. Integrin-mediated signalling of gelatinase B secretion in colon cancer cells. Biochem. Biophys. Res. Commun. 1998 249 1 287 291 10.1006/bbrc.1998.9128 9705874
    [Google Scholar]
  17. Hiratsuka S. Nakamura K. Iwai S. Murakami M. Itoh T. Kijima H. Shipley J.M. Senior R.M. Shibuya M. MMP9 induction by vascular endothelial growth factor receptor-1 is involved in lung-specific metastasis. Cancer Cell 2002 2 4 289 300 10.1016/S1535‑6108(02)00153‑8 12398893
    [Google Scholar]
  18. Nyormoi O. Mills L. Bar-Eli M. An MMP-2/MMP-9 inhibitor, 5a, enhances apoptosis induced by ligands of the TNF receptor superfamily in cancer cells. Cell Death Differ. 2003 10 5 558 569 10.1038/sj.cdd.4401209 12728254
    [Google Scholar]
  19. Rathod S. Shinde K. Porlekar J. Choudhari P. Dhavale R. Mahuli D. Tamboli Y. Bhatia M. Haval K.P. Al-Sehemi A.G. Pannipara M. Computational Exploration of Anti-cancer Potential of Flavonoids against Cyclin-Dependent Kinase 8: An in silico Molecular Docking and Dynamic Approach. ACS Omega 2023 8 1 391 409 10.1021/acsomega.2c04837 36643495
    [Google Scholar]
  20. Rajiv Gandhi G. Sharanya C.S. Jayanandan A. Haridas M. Edwin Hillary V. Rajiv Gandhi S. Sridharan G. Sivasubramanian R. Silva Vasconcelos A.B. Montalvão M.M. Antony Ceasar S. Sousa N.F. Scotti L. Scotti M.T. Gurgel R.Q. Quintans-Júnior L.J. Multitargeted molecular docking and dynamics simulation studies of flavonoids and volatile components from the peel of Citrus sinensis L. (Osbeck) against specific tumor protein markers. J. Biomol. Struct. Dyn. 2024 42 6 3051 3080 10.1080/07391102.2023.2212062 37203996
    [Google Scholar]
  21. Kumari S. Kumar P. Design and Computational Analysis of an MMP9 Inhibitor in Hypoxia-Induced Glioblastoma Multiforme. ACS Omega 2023 8 11 10565 10590 10.1021/acsomega.3c00441 36969457
    [Google Scholar]
  22. De Forni D. Poddesu B. Cugia G. Chafouleas J. Lisziewicz J. Lori F. Synergistic drug combinations designed to fully suppress SARS-CoV-2 in the lung of COVID-19 patients. PLoS One 2022 17 11 e0276751 10.1371/journal.pone.0276751 36355808
    [Google Scholar]
  23. Gupta A. Chauhan S.S. Gaur A.S. Parthasarathi R. Computational screening for investigating the synergistic regulatory potential of drugs and phytochemicals in combination with 2-deoxy-D-glucose against SARS-CoV-2. Struct. Chem. 2022 33 6 2179 2193 10.1007/s11224‑022‑02049‑0 36093277
    [Google Scholar]
  24. Wiraswati H. Bashari M. Alfarafisa N. Ma’ruf I. Sholikhah E. Wahyuningsih T. Satriyo P. Mustofa M. Satria D. Damayanti E. Pyrazoline B-Paclitaxel or Doxorubicin Combination Drugs Show Synergistic Activity Against Cancer Cells: in silico Study. Adv. Appl. Bioinform. Chem. 2024 17 33 46 10.2147/AABC.S452281 38435441
    [Google Scholar]
  25. Ajji P.K. Walder K. Puri M. Combination of Balsamin and Flavonoids Induce Apoptotic Effects in Liver and Breast Cancer Cells. Front. Pharmacol. 2020 11 574496 10.3389/fphar.2020.574496 33192517
    [Google Scholar]
  26. Daina A. Michielin O. Zoete V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017 7 1 42717 10.1038/srep42717 28256516
