3 Biotech

, 9:431 | Cite as

FlavoDb: a web-based chemical repository of flavonoid compounds

  • Baban S. Kolte
  • Sanjay R. Londhe
  • Kamini T. Bagul
  • Shristi P. Pawnikar
  • Mayuri B. Goundge
  • Rajesh N. Gacche
  • Rohan J. MeshramEmail author
Original Article


There are many online resources that focus on chemical diversity of natural compounds, but only handful of resources exist that focus solely on flavonoid compounds and integrate structural and functional properties; however, extensive collated flavonoid literature is still unavailable to scientific community. Here we present an open access database ‘FlavoDb’ that is focused on providing physicochemical properties as well as topological descriptors that can be effectively implemented in deducing large scale quantitative structure property models of flavonoid compounds. In the current version of database, we present data on 1, 19,400 flavonoid compounds, thereby covering most of the known structural space of flavonoid class of compounds. Moreover, effective structure searching tool presented here is expected to provide an interactive and easy-to-use tool for obtaining flavonoid-based literature and allied information. Data from FlavoDb can be freely accessed via its intuitive graphical user interface made available at following web address:


Phytochemicals Flavone Flavanones Isoflavones Neoflavonoids Topological descriptor Drug discovery QSPR Database 



We would like to thank Dr. Paul Thiessen and Dr. Evan Bolton, staff from NCBI Structure group for their continuous guidance and suggestion to obtain data on literature and MeSH titles from NCBI resource included in this study. We are also thankful to Dr. Sangeeta Sawant, Director, Bioinformatics Centre, SPPU, Pune for providing continuous encouragement and infrastructure for database development. We acknowledge Mr. Bhushan Solanki for critical suggestion during development of this resource. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Compliance with ethical standards:

Conflicts of interest

The authors declare no conflict of interest.


