Advertisement

Journal of Food Science and Technology

, Volume 56, Issue 12, pp 5518–5530 | Cite as

QSAR studies of the antioxidant activity of anthocyanins

  • Pablo R. DuchowiczEmail author
  • Nicolás A. Szewczuk
  • Alicia B. Pomilio
Original Article
  • 44 Downloads

Abstract

Through experimental information available from antioxidant assays of seventeen anthocyanins, and six common anthocyanidins, quantitative structure–activity relationships (QSAR) have been established in the present work. The antioxidant bioactivity has been predicted in three different lipid environments: emulsified and bulk oil (methyl linoleate) (in vitro tests) at concentrations of 50 and 250 μM, and 50 μM of the inhibitor, respectively, and in human LDL (low-density lipoprotein; “bad cholesterol”) (ex vivo test) at concentrations of 2.5, 10, and 25 μM of the inhibitor. Radical scavenging activity was predicted in the assay with the 1,1-diphenyl-2-picrylhydrazyl radical (DPPH·). The QSAR models developed for each test and concentration used allowed to obtain prospective information on the constitutional and topological molecular characteristics for anthocyanin/anthocyanidin compounds. Therefore, the antioxidant activity was predicted for twenty-one compounds with unknown experimental values, leading for some of them to a favorable predicted bioactivity.

Keywords

Anthocyanins Antioxidant activity Quantitative structure–activity relationships Molecular descriptors 

Notes

Acknowledgements

We thank the National Scientific and Technical Research Council of Argentina [Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina] (PIP0311) and Universidad de Buenos Aires (Argentina) for financial support; and Secretaría de Ciencia, Tecnología e Innovación Productiva (formerly Ministerio de Ciencia, Tecnología e Innovación Productiva) for electronic library facilities. N.A.S. thanks the Scientific Research Comission [Comisión de InvestigacionesCientíficas (CIC), La Plata city, Argentina] for a fellowship. A.B.P. and P.R.D. are Research Members of CONICET.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Supplementary material

13197_2019_4024_MOESM1_ESM.docx (179 kb)
Supplementary material 1 (DOCX 178 kb)

