Bergenin: a computationally proven promising scaffold for novel galectin-3 inhibitors

  • Ranga Srinath JayakodyEmail author
  • Prageeth Wijewardhane
  • Chamikara Herath
  • Shehani Perera
Original Paper


Bergenin is a C-glycoside of 4-O-methylgallic acid that is isolated from medicinal plants such as Flueggea leucopyrus, Bergenia crassifolia, Mallotus philippensis, Corylopsis spicata, Caesalpinia digyna, Mallotus japonicus, and Sacoglottis gabonensis. Even though there appears to be ample evidence from South Asian traditional medicine that bergenin possesses strong anticancer activity, no comprehensive scientific study has been carried out to test its anticancer potency. Therefore, in this study, the potential mechanisms of action for bergenin’s postulated anticancer activity were examined using computational techniques. Firstly, bergenin was tested for its toxicity as a drug candidate using in silico toxicity analysis. It was found that bergenin is nontoxic according to modern toxicity measures. The optimized structure of bergenin was obtained at the DFT-B3LYP/6-31G(d) level of theory. Potential biological targets of bergenin were identified using reverse docking calculations. Reverse docking results suggested that galectin-3 is a potential target of bergenin. Gelectin-3 is an enzyme that plays a major role in cell–cell adhesion, cell-matrix interactions, macrophage activation, angiogenesis, metastasis, and apoptosis in cancer, making it a popular target in anticancer drug design. Among the many potential biological targets predicted by reverse docking calculations, galectin-3 was selected as it complies with the primary objective of this study. The binding of bergenin to galectin-3 was studied by conventional forward docking calculations. Classical molecular dynamics (MD) simulations were used to study the stability of the galectin-3:bergenin complex. Docking calculations indicated that bergenin has the potential to effectively bind to the carbohydrate recognition domain (CRD) of galectin-3. As well as electrostatic and van der Waals interactions, a few strong hydrogen bonds were found to be involved in the binding of bergenin to galectin-3. There is also a plausible π-stacking interaction between the aromatic moiety of bergenin and the His158 residue at the binding site. A 50-ns MD simulation was carried out for the bergenin:galectin-3 complex in a cubic water box with periodic boundary conditions. The MD results showed that the bergenin:galectin-3 complex is highly stable and confirmed the veracity of the docking results, which suggested that bergenin potentially exerts an inhibitory effect on galectin-3. This study therefore sheds new light on the anticancer activity of bergenin and demonstrates that bergenin could potentially be used to develop more potent galectin-3 inhibitors. The study also provides scientific evidence supporting the use of bergenin-containing plants in cancer treatments in Eastern traditional medicine.

Graphical abstract

Bergenin in the galectin-3 binding site


Bergenin Galectin-3 Galectin-3 inhibitors Anticancerous natural products 



We thank the Department of Chemistry and the Faculty of Applied Sciences of the University of Sri Jayewardenepura, Gangodawila, Nugegoda, Sri Lanka for facilitating this research.