  1. Agrawal YO, Sharma PK, Shrivastava B, Ojha S, Upadhya HM, Arya DS, Goyal SN (2014) Hesperidin produces cardioprotective activity via PPAR-γ pathway in ischemic heart disease model in diabetic rats. PLoS One 9(11):e111212PubMedPubMedCentralGoogle Scholar
  2. Al-Ishaq RK, Abotaleb M, Kubatka P, Kajo K, Büsselberg D (2019) Flavonoids and their anti-diabetic effects: cellular mechanisms and effects to improve blood sugar levels. Biomolecules 9(9):430PubMedCentralGoogle Scholar
  3. Andrade-Ochoa S, Correa-Basurto J, Rodríguez-Valdez LM, Sánchez-Torres LE, Nogueda-Torres B, Nevárez-Moorillón GV (2018) In vitro and in silico studies of terpenes, terpenoids and related compounds with larvicidal and pupaecidal activity against Culex quinquefasciatus Say (Diptera: Culicidae). Chem Cent J 12(1):53PubMedPubMedCentralGoogle Scholar
  4. Bajaj S, Sambi SS, Madan AK (2005) Prediction of anti-inflammatory activity of Narylanthranilic acids: computational approach using refined Zagreb indices. Croat Chem Acta 78:165–174Google Scholar
  5. Bienfait B, Ertl P (2013) JSME: a free molecule editor in JavaScript. J Cheminform 5:24PubMedPubMedCentralGoogle Scholar
  6. Chang JH, Cheng CW, Yang YC, Chen WS, Hung WY, Chow JM, Chen PS, Hsiao M, Lee WJ, Chien MH (2018) Downregulating CD26/DPPIV by apigenin modulates the interplay between Akt and Snail/Slug signaling to restrain metastasis of lung cancer with multiple EGFR statuses. J Exp Clin Cancer Res 37(1):199PubMedPubMedCentralGoogle Scholar
  7. Chen Z, Miao H, Zhu Z, Zhang H, Huang H (2017) Daidzein induces apoptosis of non-small cell lung cancer cells by restoring STK 4/YAP 1 signaling. Int J Clin Exp Med 10:15205–15212Google Scholar
  8. Cho HJ, Ahn KC, Choi JY, Hwang SG, Kim WJ, Um HD, Park JK (2015) Luteolin acts as a radiosensitizer in non-small cell lung cancer cells by enhancing apoptotic cell death through activation of a p38/ROS/caspase cascade. Int J Oncol 46(3):1149–1158PubMedGoogle Scholar
  9. Chu J, Wang X, Bi H, Li L, Ren M, Wang J (2018) Dihydromyricetin relieves rheumatoid arthritis symptoms and suppresses expression of pro-inflammatory cytokines via the activation of Nrf2 pathway in rheumatoid arthritis model. Int Immunopharmacol 59:174–180PubMedGoogle Scholar
  10. Coe S, Collett J, Izadi H, Wade DT, Clegg M, Harrison JM, Buckingham E, Cavey A, DeLuca GC, Palace J, Dawes H (2018) A protocol for a randomised double-blind placebo-controlled feasibility study to determine whether the daily consumption of flavonoid-rich pure cocoa has the potential to reduce fatigue in people with relapsing and remitting multiple sclerosis (RRMS). Pilot Feasibility Stud 4:35PubMedPubMedCentralGoogle Scholar
  11. Congreve M, Carr R, Murray C, Jhoti H (2003) A ‘rule of three’ for fragment-based lead discovery? Drug Discov Today 8(19):876–877PubMedGoogle Scholar
  12. Cui J, Liu X, Chow LMC (2018) Flavonoids as P-gp inhibitors: a systematic review of SARs. Curr Med Chem. CrossRefPubMedGoogle Scholar
  13. Das D, Sarkar S, Bordoloi J, Wann SB, Kalita J, Manna P (2018) Daidzein, its effects on impaired glucose and lipid metabolism and vascular inflammation associated with type 2 diabetes. BioFactors 44(5):407–417PubMedGoogle Scholar
  14. Dearden JC (2017) Advances in QSAR. In: Roy K (ed) The use of topological indices in QSAR and QSPR modeling. Springer International Publishing, New York. CrossRefGoogle Scholar
  15. Dureja H, Gupta S, Madan AK (2008) Topological models for prediction of pharmacokinetic parameters of cephalosporins using random forest, decision tree and moving average analysis. Sci Pharm 76:377–394Google Scholar
