A Review on Procedure of QSAR Assessment in Organic Compounds As a Measure of Antioxidant Potentiality

Vinay Tomar

doi:10.55938/ijgasr.v1i1.2

Authors

Vinay Tomar Jiwaji University

DOI:

https://doi.org/10.55938/ijgasr.v1i1.2

Keywords:

QSAR Assessment, Organic Compounds, Anti-Oxidant Potentiality

Abstract

Chemical and biological properties of substances may be inferred from their more fundamental physical, chemical, and biological characteristics using QSAR models. An insilico model may be built using QSAR to anticipate the activity of novel molecules before they are synthesised, allowing the author to establish a quantifiable link between structure and behaviour. QSAR is a powerful tool. Although QSAR modelling is a computer area, medicinal chemists are the main users and ultimate assessors, especially when it comes to developing compounds with the necessary biological activity. Several studies were conducted in which medicinal chemists and cheminformaticians collaborated to discover new compounds with specific biological activity. This was done through the development of QSAR models and their use in virtual screening, followed by experimental verification. Despite the fact that QSAR methods have their own set of limitations, their use in molecular prediction and assessment has been effective due to a division of labour in which mathematical professionals ensured the greatest quality of models. The predictions also helped experimental chemists design and test compounds that were expected to be successful. This review is being developed and implemented to look into the development of the QSAR tool in the assessment of antioxidant potentiality for diverse organic chemicals found in our environment.

Downloads

Download data is not yet available.

References

A. Sapra, P. Kumar, S. Kakkar, B. Narasimhan: Synthesis, Antimicrobial Evaluation and QSAR Studies of p-hydroxy Benzoic Acid Derivatives. Drug Res (Stuttg). Issue-64(01). pp-7-22 2014. DOI: https://doi.org/10.1055/s-0033-1349866

P. Erzincan, Melek Türker Saçan, Basak Yuce-Dursun, Özkan Danış: QSAR models for antioxidant activity of new coumarin derivatives. SAR and QSAR in environmental research 26(7). 2015 DOI: https://doi.org/10.1080/1062936X.2015.1088571

N. Vashist, S. S. Sambi, P. Kumar, B. Narasimhan: Development of QSAR for Antimicrobial Activity of Substituted Benzimidazoles. Drug Res (Stuttg). Issue-65(05). pp-225-230. 2015. DOI: https://doi.org/10.1055/s-0034-1371828

João Luiz Baldim, Bianca Gonçalves Vasconcelos de Alcântara, Olívia da Silva Domingos, Marisi Gomes Soares, Ivo Santana Caldas, Rômulo Dias Novaes, Tiago Branquinho Oliveira, João Henrique Ghilardi Lago, and Daniela Aparecida Chagas-Paula: The Correlationbetween Chemical Structures and Antioxidant, Prooxidant, and Antitrypanosomatid Properties of Flavonoids. Oxidative Medicine and Cellular Longevity. 2017. DOI: https://doi.org/10.1155/2017/3789856

Bruno J. Neves, Rodolpho C. Braga, Cleber C. Melo-Filho, José Teófilo Moreira-Filho, Eugene N. Muratov, and Carolina HortaAndrade: QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery. Front. Pharmacol. 2018 DOI: https://doi.org/10.3389/fphar.2018.01275

Ikechukwu Ogadimma Alisi, Adamu Uzairu, Stephen Eyije Abechi, Sulaiman Ola Idris: Development of Predictive Antioxidant Models for 1,3,4-Oxadiazoles by Quantitative Structure Activity Relationship. Journal of the Turkish Society Chemistry. Issue-6(2). pp-103-114. 2019. DOI: https://doi.org/10.18596/jotcsa.406207

Sharma Mukesh, Ahuja Dharmendra: QSAR Studies of Flavonoids Derivatives for Antioxidant and Antimicrobial Activity. Journal of Drug Delivery and Therapeutics. 9(4. pp-765-773. 2019 DOI: https://doi.org/10.22270/jddt.v10i2-s.3965