  1. 1.
    Li JWH, Vederas JC (2009) Drug discovery and natural products: end of an era or an endless frontier? Science 325(5937):161–165Google Scholar
  2. 2.
    Koehn FE, Carter GT (2005) The evolving role of natural products in drug discovery. Nat Rev Drug Discov 4(3):206–220Google Scholar
  3. 3.
    Newman DJ, Cragg GM (2007) Natural products as sources of new drugs over the last 25 years. J Nat Prod 70(3):461–477Google Scholar
  4. 4.
    Cragg GM, Newman DJ (2013) Natural products: a continuing source of novel drug leads. Biochim Biophys Acta 1830(6):3670–3695Google Scholar
  5. 5.
    Soysa P, De Silva IS, Wijayabandara J (2014) Evaluation of antioxidant and anti proliferative activity of Flueggea leucopyrus Willd (Katupila). BMC Complement Altern Med 14(1):274Google Scholar
  6. 6.
    Kim H-S, Lim H-K, Chung M-W, Kim YC (2000) Antihepatotoxic activity of bergenin, the major constituent of Mallotus japonicus, on carbon tetrachloride-intoxicated hepatocytes. J Ethnopharmacol 69(1):79–83Google Scholar
  7. 7.
    Lim H-K, Kim H-S, Choi H-S, Oh S, Choi J (2000) Hepatoprotective effects of bergenin, a major constituent of Mallotus japonicus, on carbon tetrachloride-intoxicated rats. J Ethnopharmacol 72(3):469–474Google Scholar
  8. 8.
    Prithiviraj B, Singh UP, Manickam M, Srivastava JS, Ray AB (1997) Antifungal activity of bergenin, a constituent of Flueggea microcarpa. Plant Pathol 46(2):224–228Google Scholar
  9. 9.
    Nunomura R, Oliveira VG, Da Silva SL, Nunomura SM (2009) Characterization of bergenin in Endopleura uchi bark and its anti-inflammatory activity. J Braz Chem Soc 20(6):1060–1064Google Scholar
  10. 10.
    Nazir N, Koul S, Qurishi MA, Taneja SC, Ahmad SF, Bani S, Qazi GN (2007) Immunomodulatory effect of bergenin and norbergenin against adjuvant-induced arthritis—a flow cytometric study. J Ethnopharmacol 112(2):401–405CrossRefGoogle Scholar
  11. 11.
    Swarnalakshmi T, Sethuraman MG, Sulochana N, Arivudainambi R (1984) A note on the antiinflammatory activity of bergenin. Curr Sci 53(17):917Google Scholar
  12. 12.
    Raj MK, Duraipandiyan V, Agustin P, Ignacimuthu S (2012) Antimicrobial activity of bergenin isolated from Peltophorum pterocarpum DC. flowers. Asian Pac J Trop Biomed 2(2):S901–S904Google Scholar
  13. 13.
    Patel DK, Patel K, Kumar R, Gadewar M, Tahilyani V (2012) Pharmacological and analytical aspects of bergenin: a concise report. Asian Pacific J Trop Dis 2(2):163–167CrossRefGoogle Scholar
  14. 14.
    Gill PMW, Johnson BG, Pople JA, Frisch MJ (1992) The performance of the Becke–Lee–Yang–Parr (B–LYP) density functional theory with various basis sets. Chem Phys Lett 197(4):499–505Google Scholar
  15. 15.
    Frisch MJ, Trucks GW, Schlegel HB, Scuseria GE, Robb MA, Cheeseman JR, Scalmani G, Barone V, Petersson GA, Nakatsuji H et al (2016) Gaussian 16 (R), A.03. Gaussian Inc., WallingfordGoogle Scholar
  16. 16.
    Lagorce D, Sperandio O, Baell JB, Miteva MA, Villoutreix BO (2015) FAF-Drugs3: a web server for compound property calculation and chemical library design. Nucleic Acids Res 43(W1):W200–W207CrossRefGoogle Scholar
  17. 17.
    Liu X, Ouyang S, Yu B, Liu Y, Huang K, Gong J, Zheng S, Li Z, Li H, Jiang H (2010) PharmMapper server: a web server for potential drug target identification using pharmacophore mapping approach. Nucleic Acids Res 38(suppl 2):W609–W614CrossRefGoogle Scholar
  18. 18.
    Sörme P, Arnoux P, Kahl-Knutsson B, Leffler H, Rini JM, Nilsson UJ (2005) Structural and thermodynamic studies on cation–π interactions in lectin–ligand complexes: high-affinity galectin-3 inhibitors through fine-tuning of an arginine–arene interaction. J Am Chem Soc 127(6):1737–1743Google Scholar
  19. 19.
    Vriend G (1990) WHAT IF: a molecular modeling and drug design program. J Mol Graph 8(1):52–56, 29 Google Scholar
  20. 20.
    Søndergaard CR, Olsson MHM, Rostkowski M, Jensen JH (2011) Improved treatment of ligands and coupling effects in empirical calculation and rationalization of pK a values. J Chem Theory Comput 7(7):2284–2295CrossRefGoogle Scholar
  21. 21.
    Olsson MHM, Søndergaard CR, Rostkowski M, Jensen JH (2011) PROPKA3: consistent treatment of internal and surface residues in empirical pK a predictions. J Chem Theory Comput 7(2):525–537Google Scholar
  22. 22.
    Allen WJ, Balius TE, Mukherjee S, Brozell SR, Moustakas DT, Lang PT, Case DA, Kuntz ID, Rizzo RC (2015) DOCK 6: impact of new features and current docking performance. J Comput Chem 36(15):1132–1156CrossRefGoogle Scholar
  23. 23.