  16. Egan WJ, Merz KM Jr, Baldwin JJ (2000) Prediction of drug absorption using multivariate statistics. J Med Chem 43(21):3867–3877PubMedGoogle Scholar
  17. Gacche RN, Shegokar HD, Gond DS, Yang Z, Jadhav AD (2011) Evaluation of selected flavonoids as antiangiogenic, anticancer, and radical scavenging agents: an experimental and in silico analysis. Cell Biochem Biophys 61(3):651–663PubMedGoogle Scholar
  18. Gacche RN, Meshram RJ, Shegokar HD, Gond DS, Kamble SS, Dhabadge VN, Utage BG, Patil KK, More RA (2015) Flavonoids as a scaffold for development of novel anti-angiogenic agents: an experimental and computational enquiry. Arch Biochem Biophys 577–578:35–48PubMedGoogle Scholar
  19. Gutman I, Trinajstic N (1972) Graph theory and molecular orbitals. Total p-electron energy of alternant hydrocarbons. Chem Phys Lett 17:535–538Google Scholar
  20. Halberstadt AL, Klein LM, Chatha M, Valenzuela LB, Stratford A, Wallach J, Nichols DE, Brandt SD (2018) Pharmacological characterization of the LSD analog N-ethyl-N-cyclopropyl lysergamide (ECPLA). Psychopharmacology. CrossRefPubMedGoogle Scholar
  21. Hann MM, Leach AR, Harper G (2001) Molecular complexity and its impact on the probability of finding leads for drug discovery. J Chem Inf Comput Sci 41:856–864PubMedGoogle Scholar
  22. Hansch C, Kurup A (2003) QSAR of chemical polarizability and nerve toxicity. 2. J Chem Inf Comput Sci 43:1647–1651PubMedGoogle Scholar
  23. Hariono M, Kamarulzaman EE, Wahab HA (2014) Computational design of dengue type-2 NS2B/NS3 protease inhibitor: 2D/3D QSAR of quinoline and its molecular docking. In: 3rd international conference on computation for science and technology (ICCST-3).
  24. Heller S, McNaught A, Stein S, Tchekhovskoi D, Pletnev I (2013) InChI—the worldwide chemical structure identifier standard. J Cheminform 5(1):7PubMedPubMedCentralGoogle Scholar
  25. Jadhav A, Ezhilarasan V, Prakash Sharma O, Pan A (2013) Clostridium-DT (DB): a comprehensive database for potential drug targets of Clostridium difficile. Comput Biol Med 43(4):362–367PubMedGoogle Scholar
  26. Jin CY, Park C, Hwang HJ, Kim GY, Choi BT, Kim WJ, Choi YH (2011) Naringenin up-regulates the expression of death receptor 5 and enhances TRAIL-induced apoptosis in human lung cancer A549 cells. Mol Nutr Food Res 55(2):300–309PubMedGoogle Scholar
  27. Jung UJ, Lee MK, Jeong KS, Choi MS (2004) The hypoglycemic effects of hesperidin and naringin are partly mediated by hepatic glucose-regulating enzymes in C57BL/KsJ-db/db mice. J Nutr 134(10):2499–2503PubMedGoogle Scholar
  28. Kenny PW, Montanari CA (2013) Inflation of correlation in the pursuit of drug-likeness. J Comput Aided Mol Des 27(1):1–13PubMedGoogle Scholar
  29. Kim EK, Kwon KB, Song MY, Han MJ, Lee JH, Lee YR, Lee JH, Ryu DG, Park BH, Park JW (2007) Flavonoids protect against cytokine-induced pancreatic beta-cell damage through suppression of nuclear factor kappaB activation. Pancreas 35(4):e1–e9PubMedGoogle Scholar
  30. Kinoshita T, Lepp Z, Kawai Y, Terao J, Chuman H (2006) An integrated database of flavonoids. BioFactors 26(3):179–188PubMedGoogle Scholar
  31. Kolte BS, Londhe SR, Solanki BR, Gacche RN, Meshram RJ (2018) FilTer BaSe: a web accessible chemical database for small compound libraries. J Mol Graph Model 80:95–103PubMedGoogle Scholar
  32. Li JM, Che CT, Lau CB, Leung PS, Cheng CH (2006) Inhibition of intestinal and renal Na+-glucose cotransporter by naringenin. Int J Biochem Cell Biol 38(5–6):985–995PubMedGoogle Scholar
  33. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46(1–3):3–26PubMedGoogle Scholar