    [Google Scholar]
  27. Banerjee P. Eckert A.O. Schrey A.K. Preissner R. ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Res. 2018 46 W1 W257 W263 10.1093/nar/gky318 29718510
    [Google Scholar]
  28. Raghavendra S. Aditya Rao S. J. Kumar V. Ramesh C. K. Multiple ligand simultaneous docking (MLSD): A novel approach to study the effect of inhibitors on substrate binding to PPO. Comput Biol Chem 2015 59 81 6 10.1016/j.compbiolchem.2015.09.008
    [Google Scholar]
  29. Lipinski C.A. Lombardo F. Dominy B.W. Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001 46 1-3 3 26 10.1016/S0169‑409X(00)00129‑0 11259830
    [Google Scholar]
  30. Yousef E.M. Tahir M.R. St-Pierre Y. Gaboury L.A. MMP-9 expression varies according to molecular subtypes of breast cancer. BMC Cancer 2014 14 1 609 10.1186/1471‑2407‑14‑609 25151367
    [Google Scholar]
  31. Reiner A.T. Tan S. Agreiter C. Auer K. Bachmayr-Heyda A. Aust S. Pecha N. Mandorfer M. Pils D. Brisson A.R. Zeillinger R. Lim S.K. EV-Associated MMP9 in High-Grade Serous Ovarian Cancer Is Preferentially Localized to Annexin V-Binding EVs. Dis. Markers 2017 2017 1 9 10.1155/2017/9653194 28607529
    [Google Scholar]
  32. Tian M. Cui Y.Z. Song G.H. Zong M.J. Zhou X.Y. Chen Y. Han J.X. Proteomic analysis identifies MMP-9, DJ-1 and A1BG as overexpressed proteins in pancreatic juice from pancreatic ductal adenocarcinoma patients. BMC Cancer 2008 8 1 241 10.1186/1471‑2407‑8‑241 18706098
    [Google Scholar]
  33. Li Y. Wu T. Zhang B. Yao Y. Yin G. Matrix metalloproteinase-9 is a prognostic marker for patients with cervical cancer. Med Oncol 2012 29 5 3394 9 10.1007/s12032‑012‑0283‑z
    [Google Scholar]
  34. Liu N. Wang X. Wu H. Lv X. Xie H. Guo Z. Wang J. Dou G. Zhang C. Sun M. Computational study of effective matrix metalloproteinase 9 (MMP9) targeting natural inhibitors. Aging (Albany NY) 2021 13 19 22867 22882 10.18632/aging.203581 34607974
    [Google Scholar]
  35. Adhipandito C. F. Ludji D. P. K. S. Aprilianto E. Jenie R. I. Al-Najjar B. Hariono M. Matrix metalloproteinase9 as the protein target in anti-breast cancer drug discovery: An approach by targeting hemopexin domain. Futur J Pharm Sci 2019 10.1186/s43094‑019‑0001‑1
    [Google Scholar]
  36. Hariono M. Rollando R. Karamoy J. Hariyono P. Atmono M. Djohan M. Wiwy W. Nuwarda R. Kurniawan C. Salin N. Wahab H. Bioguided Fractionation of Local Plants against Matrix Metalloproteinase9 and Its Cytotoxicity against Breast Cancer Cell Models: in silico and in vitro Study. Molecules 2020 25 20 4691 10.3390/molecules25204691
    [Google Scholar]
  37. Kalva S. Azhagiya Singam E.R. Rajapandian V. Saleena L.M. Subramanian V. Discovery of potent inhibitor for matrix metalloproteinase-9 by pharmacophore based modeling and dynamics simulation studies. J. Mol. Graph. Model. 2014 49 25 37 10.1016/j.jmgm.2013.12.008 24473069
    [Google Scholar]