References

  1. ACD/ChemSketch (2016) www.acdlabs.com
  2. Bentz EN, Pomilio AB, Lobayan RM (2017) Donor–acceptor interactions as descriptors of the free radical scavenging ability of flavans and catechin. Comput Theor Chem 1110:14–24CrossRefGoogle Scholar
  3. Bonesi M, Leporini M, Tenuta MC, Tundis R (2019) The role of anthocyanins in drug discovery: recent developments. Curr Drug Discov Technol.  https://doi.org/10.2174/1570163816666190125152931 CrossRefPubMedGoogle Scholar
  4. Cherkasov A, Muratov EN, Fourches D, Varnek A, Baskin II, Cronin M, Dearden J, Gramatica P, Martin YC, Todeschini R, Consonni V, Kuz’min VE, Cramer R, Benigni R, Yang C, Rathman J, Terfloth L, Gasteiger J, Richard A, Tropsha A (2014) QSAR modeling: Where have you been? Where are you going to? J Med Chem 57:4977–5010CrossRefGoogle Scholar
  5. Chirico N, Gramatica P (2012) Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection. J Chem Inf Model 52:2044–2058CrossRefGoogle Scholar
  6. de Sousa Moraes LF, Sun X, Peluzio MDCG, Zhu MJ (2019) Anthocyanins/anthocyanidins and colorectal cancer: What is behind the scenes? Crit Rev Food Sci Nutr 59:59–71CrossRefGoogle Scholar
  7. Du H, Lai L, Wang F, Sun W, Zhang L, Li X, Wang L, Jiang L, Zheng Y (2018) Characterisation of flower colouration in 30 Rhododendron species via anthocyanin and flavonol identification and quantitative traits. Plant Biol (Stuttg) 20:121–129CrossRefGoogle Scholar
  8. Duchowicz PR (2018) Linear regression QSAR models for Polo-Like Kinase-1 Inhibitors. Cells 7:1–11CrossRefGoogle Scholar
  9. Duchowicz PR, Castro EA, Fernández FM (2006) Alternative algorithm for the search of an optimal set of descriptors in QSAR-QSPR studies. MATCH Commun Math Comput Chem 55:179–192Google Scholar
  10. Fujiwara Y, Kono M, Ito A, Ito M (2018) Anthocyanins in Perilla plants and dried leaves. Phytochemistry 147:158–166CrossRefGoogle Scholar
  11. Harborne JB, Williams CA (2000) Advances in flavonoid research since 1992. Phytochemistry 55:481–504CrossRefGoogle Scholar
  12. He J, Giusti MM (2010) Anthocyanins: natural colorants with health-promoting properties. Annu Rev Food Sci Technol 1:163–187CrossRefGoogle Scholar
  13. Hong H, Xie Q, Ge W, Qian F, Fang H, Shi L, Su Z, Perkin R, Tong W (2008) Mold(2), molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics. J Chem Inf Model 48:1337–1344CrossRefGoogle Scholar
  14. Jaganath IB, Crozier A (2010) Dietary flavonoids and phenolic compounds. In: Fraga CG (ed) Plant phenolics and human health: biochemistry, nutrition, and pharmacology. Wiley, HobokenGoogle Scholar
  15. Jiang X, Li X, Zhu C, Sun J, Tian L, Chen W, Bai W (2019) The target cells of anthocyanins in metabolic syndrome. Crit Rev Food Sci Nutr 59:921–946CrossRefGoogle Scholar
  16. Kähkönen MP, Heinonen M (2003) Antioxidant activity of anthocyanins and their aglycons. J Agric Food Chem 51:628–633CrossRefGoogle Scholar
  17. Kaurinovic B, Vastag D (2019) Flavonoids and phenolic acids as potential natural antioxidants. intechopen. Open access peer-reviewed chapter—online first.  https://doi.org/10.5772/intechopen.83731. https://www.intechopen.com/online-first/flavonoids-and-phenolic-acids-as-potential-natural-antioxidants. Accessed 10 June 2019Google Scholar
  18. Khan MS, Ali T, Kim MW, Jo MH, Chung JI, Kim MO (2019) Anthocyanins improve hippocampus-dependent memory function and prevent neurodegeneration via JNK/Akt/GSK3β signaling in LPS-treated adult mice. Mol Neurobiol 56:671–687CrossRefGoogle Scholar
  19. Krga I, Milenkovic D (2019) Anthocyanins: from sources and bioavailability to cardiovascular-health benefits and molecular mechanisms of action. J Agric Food Chem 67:1771–1783CrossRefGoogle Scholar
  20. Lavine BK, Davidson CE, Breneman C, Katt W, Sundling CM (2003) Electronic van der Waals surface property descriptors and genetic algorithms for developing structure-activity correlations in olfactory databases. J Chem Inf Comput Sci 43:1890–1905CrossRefGoogle Scholar
  21. Li S, Wu B, Fu W, Reddivari L (2019) The anti-inflammatory effects of dietary anthocyanins against ulcerative colitis. Int J Mol Sci.  https://doi.org/10.3390/ijms20102588 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Ma X, Ning S (2019) Cyanidin-3-glucoside attenuates the angiogenesis of breast cancer via inhibiting STAT3/VEGF pathway. Phytother Res 33:81–89CrossRefGoogle Scholar
