Support vector regression-guided unravelling: antioxidant capacity and quantitative structure-activity relationship predict reduction and promotion effects of flavonoids on acrylamide formation

Sci Rep. 2016 Sep 2:6:32368. doi: 10.1038/srep32368.

Abstract

We used the support vector regression (SVR) approach to predict and unravel reduction/promotion effect of characteristic flavonoids on the acrylamide formation under a low-moisture Maillard reaction system. Results demonstrated the reduction/promotion effects by flavonoids at addition levels of 1-10000 μmol/L. The maximal inhibition rates (51.7%, 68.8% and 26.1%) and promote rates (57.7%, 178.8% and 27.5%) caused by flavones, flavonols and isoflavones were observed at addition levels of 100 μmol/L and 10000 μmol/L, respectively. The reduction/promotion effects were closely related to the change of trolox equivalent antioxidant capacity (ΔTEAC) and well predicted by triple ΔTEAC measurements via SVR models (R: 0.633-0.900). Flavonols exhibit stronger effects on the acrylamide formation than flavones and isoflavones as well as their O-glycosides derivatives, which may be attributed to the number and position of phenolic and 3-enolic hydroxyls. The reduction/promotion effects were well predicted by using optimized quantitative structure-activity relationship (QSAR) descriptors and SVR models (R: 0.926-0.994). Compared to artificial neural network and multi-linear regression models, SVR models exhibited better fitting performance for both TEAC-dependent and QSAR descriptor-dependent predicting work. These observations demonstrated that the SVR models are competent for predicting our understanding on the future use of natural antioxidants for decreasing the acrylamide formation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acrylamide / chemistry*
  • Antioxidants / chemistry*
  • Flavonoids / chemistry*
  • Glycosides / chemistry*
  • Hydroxyl Radical / chemistry
  • Linear Models
  • Maillard Reaction
  • Oxidation-Reduction
  • Quantitative Structure-Activity Relationship
  • Support Vector Machine*

Substances

  • Antioxidants
  • Flavonoids
  • Glycosides
  • Acrylamide
  • Hydroxyl Radical