  38. Gao Q. Wang Y. Hou J. Yao Q. Zhang J. Multiple receptor-ligand based pharmacophore modeling and molecular docking to screen the selective inhibitors of matrix metalloproteinase-9 from natural products. J. Comput. Aided Mol. Des. 2017 31 7 625 641 10.1007/s10822‑017‑0028‑3 28623487
    [Google Scholar]
  39. Zhang Q. Liu S. Li Z.Y. Shang Y.J. Kollie L. Liang Z.S. Exploring the potential mechanisms of luteolin against ulcerative colitis and colorectal cancer via network pharmacology and molecular docking. TMR Integrativ Med 2023 7 0 e23026 10.53388/TMRIM202307026
    [Google Scholar]
  40. Chang M. Chen S. Li C. Zhang Y. Zhao H. Exploring the bioactive compounds derived from Plumula Nelumbinis and potential targets for the treatment of non-small cell lung cancer: A network pharmacology study. J Cancer Discov 2022 10.55976/jcd.1202219630‑48
    [Google Scholar]
  41. Wu L. Lin Y. Gao S. Wang Y. Pan H. Wang Z. Pozzolini M. Yang F. Zhang H. Yang Y. Xiao L. Xu Y. Luteolin inhibits triple-negative breast cancer by inducing apoptosis and autophagy through SGK1-FOXO3a-BNIP3 signaling. Front. Pharmacol. 2023 14 1200843 10.3389/fphar.2023.1200843 37346292
    [Google Scholar]
  42. Sain A. Khamrai D. Kandasamy T. Naskar D. Apigenin exerts anti-cancer effects in colon cancer by targeting HSP90AA1. J. Biomol. Struct. Dyn. 2023 1 13 10.1080/07391102.2023.2299305 38157250
    [Google Scholar]
  43. Nair N.U. Greninger P. Zhang X. Friedman A.A. Amzallag A. Cortez E. Sahu A.D. Lee J.S. Dastur A. Egan R.K. Murchie E. Ceribelli M. Crowther G.S. Beck E. McClanaghan J. Klump-Thomas C. Boisvert J.L. Damon L.J. Wilson K.M. Ho J. Tam A. McKnight C. Michael S. Itkin Z. Garnett M.J. Engelman J.A. Haber D.A. Thomas C.J. Ruppin E. Benes C.H. A landscape of response to drug combinations in non-small cell lung cancer. Nat. Commun. 2023 14 1 3830 10.1038/s41467‑023‑39528‑9 37380628
    [Google Scholar]
  44. Lafi Z. Alshaer W. Gharaibeh L. Alqudah D.A. AlQuaissi B. Bashaireh B. Ibrahim A.A. Synergistic combination of doxorubicin with hydralazine, and disulfiram against MCF-7 breast cancer cell line. PLoS One 2023 18 9 e0291981 10.1371/journal.pone.0291981 37768997
    [Google Scholar]
  45. Hong D. S. Moore K. N. Bendell J. C. Karp D. D. Wang J. S. Ulahannan S. V Jones S. Wu W. Donoho G. P. Ding Y. Capen A. Wang X. Lin A. B. Patel M. R. Preclinical Evaluation and Phase Ib Study of Prexasertib, a CHK1 Inhibitor, and Samotolisib (LY3023414), a Dual PI3K/mTOR Inhibitor. Clin Cancer Res 2021 27 7 1864 1874 10.1158/1078‑0432.CCR‑20‑3242
    [Google Scholar]
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Synergistic Structural Inhibition of MMP-9 by Natural Flavonoids: A Natural Combinatorial Therapy against Cancer
Bentham Science Publishers ; https://doi.org/10.2174/0122115501324502240919104816
/content/journals/cbiot/10.2174/0122115501324502240919104816
/content/journals/cbiot/10.2174/0122115501324502240919104816
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  • Article Type:     Research Article
Keywords: MMP-9 ; Cancer ; docking ; flavonoids ; synergistic combinations ; ADMET

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