Quantitative Structure-Antioxidant Activity Relationship of Quercetin and its New Synthetised Derivatives

Open access

Quantitative Structure-Antioxidant Activity Relationship of Quercetin and its New Synthetised Derivatives

Interest in the biological activity of the flavonoids increases due to the potential health benefits of these polyphenolic components of foodstuff. Our research investigates biological properties of the flavonoids and their new synthetized derivatives, focuses on the relationship between their antioxidant activity and their chemical structures.

Quantitative structure-activity relationship (QSAR) attempts to correlate chemical structure with biological activity using statistical approaches. It is the process by which chemical structure of a molecule is quantitatively correlated with a well defined process, such as biological activity, that can be expressed quantitatively as the concentration of a substance required to give a certain biological response. When physicochemical properties or structures are expressed by numbers, the mathematical relation can be formed between the two. The mathematical expression can then be used to predict the biological response of other chemical compounds.

QSARs represent predictive models derived from application of statistical tools correlating antioxidant activity (including desirable therapeutic effect and undesirable side effects) of chemicals with descriptors representative of molecular structure and properties. Obtaining a good QSAR model depends on many factors, such as the quality of biological data, the choice of descriptors and statistical methods. Any QSAR modeling should ultimately lead to statistically robust models capable of making accurate and reliable predictions of biological activities of new untested compounds.

If the inline PDF is not rendering correctly, you can download the PDF file here.

  • BOCAZ-BENEVENTI G. LATORRE R. FARKOVÁ M. HAVEL J.: Artificial neural networks for quantification in unresolved capillary electrophoresis peaks. Anal. Chim. Acta 452 2002 47-63.

  • CABALLERO J.: 3D-QSAR (CoMFA and CoMSIA) and pharmacophore (GALAHAD) studies on the differential inhibition of aldose reductase by flavonoid compounds. J. Molec. Graph. Model. 29 2010 363-371.

  • CONSONNI V. BALLABIO D. TODESCHINI R.: Evaluation of model predictive ability by external validation techniques. J. Chemometr. 24 2010 194-201.

  • DAWIDOWICZ A.L. WIANOWSKA D. OLSZOWY M.: On practical problems in estimation of antioxidant activity of compounds by DPPH method (Problems in estimation of antioxidant activity). Food Chem. 131 2012 1037-1043.

  • DUTHIE S.J. COLLINS A.R. DUTHIE G.G. DOBSON V.L.: Quercetin and myricetin protect against hydrogen peroxide-induced DNA damage (strand breaks and oxidised pyrimidines) in human lymphocytes. Mutat. Res. 393 1997 223-231.

  • FAN D. ZHOU X. ZHAO CH. CHEN H. ZHAO Y. GONG X.: Anti-inflammatory antiviral and quantitative study of quercetin-3-O-β-D-glucuronide in Polygonum perfoliatum L. Fitoterapia 82 2011 805-810.

  • FLOEGEL A. KIM D.-O. CHUNG S.-J. KOO S.I. CHUN O.K.: Comparison of ABTS/DPPH assays to measure antioxidant capacity in popular antioxidant-rich US foods. J. Food Comp. Anal. 24 2011 1043-1048.

  • GASTEIGER J.: The central role of chemoinformatics. Chem. Int. Lab. Sys. 82 2006 200-209.

  • KARTASASMITA R.E. HEROWATI R. GUSDINAR T.: Docking study of quercetin derivatives on inducible nitric oxide synthase and prediction of their absorption and distribution properties. J. App. Sci. 23 2009 3098-3104.

  • KRUZLICOVA D. MOCAK J. BALLA B. PETKA J. FARKOVA M. HAVEL J.: Classification of Slovak white wines using artificial neural networks and discriminant techniques. Food Chem. 112 2009 1046-1052.

  • KVASNIČKA V. BEŇUŠKOVÁ Ľ. POSPÍCHAL J. FARKAŠ I. TIŇO P. & KRÁĽ A.: Introduction to theory of neural networks. IRIS Publisher Bratislava 1999.

  • MARKOVITS J. LINASSIER C. FOSSE P. COUPRIE J. PIERRE J. JACQUEMIN-SABLON A. SAUCIER J.M. LE PECQ J.B. LARSEN A.K.: Inhibitory effects of the tyrosine kinase inhibitor genistein on mammalian DNA topoisomerase II Cancer Res. 49 1989 5111-5117.

  • NEMEČEK P. ĎURČEKOVÁ T. MOCÁK J. LEHOTAY J. WAISSER K.: Štúdium vzťahov medzi biologickou aktivitou a fyzikálnochemickými vlastnosťami potenciálnych antituberkulotík. Nova Biotechnol. VI-I 2006 37-47.

  • PICK A. MÜLLER H. MAYER R. HAENISCH B. PAJEVA K.I. WEIGT M. BÖNISCH H. MÜLLER E.CH. WIESE M.: Structure-activity relationships of flavonoids as inhibitors of breast cancer resistance protein (BCRP). Bioorg. Med. Chem. 19 2011 2090-2102.

  • SKAPER S.D. FABRIS M. FERRARI V. DALLE CARBONARE M. LEON A.: Quercetin protects cutaneous tissue-associated cell types including sensory neurons from oxidative stress induced by glutathione depletion: cooperative effects of ascorbic acid. Free Radic. Biol. Med. 22 1997 669-678.

  • TIAN X.-J. YANG X.-W. YANG X. WANG K.: Studies of intestinal permeability of 36 flavonoids using Caco-2 cell monolayer model. Int. J. Pharm. 367 2009 58-64.

  • THAKUR A. VISHWAKARMA S. THAKUR M.: QSAR study of flavonoid derivatives as p56lck tyrosinkinase inhibitors. Bioorg. Med. Chem. 12 2004 1209-1214.

  • TODESCHINI R. CONSONNI V. GRAMATICA P.: 4.05 - Chemometrics in QSAR. Comprehensive Chemometrics. Chemical and Biochemical Data Analysis Vol. 4 2009 129-172.

Search
Journal information
Impact Factor


CiteScore 2018: 0.68

SCImago Journal Rank (SJR) 2018: 0.173
Source Normalized Impact per Paper (SNIP) 2018: 0.288


Cited By
Metrics
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 386 111 2
PDF Downloads 145 52 1