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In Silico Analysis of Anti-inflammatory Activity of Quercetin from M. calabura Fruit

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Natural Product Experiments in Drug Discovery

Part of the book series: Springer Protocols Handbooks ((SPH))

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Abstract

The aim of the present study is to reveal the mechanism of quercetin compound from M. calabura fruit extract in anti-inflammatory reaction using in silico studies. In silico screening of quercetin against the crucial inflammatory molecular target COX-2 was done using DS 2.1 tool. Maximum binding affinity of −2.583 was exhibited against COX-2. In silico modeling confirms the anti-inflammatory efficacy of quercetin. From the in silico analysis, we infer that quercetin has great efficacy in anti-inflammatory activity which could be used to treat inflammatory diseases.

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References

  1. Lengauer T, Rarey M (1996) Computational methods for biomolecular docking. Curr Opin Struct Biol 6(3):402–406

    Article  CAS  Google Scholar 

  2. Kitchen DB, Decornez H, Furr JR, Bajorath J (2004) Docking and scoring in virtual screening for drug discovery: methods and applications. Nat Rev Drug Discov 3(11):935–949

    Article  CAS  Google Scholar 

  3. Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Belew RK, Olson AJ (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem 19(14):1639–1662

    Article  CAS  Google Scholar 

  4. Meng EC, Shoichet BK, Kuntz ID (2004) Automated docking with grid-based energy evaluation. J Comput Chem 13(4):505–524

    Article  Google Scholar 

  5. Feig M, Onufriev A, Lee MS, Im W, Case DA, Brooks CL (2004) Performance comparison of generalized born and Poisson methods in the calculation of electrostatic solvation energies for protein structures. J Comput Chem 25(2):265–284

    Article  CAS  Google Scholar 

  6. Lin F, Chen J, Shih G (2005) Antinociceptive and anti-inflammatory activity of the water- soluble extracts from leaves of Muntingia calabura. Chin Pharm J 57:81–88

    CAS  Google Scholar 

  7. Zakaria ZA, Hazalin NA, Mohd-Zaid SNH, Abul Ghani M, Hassan MH, Hanankumar G et al (2007) Antinociceptive, anti- inflammatory and antipyretic effects of Muntingia calabura aqueous extract in animal models. J Nat Med 1(4):443–448

    Article  Google Scholar 

  8. Wang S, Xiang-Yu-Lan, Xiao J, Yang J, Kao J, Chang S (2008) Antiinflammatory activity of Lindera erythrocarpa fruits. Phytother Res 22:213–216

    Article  CAS  Google Scholar 

  9. Bora A, Pacureanu L, Crisan L (2021) In silico study of some natural flavonoids as potential agents against COVID-19: preliminary results. Chem Proc MDPI

    Google Scholar 

  10. Manach C, Scalbert A, Morand C, Remesy C, Jimenez L (2004) Polyphenols: food sources and bioavailability. Am J Clin Nutr 79:727–747

    Article  CAS  Google Scholar 

  11. Hollman PC, Katan MB (1999) Dietary flavonoids: intake, health effects and bioavailability. Food Chem Toxicol 37:937–942

    Article  CAS  Google Scholar 

  12. Preethi K, Sasikumar JM, Microcore. (2011) Phytochemical studies on Muntingia calabura L. fruits from Tamilnadu, India. Int J Biotechnol Biochem 7(3):311–320

    Google Scholar 

  13. Marnett LJ, Kalgutkar AS (1999) Cyclooxygenase 2 inhibitors discovery selectivity and the future. Trends Pharmacol Sci 20(11):465–469

    Article  CAS  Google Scholar 

  14. Marnett LJ, Kalgutkar AS (1998) Design of selective inhibitors of Cyclooxygenase-2 as nonulcergenic antiinflammatory agents. Curr Opin Chem Biol 2(4):482–490

    Article  CAS  Google Scholar 

  15. King F (ed) (2002) Medicinal chemistry: principles and practice. The Royal Society of chemistry, Cambridge

    Google Scholar 

  16. Lorens O, Perez JJ et al (1999) Structural basis of the dynamic mechanism of ligand binding to cyclooxygenase. Biol Med Chem Lett 9(19):2779–2784

    Article  Google Scholar 

  17. Chhajed SS, Hiwanj PB, Bastikar VA, Upasani CD, Upasani CD, Udavant PB, Dhake AS, Mahajan NP (2010) Structure based design and in-silico molecular docking analysis of some novel benzimidazoles. Int J ChemTech Res 2(2):1135–1040

    CAS  Google Scholar 

  18. Venkatachalam CM, Jiang X, Oldfield T, Waldman M (2003) LigandFit: a novel method for the shape-directed rapid docking of ligands to protein active sites. J Mol Graph Model 21:289–307

    Article  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Biopharmacy Lab, Department of Microbial Biotechnology, Bharathiar University, Coimbatore, Tamil Nadu, India

    K. Preethi

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  1. K. Preethi
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Correspondence to K. Preethi .

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Editors and Affiliations

  1. Key Laboratory of Economic Plants and Biotechnology and the Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China

    Karuppusamy Arunachalam

  2. Key Laboratory of Economic Plants and Biotechnology and the Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China

    Xuefei Yang

  3. Department of Botany, NSS College, Nemmara, Palakkad, Kerala, India

    Sreeja Puthanpura Sasidharan

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Preethi, K. (2023). In Silico Analysis of Anti-inflammatory Activity of Quercetin from M. calabura Fruit. In: Arunachalam, K., Yang, X., Puthanpura Sasidharan, S. (eds) Natural Product Experiments in Drug Discovery. Springer Protocols Handbooks. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2683-2_29

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  • DOI: https://doi.org/10.1007/978-1-0716-2683-2_29

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2682-5

  • Online ISBN: 978-1-0716-2683-2

  • eBook Packages: Springer Protocols

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