Development a QSAR Model of 1,3,4-Triazole Derivatives for Antioxidant Activity Prediction

Aims and Objectives: The aim of this study was to derive robust and reliable QSAR models for clarification and prediction of antioxidant activity of 43 heterocyclic and Schiff bases dipicolinic acid derivatives. According to the best obtained QSAR model, structures of new compounds with possible great activities should be proposed. Methods: Molecular descriptors were calculated by DRAGON and ADMEWORKS from optimized molecular structure and two algorithms were used for creating the training and test sets in both set of descriptors. Regression analysis and validation of models were performed using QSARINS. Results: The model with best internal validation result was obtained by DRAGON descriptors (MATS4m, EEig03d, BELm4, Mor10p), split by ranking method (R2 = 0.805; R2 ext = 0.833; F = 30.914). The model with best external validation result was obtained by ADMEWORKS descriptors (NDB, MATS5p, MDEN33, TPSA), split by random method (R2 = 0.692; R2 ext = 0.848; F = 16.818). Conclusion: Important structural requirements for great antioxidant activity are: low number of double bonds in molecules; absence of tertial nitrogen atoms; higher number of hydrogen bond donors; enhanced molecular polarity; and symmetrical moiety. Two new compounds with potentially great antioxidant activities were proposed.

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Synthesis, Antiproliferative and Antioxidant Activity of 3-Mercapto-1,2,4-Triazole Derivatives as Combretastatin A-4 Analogues

Pharmaceutical Chemistry Journal ◽

10.1007/s11094-021-02459-0 ◽

2021 ◽

Author(s):

Sadiq Al-Mansury ◽

Asim A. Balakit ◽

Fatin Fadhel Alkazazz ◽

Rana A. Ghaleb

Keyword(s):

Antioxidant Activity ◽

Triazole Derivatives

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Theoretical Bioevaluation of 1,2,4-Thiadiazole-1,2,4-triazole Derivatives via Molecular Modelling Approach

Asian Journal of Organic & Medicinal Chemistry ◽

10.14233/ajomc.2021.ajomc-p307 ◽

2021 ◽

Vol 6 (1) ◽

pp. 40-46

Author(s):

Oyebamiji Abel Kolawole ◽

Akintelu Sunday Adewale ◽

Simon N. Odoemene ◽

Oyeneyin Oluwatoba Emmanuel ◽

Semire Banjo

Keyword(s):

Breast Cancer ◽

Docking Study ◽

Qsar Model ◽

Qsar Study ◽

Triazole Derivatives ◽

Discovery Studio ◽

Artificial Neural Network Ann ◽

Type 3 ◽

Better Than ◽

Modelling Approach

Breast cancer still remains one of the precarious ailments among humans globally. The vulnerability of this ailment in homeopathic world remains colossal and this has drawn the attention of seasoned researchers to find lasting solution to this hazard. Therefore, 10 novel 1,2,4-thiadiazole-1,2,4-triazole derivatives were studied so as to explore their anti-breast cancer activities. The studied compounds were optimized using Spartan 14 and the QSAR study was executed by using Gretl and MATLAB. Also, docking study was observed using Pymol (for treating downloaded protein), Autodock Tool (for locating binding site in the downloaded protein and for converting ligand and receptor to .pdbqt format from .pdb format), Auto dock vina (for docking calculation) and discovery studio (for viewing the nonbonding interaction between the docked complexes). The selected descriptors were used to developed effective QSAR model and it was observed that the developed QSAR model using artificial neural network (ANN) predicted better than the prediction made by multiple linear regression (MLR). More so, the calculated binding affinity revealed that compound g (-11.4 kcal/mol) possess ability to inhibit 3α-hydroxysteroid dehydrogenase type 3 (PDB ID: 4xo6) than other studied compounds as well as etoposide (Standard).

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Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction

International Journal of Molecular Sciences ◽

10.3390/ijms161025353 ◽

2015 ◽

Vol 16 (10) ◽

pp. 25353-25376 ◽

Cited By ~ 16

Author(s):

Anna Torkova ◽

Olga Koroleva ◽

Ekaterina Khrameeva ◽

Tatyana Fedorova ◽

Mikhail Tsentalovich

Keyword(s):

Antioxidant Activity ◽

Functional Study ◽

Activity Prediction

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Varietal classification and antioxidant activity prediction of Osmanthus fragrans Lour. flowers using UPLC–PDA/QTOF–MS and multivariable analysis

Food Chemistry ◽

10.1016/j.foodchem.2016.08.125 ◽

2017 ◽

Vol 217 ◽

pp. 490-497 ◽

Cited By ~ 16

Author(s):

Fei Zhou ◽

Jiyu Peng ◽

Yajing Zhao ◽

Weisu Huang ◽

Yirong Jiang ◽

...

Keyword(s):

Antioxidant Activity ◽

Multivariable Analysis ◽

Activity Prediction ◽

Osmanthus Fragrans ◽

Varietal Classification

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Supercritical Antisolvent Fractionation of Antioxidant Compounds from Salvia officinalis

International Journal of Molecular Sciences ◽

10.3390/ijms22179351 ◽

2021 ◽

Vol 22 (17) ◽

pp. 9351

Author(s):

Raquel Mur ◽

Juan I. Pardo ◽

M. Rosa Pino-Otín ◽

José S. Urieta ◽

Ana M. Mainar

Keyword(s):

Antioxidant Activity ◽

Rosmarinic Acid ◽

Supercritical Co2 ◽

Qsar Model ◽

Salvia Officinalis ◽

Training Dataset ◽

Antioxidant Compounds ◽

Supercritical Antisolvent ◽

Pure Compounds ◽

Co2 Flow

The increasing interest towards greener antioxidants obtained via natural sources and more sustainable processes encourages the development of new theoretical and experimental methods in the field of those compounds. Two advanced separation methods using supercritical CO2 are applied to obtain valuable antioxidants from Salvia officinalis, and a first approximation to a QSAR model relating molecular structure with antioxidant activity is explored in order to be used, in the future, as a guide for the preselection of compounds of interest in these processes. Separation experiments through antisolvent fractionation with supercritical CO2 were designed using a Response Surface Methodology to study the effect of pressure and CO2 flow rate on both mass yields and capability to obtain fractions enriched in three antioxidant compounds: chlorogenic acid, caffeic acid and rosmarinic acid which were tracked using HPLC PDA. Rosmarinic acid was completely retained in the precipitation vessel while chlorogenic and caffeic acids, though distributed between the two separated fractions, had a major presence in the precipitation vessel too. The conditions predicted for an optimal overall yield and enrichment were 148 bar and 10 g/min. Although a training dataset including much more compounds than those now considered can be recommended, descriptors calculated from the σ-profiles provided by COSMO-RS model seem to be adequate for estimating the antioxidant activity of pure compounds through QSAR.

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