    Pearlman DA, Case DA, Caldwell JW, Ross WS, Cheatham TE, DeBolt S, Ferguson D, Seibel G, Kollman P (1995) AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules. Comput Phys Commun 91(1):1–41CrossRefGoogle Scholar
  24. 24.
    Gasteiger J, Marsili M (1978) A new model for calculating atomic charges in molecules. Tetrahedron Lett 19(34):3181–3184CrossRefGoogle Scholar
  25. 25.
    Gasteiger J, Marsili M (1980) Iterative partial equalization of orbital electronegativity—a rapid access to atomic charges. Tetrahedron 36(22):3219–3228CrossRefGoogle Scholar
  26. 26.
    Berendsen HJC, van der Spoel D, van Drunen R (1995) GROMACS: a message-passing parallel molecular dynamics implementation. Comput Phys Commun 91(1):43–56CrossRefGoogle Scholar
  27. 27.
    Berendsen HJC, Grigera JR, Straatsma TP (1987) The missing term in effective pair potentials. J Phys Chem 91(24):6269–6271CrossRefGoogle Scholar
  28. 28.
    Grubmüller H, Heller H, Windemuth A, Schulten K (1991) Generalized Verlet algorithm for efficient molecular dynamics simulations with long-range interactions. Mol Simul 6(1–3):121–142CrossRefGoogle Scholar
  29. 29.
    Darden T, York D, Pedersen L (1993) Particle mesh Ewald: an N·log (N) method for Ewald sums in large systems. J Chem Phys 98(12):10089–10092Google Scholar
  30. 30.
    van Aalten DMF, Bywater R, Findlay JBC, Hendlich M, Hooft RWW, Vriend G (1996) PRODRG, a program for generating molecular topologies and unique molecular descriptors from coordinates of small molecules. J Comput Aided Mol Des 10(3):255–262CrossRefGoogle Scholar
  31. 31.
    Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL (2000) OPLS-AA/L force field for proteins using accurate quantum mechanical data. Abstr Pap Am Chem Soc 220:U279Google Scholar
  32. 32.
    Fernandes CL, Sachett LG, Pol-Fachin L, Verli H (2010) GROMOS96 43a1 performance in predicting oligosaccharide conformational ensembles within glycoproteins. Carbohydr Res 345(5):663–671CrossRefGoogle Scholar
  33. 33.
    Reed AE, Weinstock RB, Weinhold F (1985) Natural population analysis. J Chem Phys 83(2):735–746CrossRefGoogle Scholar
  34. 34.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2012) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 64:4–17CrossRefGoogle Scholar
  35. 35.
    Hughes JD, Blagg J, Price DA, Bailey S, DeCrescenzo GA, Devraj RV, Ellsworth E, Fobian YM, Gibbs ME, Gilles RW (2008) Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorg Med Chem Lett 18(17):4872–4875CrossRefGoogle Scholar
  36. 36.
    Veber DF, Johnson SR, Cheng H-Y, Smith BR, Ward KW, Kopple KD (2002) Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 45(12):2615–2623CrossRefGoogle Scholar
  37. 37.
    Bender A, Scheiber J, Glick M, Davies JW, Azzaoui K, Hamon J, Urban L, Whitebread S, Jenkins JL (2007) Analysis of pharmacology data and the prediction of adverse drug reactions and off-target effects from chemical structure. ChemMedChem 2(6):861–873Google Scholar
  38. 38.
    Xie L, Xie L, Bourne PE (2011) Structure-based systems biology for analyzing off-target binding. Curr Opin Struct Biol 21(2):189–199CrossRefGoogle Scholar
  39. 39.
    Ahmed H, Alsadek DMM (2015) Galectin-3 as a potential target to prevent cancer metastasis. Clin Med Insights Oncol 9:113–121Google Scholar
  40. 40.
    Nakahara S, Oka N, Raz A (2005) On the role of galectin-3 in cancer apoptosis. Apoptosis 10(2):267–275Google Scholar
  41. 41.
    Song L, Tang J, Owusu L, Sun M-Z, Wu J, Zhang J (2014) Galectin-3 in cancer. Clin Chim Acta 431:185–191CrossRefGoogle Scholar
  42. 42.
    Folkman J (1992) The role of angiogenesis in tumor growth. Semin Cancer Biol 3(2):65–71Google Scholar
  43. 43.
    Gasparini G, Longo R, Toi M, Ferrara N (2005) Angiogenic inhibitors: a new therapeutic strategy in oncology. Nat Clin Pract Oncol 2:562CrossRefGoogle Scholar
  44. 44.
    Seetharaman J, Kanigsberg A, Slaaby R, Leffler H, Barondes SH, Rini JM (1998) X-ray crystal structure of the human galectin-3 carbohydrate recognition domain at 2.1-Å resolution. J Biol Chem 273(21):13047–13052Google Scholar
  45. 45.
    Akahani S, Nangia-Makker P, Inohara H, Kim H-RC, Raz A (1997) Galectin-3: a novel antiapoptotic molecule with a functional BH1 (NWGR) domain of Bcl-2 family. Cancer Res 57(23):5272–5276Google Scholar
  46. 46.
    Dumic J, Dabelic S, Flögel M (2006) Galectin-3: an open-ended story. Biochim Biophys Acta 1760(4):616–635Google Scholar
  47. 47.
    Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci 98(18):10037–10041CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of ChemistryUniversity of Sri JayewardenepuraNugegodaSri Lanka

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