Literature DB >> 33466934

QSAR Assessing the Efficiency of Antioxidants in the Termination of Radical-Chain Oxidation Processes of Organic Compounds.

Veronika Khairullina1, Irina Safarova1, Gulnaz Sharipova1, Yuliya Martynova1, Anatoly Gerchikov1.   

Abstract

Using the GUSAR 2013 program, the quantitative structure-antioxidant activity relationship has been studied for 74 phenols, aminophenols, aromatic amines and uracils having lgk7 = 0.01-6.65 (where k7 is the rate constant for the reaction of antioxidants with peroxyl radicals generated upon oxidation). Based on the atomic descriptors (Quantitative Neighborhood of Atoms (QNA) and Multilevel Neighborhoods of Atoms (MNA)) and molecular (topological length, topological volume and lipophilicity) descriptors, we have developed 9 statistically significant QSAR consensus models that demonstrate high accuracy in predicting the lgk7 values for the compounds of training sets and appropriately predict lgk7 for the test samples. Moderate predictive power of these models is demonstrated using metrics of two categories: (1) based on the determination coefficients R2 (R2TSi, R20, Q2(F1), Q2(F2), RmTSi2¯) and based on the concordance correlation coefficient (CCC)); or (2) based on the prediction lgk7 errors (root mean square error (RMSEP), mean absolute error (MAE) and standard deviation (S.D.)) The RBF-SCR method has been used for selecting the descriptors. Our theoretical prognosis of the lgk7 for 8-PPDA, a known antioxidant, based on the consensus models well agrees with the experimental value measure in the present work. Thus, the algorithms for calculating the descriptors implemented in the GUSAR 2013 program allow simulating kinetic parameters of the reactions underling the liquid-phase oxidation of hydrocarbons.

Entities:  

Keywords:  GUSAR 2013 program; MNA descriptors; QNA descriptors; QSAR models; antioxidant activity; antioxidants

Mesh:

Substances:

Year:  2021        PMID: 33466934      PMCID: PMC7830365          DOI: 10.3390/molecules26020421

Source DB:  PubMed          Journal:  Molecules        ISSN: 1420-3049            Impact factor:   4.411


  33 in total

1.  Phenolic antioxidants: electrochemical behavior and the mechanistic elements underlying their anodic oxidation reaction.

Authors:  Zhiyong Cheng; Jie Ren; Yuanzong Li; Wenbao Chang; Zhida Chen
Journal:  Redox Rep       Date:  2002       Impact factor: 4.412

Review 2.  Antioxidant Activity/Capacity Measurement. 1. Classification, Physicochemical Principles, Mechanisms, and Electron Transfer (ET)-Based Assays.

Authors:  Reşat Apak; Mustafa Özyürek; Kubilay Güçlü; Esra Çapanoğlu
Journal:  J Agric Food Chem       Date:  2016-01-27       Impact factor: 5.279

3.  Real external predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient.

Authors:  Nicola Chirico; Paola Gramatica
Journal:  J Chem Inf Model       Date:  2011-08-12       Impact factor: 4.956

4.  Quantitative prediction of antitarget interaction profiles for chemical compounds.

Authors:  Alexey V Zakharov; Alexey A Lagunin; Dmitry A Filimonov; Vladimir V Poroikov
Journal:  Chem Res Toxicol       Date:  2012-11-02       Impact factor: 3.739

Review 5.  Antioxidant polyphenols in cancer treatment: Friend, foe or foil?

Authors:  Gian Luigi Russo; Idolo Tedesco; Carmela Spagnuolo; Maria Russo
Journal:  Semin Cancer Biol       Date:  2017-05-13       Impact factor: 15.707

6.  Flavonoid antioxidants: chemistry, metabolism and structure-activity relationships.

Authors:  Kelly E. Heim; Anthony R. Tagliaferro; Dennis J. Bobilya
Journal:  J Nutr Biochem       Date:  2002-10       Impact factor: 6.048

7.  Free Radical Scavenging and Antioxidant Activities of Silymarin Components.

Authors:  Kevin P Anthony; Mahmoud A Saleh
Journal:  Antioxidants (Basel)       Date:  2013-12-10

8.  A Quantum Chemical and Statistical Study of Phenolic Schiff Bases with Antioxidant Activity against DPPH Free Radical.

Authors:  El Hassane Anouar
Journal:  Antioxidants (Basel)       Date:  2014-04-21

9.  On two novel parameters for validation of predictive QSAR models.

Authors:  Partha Pratim Roy; Somnath Paul; Indrani Mitra; Kunal Roy
Journal:  Molecules       Date:  2009-04-29       Impact factor: 4.411

10.  Comparison of Quantitative and Qualitative (Q)SAR Models Created for the Prediction of Ki and IC50 Values of Antitarget Inhibitors.

Authors:  Alexey A Lagunin; Maria A Romanova; Anton D Zadorozhny; Natalia S Kurilenko; Boris V Shilov; Pavel V Pogodin; Sergey M Ivanov; Dmitry A Filimonov; Vladimir V Poroikov
Journal:  Front Pharmacol       Date:  2018-10-10       Impact factor: 5.810

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  1 in total

1.  QSPR Modeling and Experimental Determination of the Antioxidant Activity of Some Polycyclic Compounds in the Radical-Chain Oxidation Reaction of Organic Substrates.

Authors:  Veronika Khairullina; Yuliya Martynova; Irina Safarova; Gulnaz Sharipova; Anatoly Gerchikov; Regina Limantseva; Rimma Savchenko
Journal:  Molecules       Date:  2022-10-02       Impact factor: 4.927

  1 in total

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