  23. Mercader AG, Duchowicz PR, Fernández FM, Castro EA (2010) Replacement method and enhanced replacement method versus the genetic algorithm approach for the selection of molecular descriptors in QSPR/QSAR Theories. J Chem Inf Model 50:1542–1548CrossRefGoogle Scholar
  24. Mercader AG, Duchowicz PR, Sivakumar PM (eds) (2016) Chemometrics applications and research: QSAR in medicinal chemistry. CRC Press, Boca RatonGoogle Scholar
  25. Miguel MG (2011) Anthocyanins: antioxidant and/or anti-inflammatory activities. J Appl Pharm Sci 1:7–15Google Scholar
  26. Pomilio AB, Mercader AG (2017) Natural acylated anthocyanins and other related flavonoids: structure elucidation of Ipomoea cairica compounds and QSAR studies including multidrug resistance. In: Atta-ur-Rahman D (ed) Studies in natural products chemistry. (Bioactive natural products). Elsevier, The Netherlands, pp 291–321Google Scholar
  27. Roy K, Chakraborty P, Mitra I, Ojha PK, Kar S, Das RN (2013) Some case studies on application of ‘‘r2 m’’ metrics for judging quality of Quantitative Structure-Activity Relationship predictions: emphasis on scaling of response data. J Comput Chem 34:1071–1082CrossRefGoogle Scholar
  28. Roy K, Kar S, Ambure P (2015) On a simple approach for determining applicability domain of QSAR models. Chemom Intell Lab Syst 145:22–29CrossRefGoogle Scholar
  29. Sakuta M (2014) Diversity in plant red pigments: anthocyanins and betacyanins. Plant Biotechnol Rep 8:37–48CrossRefGoogle Scholar
  30. Sousa A, Araújo P, Azevedo J, Cruz L, Fernandes I, Mateus N, de Freitas V (2016) Antioxidant and antiproliferative properties of 3-deoxyanthocyanidins. Food Chem 192:142–148CrossRefGoogle Scholar
  31. Thankam Finosh G, Jayabalan M (2013) Reactive oxygen species—control and management using amphiphilic biosynthetic hydrogels for cardiac applications. Adv Biosci Biotechnol 4:1134–1146CrossRefGoogle Scholar
  32. Tsakiroglou P, VandenAkker NE, Del Bo’ C, Riso P, Klimis-Zacas D (2019) Role of berry anthocyanins and phenolic acids on cell migration and angiogenesis: an updated overview. Nutrients.  https://doi.org/10.3390/nu11051075 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Ullah R, Khan M, Shah SA, Saeed K, Kim MO (2019) Natural antioxidant anthocyanins—a hidden therapeutic candidate in metabolic disorders with major focus in neurodegeneration. Nutrients.  https://doi.org/10.3390/nu11061195 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Valdes-Martini JR, García Jacas CR, Marrero-Ponce Y, Silveira Vaz‘d Almeida Y, Morrel C (2012) Versión 1.0. CAMD-BIR Unit, CENDA Number of register: 2373-2012Google Scholar
  35. Vishnu VR, Renjith RS, Mukherjee A, Anil SR, Sreekumar J, Jyothi AN (2019) Comparative study on the chemical structure and in vitro antiproliferative activity of anthocyanins in purple root tubers and leaves of sweet potato (Ipomoea batatas). J Agric Food Chem 67:2467–2475CrossRefGoogle Scholar
  36. Vitale AA, Bernatene EA, Vitale MG, Pomilio AB (2016) New insights of the Fenton reaction using glycerol as experimental model. Effect of O2, inhibition by Mg2+, and oxidation state of Fe. J Phys Chem A 120:5435–5445CrossRefGoogle Scholar
  37. Wongwichai T, Teeyakasem P, Pruksakorn D, Kongtawelert P, Pothacharoen P (2019) Anthocyanins and metabolites from purple rice inhibit IL-1β-induced matrix metalloproteinases expression in human articular chondrocytes through the NF-κB and ERK/MAPK pathway. Biomed Pharmacother 112:108610CrossRefGoogle Scholar
  38. Zhang ZC, Zhou Q, Yang Y, Wang Y, Zhang JL (2019) Highly acylated anthocyanins from purple sweet potato (Ipomoea batatas L.) alleviate hyperuricemia and kidney inflammation in hyperuricemic mice: possible attenuation effects on allopurinol. J Agric Food Chem 67:6202–6211CrossRefGoogle Scholar

Copyright information

© Association of Food Scientists & Technologists (India) 2019

Authors and Affiliations

  • Pablo R. Duchowicz
    • 1
    Email author
  • Nicolás A. Szewczuk
    • 1
  • Alicia B. Pomilio
    • 2
  1. 1.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), CONICETUniversidad Nacional de La Plata (UNLP)La PlataArgentina
  2. 2.Laboratorio de Química y Bioquímica Estructural, Departamento de Bioquímica Clínica, Hospital de Clínicas “José de San Martín”Universidad de Buenos AiresBuenos AiresArgentina

Personalised recommendations