  34. Loharch S, Bhutani I, Jain K, Gupta P, Sahoo DK, Parkesh R (2015) EpiDBase: a manually curated database for small molecule modulators of epigenetic landscape. Database (Oxford)Google Scholar
  35. Ma L, Peng H, Li K, Zhao R, Li L, Yu Y, Wang X, Han Z (2015) Luteolin exerts an anticancer effect on NCI-H460 human non-small cell lung cancer cells through the induction of Sirt1-mediated apoptosis. Mol Med Rep 12(3):4196–4202PubMedPubMedCentralGoogle Scholar
  36. Martin YC (2005) A bioavailability score. J Med Chem 48(9):3164–3170PubMedGoogle Scholar
  37. Martinez-Gonzalez AI, Díaz-Sánchez ÁG, de la Rosa LA, Bustos-Jaimes I, Alvarez-Parrilla E (2019) Inhibition of a-amylase by flavonoids: structure activity relationship (SAR). Spectrochim Acta A Mol Biomol Spectrosc 206:437–447Google Scholar
  38. Meshram RJ, Bagul KT, Pawnikar SP, Barage SH, Kolte BS, Gacche RN (2019) Known compounds and new lessons: structural and electronic basis of flavonoid-based bioactivities. J Biomol Struct Dyn 5:1–17Google Scholar
  39. O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR (2011) Open Babel: an open chemical toolbox. J Cheminform 3(1):33PubMedPubMedCentralGoogle Scholar
  40. Oprea TI (2000) Property distribution of drug-related chemical databases. J Comput Aided Mol Des 14(3):251–264PubMedGoogle Scholar
  41. Oprea TI, Davis AM, Teague SJ, Leeson PD (2001) Is there a difference between leads and drugs? A historical perspective. J Chem Inf Comput Sci 41(5):1308–1315PubMedGoogle Scholar
  42. Palanisamy N, Viswanathan P, Anuradha CV (2008) Effect of genistein, a soy isoflavone, on whole body insulin sensitivity and renal damage induced by a high-fructose diet. Ren Fail 30(6):645–654PubMedGoogle Scholar
  43. Panda S, Kar A (2007) Apigenin (4′,5,7-trihydroxyflavone) regulates hyperglycaemia, thyroid dysfunction and lipid peroxidation in alloxan-induced diabetic mice. J Pharm Pharmacol 59(11):1543–1548PubMedGoogle Scholar
  44. Patil KK, Gacche RN (2017) Inhibition of glycation and aldose reductase activity using dietary flavonoids: a lens organ culture studies. Int J Biol Macromol 98:730–738PubMedGoogle Scholar
  45. Patil KK, Meshram RJ, Gacche RN (2016) Effect of monohydroxylated flavonoids on glycation-induced lens opacity and protein aggregation. J Enzyme Inhib Med Chem 31(sup1):148–156PubMedGoogle Scholar
  46. Petitjean M (1992) Applications of the radius-diameter diagram to the classification of topological and geometrical shapes of chemical compounds. J Chem Inf Comput Sci 32:331–337Google Scholar
  47. Pu P, Gao DM, Mohamed S, Chen J, Zhang J, Zhou XY, Zhou NJ, Xie J, Jiang H (2012) Naringin ameliorates metabolic syndrome by activating AMP-activated protein kinase in mice fed a high-fat diet. Arch Biochem Biophys 518(1):61–70PubMedGoogle Scholar
  48. Ramteke P, Yadav UCS (2019) Hesperetin, a Citrus bioflavonoid, prevents IL-1β-induced inflammation and a cell proliferation in lung epithelial A549 cells. Indian J Exp Biol 57:7–14Google Scholar
  49. Rao N (1994) In graph theory. In: Forsythe G (ed) Basic graph theory. Prentice Hall, New DelhiGoogle Scholar
  50. Rengasamy KRR, Khan H, Gowrishankar S, Lagoa RJL, Mahomoodally FM, Khan Z, Suroowan S, Tewari D, Zengin G, Hassan STS, Pandian SK (2018) The role of flavonoids in autoimmune diseases: therapeutic updates. Pharmacol Ther. CrossRefPubMedGoogle Scholar
  51. Sharma V, Goswami R, Madan AK (1997) Eccentric connectivity index: a novel highly discriminating topological descriptor for structure-property and structure-activity studies. J Chem Inf Comput Sci 37:273–282Google Scholar