Pablo R. Duchowicz, Nicolás A. Szewczuk, and Alicia B. Pomilio: QSAR studies of the antioxidant activity of anthocyanins. J Food Sci Technol. Issue-56(12): pp-5518–5530. 2019. DOI: https://doi.org/10.1007/s13197-019-04024-w

Asghari Gul, Zareen Akhter, Fouzia Perveen, Saima Kalsoom, Farzana L. Ansari, and Muhammad Siddiq: Molecular Docking and Quantitative Structure Activity Relationship (QSAR) Studies of Some Newly Synthesized Poly (Azomethine) Esters. International Journal of Polymer Science. 2019 DOI: https://doi.org/10.1155/2019/2103891

Іryna Drapak, Borys Zimenkovsky, Lina Perekhoda, Hanna Yeromina, Kateryna Lipakova, Inna Demchuk, Marina Rakhimova: QSAR-analysis of 1-[2-(R-phenylimino)- 4-methyl-3-(3-[morpholine-4-yl]propyl)-2,3-dihydro-1,3-thiazol-5-yl]ethane-1-one's derivatives as potential antioxidants. Pharmacia 66(1). pp-33–40. 2019 DOI: https://doi.org/10.3897/pharmacia.66.e35083

Wenli Yan, Guimei Lin, Rong Zhang, Zhen Lianga, Wenjuan Wu: Studies on the bioactivities and molecular mechanism of antioxidant peptides by 3D-QSAR, in vitro evaluation and molecular dynamic simulations. Food & Function. 2020 DOI: https://doi.org/10.1039/C9FO03018B

Maciej Spiegel, Karina Kapusta, Wojciech Kołodziejczyk, Julia Saloni, Beata ˙Zbikowska, Glake A. Hill, Zbigniew Sroka: Antioxidant Activity of Selected PhenolicAcids–Ferric Reducing Antioxidant Power Assayand QSAR Analysis of the Structural Features. Molecules. 2020 DOI: https://doi.org/10.3390/molecules25133088

Bambang Wijianto, Ritmaleni, Hari Purnomo, Arief Nurrochmad: Quantitative Structure Activity Relationship (QSAR) study and Biological evaluation on Mono-ketone analogs of Curcumin as Antioxidant. Research Journal of Pharmacy and Technology. Vol-13. Issue - 10. 2020 DOI: https://doi.org/10.5958/0974-360X.2020.00850.1

Ying Shi: Support vector regression-based QSAR models for prediction of antioxidant activity of phenolic compounds. Scientific Reports. Vol. 11. Article number: 8806. 2021 DOI: https://doi.org/10.1038/s41598-021-88341-1

Veronika Khairullina, Irina Safarova, Gulnaz Sharipova, Yuliya Martynova and Anatoly Gerchikov: QSAR Assessing the Efficiency of Antioxidants in theTermination of RadicalChain Oxidation Processes of Organic Compounds. Molecules 26(421). 2021. DOI: https://doi.org/10.3390/molecules26020421

Artem Cherkasov, Eugene N. Muratov, Denis Fourches, Alexandre Varnek, Igor I. Baskin, Mark Cronin, John Dearden, Paola Gramatica, Yvonne C. Martin, Roberto Todeschini, Viviana Consonni, Victor E. Kuz'min, Richard Cramer, Romualdo Benigni, Chihae Yang, James Rathman, Lothar Terfloth, Johann Gasteiger, Ann Richard, and Alexander Tropsha: QSAR Modeling: Where have you been? Where are you going to?. J Med Chem. 57(12). pp-4977–5010. 2014. DOI: https://doi.org/10.1021/jm4004285

Layla Abdel-Ilah, Elma Veljović, Lejla Gurbeta, Almir Badnjević: Applications of QSAR Study in Drug Design. International Journal of Engineering Research & Technology (IJERT). Vol. 6 Issue 06. 2017

Umma Muhammad, Adamu Uzairu, David Ebuka Arthur: Review on: quantitative structure activity relationship (QSAR) modeling. Journal of Analytical & Pharmaceutical Research. 2018. DOI: https://doi.org/10.15406/japlr.2018.07.00232

Rex Jeya Rajkumar S, Muthukumar Nadar MSA