  52. Shi LM, Fan Y, Myers TG, O’Connor PM, Paull KD, Friend SH, Weinstein JN (1998) Mining the NCI anticancer drug discovery database: genetic function approximation for the QSAR study of anticancer ellipticine analogues. J Chem Inf Comput Sci 38:189–199PubMedGoogle Scholar
  53. Sonoki H, Tanimae A, Endo S, Matsunaga T, Furuta T, Ichihara K, Ikari A (2017) Kaempherol and luteolin decrease claudin-2 expression mediated by inhibition of stat3 in lung adenocarcinoma a549 cells. Nutrients 9(6):597PubMedCentralGoogle Scholar
  54. Thangapandian S, John S, Lee KW (2011) Genetic function approximation and bayesian models for the discovery of future HDAC8 inhibitors. IBC 3(15):1–11Google Scholar
  55. Tian T, Li J, Li B, Wang Y, Li M, Ma D, Wang X (2014) Genistein exhibits anti-cancer effects via down-regulating FoxM1 in H446 small-cell lung cancer cells. Tumour Biol 35(5):4137–4145PubMedGoogle Scholar
  56. Tungmunnithum D, Thongboonyou A, Pholboon A, Yangsabai A (2018) Flavonoids and other phenolic compounds from medicinal plants for pharmaceutical and medical aspects: an overview. Medicines (Basel) 5(3):93Google Scholar
  57. Valsecchi AE, Franchi S, Panerai AE, Rossi A, Sacerdote P, Colleoni M (2011) The soy isoflavone genistein reverses oxidative and inflammatory state, neuropathic pain, neurotrophic and vasculature deficits in diabetes mouse model. Eur J Pharmacol 650(2–3):694–702PubMedGoogle Scholar
  58. Veber DF, Johnson SR, Cheng HY, Smith BR, Ward KW, Kopple KD (2002) Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 45(12):2615–2623PubMedPubMedCentralGoogle Scholar
  59. Wang J, Huang S (2018) Fisetin inhibits the growth and migration in the A549 human lung cancer cell line via the ERK1/2 pathway. Exp Ther Med 15(3):2667–2673PubMedGoogle Scholar
  60. Yan A, Gasteiger J (2003) Prediction of aqueous solubility of organic compounds based on a 3D structure representation. J Chem Inf Comput Sci 43:429–434PubMedGoogle Scholar
  61. Yang Y, Engkvist O, Llinàs A, Chen H (2012) Beyond size, ionization state, and lipophilicity: influence of molecular topology on absorption, distribution, metabolism, excretion, and toxicity for druglike compounds. J Med Chem 55(8):3667–3677PubMedGoogle Scholar
  62. Yin Y, Chang DT, Grulke CM, Tan YM, Goldsmith MR, Velez RT (2014) Essential set of molecular descriptors for ADME prediction in drug and environmental chemical space. Research 1:996Google Scholar
  63. Yin H, Huang L, Ouyang T, Chen L (2018) Baicalein improves liver inflammation in diabetic db/db mice by regulating HMGB1/TLR4/NF-?B signaling pathway. Int Immunopharmacol 55:55–62PubMedGoogle Scholar
  64. Zalden P, Song L, Wu X, Huang H, Ahr F, Mücke OD, Reichert J, Thorwart M, Mishra PK, Welsch R, Santra R, Kärtner FX, Bressler C (2018) Molecular polarizability anisotropy of liquid water revealed by terahertz-induced transient orientation. Nat Commun 9(1):2142PubMedPubMedCentralGoogle Scholar
  65. Zhao Y, Abraham M, Zissimos A (2003) Fast calculation of van der Waals volume as a sum of atomic and bond contributions and its application to drug compounds. J Org Chem 68:7368PubMedGoogle Scholar

Copyright information

© King Abdulaziz City for Science and Technology 2019

Authors and Affiliations

  1. 1.Bioinformatics CentreSavitribai Phule Pune UniversityPuneIndia
  2. 2.Department of BiotechnologySavitribai Phule Pune UniversityPuneIndia
  3. 3.Institute of Biochemistry and Molecular Biology, Department of ChemistryUniversity of HamburgHamburgGermany
  4. 4.Center for BioinformaticsUniversity of KansasLawrenceUSA

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