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Pregled bibliografske jedinice broj: 1201769

Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy


Jeličić, Mario-Livio; Kovačić, Jelena; Cvetnić, Matija; Mornar, Ana; Amidžić Klarić, Daniela
Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy // Pharmaceuticals, 15 (2022), 7; 791, 13 doi:10.3390/ph15070791 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1201769 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy

Autori
Jeličić, Mario-Livio ; Kovačić, Jelena ; Cvetnić, Matija ; Mornar, Ana ; Amidžić Klarić, Daniela

Izvornik
Pharmaceuticals (1424-8247) 15 (2022), 7; 791, 13

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
pharmaceuticals ; antioxidative activity ; DPPH ; HPLC ; QSAR prediction

Sažetak
Since oxidative stress has been linked to several pathological conditions and diseases, drugs with additional antioxidant activity can be beneficial in the treatment of these diseases. Therefore, this study takes a new look at the antioxidant activity of frequently prescribed drugs using the HPLC‐DPPH method. The antioxidative activity expressed as the TEAC value of 82 drugs was successfully determined and is discussed in this work. Using the obtained values, the QSAR model was developed to predict the TEAC based on the selected molecular descriptors. The results of QSAR modeling showed that four‐ and seven‐variable models had the best potential for TEAC prediction. Looking at the statistical parameters of each model, the four‐variable model was superior to sevenvariable. The final model showed good predicting power (r = 0.927) considering the selected descriptors, implying that it can be used as a fast and economically acceptable evaluation of antioxidative activity. The advantage of such model is its ability to predict the antioxidative activity of a drug regardless of its structural diversity or therapeutic classification.

Izvorni jezik
Engleski

Znanstvena područja
Kemija, Farmacija



POVEZANOST RADA


Projekti:
UIP-2017-05-3949 - Razvoj naprednih analitičkih metoda za lijekove i biološki aktivne tvari u liječenju upalnih bolesti crijeva (IBDAnalytics) (Mornar Turk, Ana, HRZZ - 2017-05) ( CroRIS)

Ustanove:
Farmaceutsko-biokemijski fakultet, Zagreb,
Fakultet kemijskog inženjerstva i tehnologije, Zagreb

Poveznice na cjeloviti tekst rada:

doi dx.doi.org www.mdpi.com

Citiraj ovu publikaciju:

Jeličić, Mario-Livio; Kovačić, Jelena; Cvetnić, Matija; Mornar, Ana; Amidžić Klarić, Daniela
Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy // Pharmaceuticals, 15 (2022), 7; 791, 13 doi:10.3390/ph15070791 (međunarodna recenzija, članak, znanstveni)
Jeličić, M., Kovačić, J., Cvetnić, M., Mornar, A. & Amidžić Klarić, D. (2022) Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy. Pharmaceuticals, 15 (7), 791, 13 doi:10.3390/ph15070791.
@article{article, author = {Jeli\v{c}i\'{c}, Mario-Livio and Kova\v{c}i\'{c}, Jelena and Cvetni\'{c}, Matija and Mornar, Ana and Amid\v{z}i\'{c} Klari\'{c}, Daniela}, year = {2022}, pages = {13}, DOI = {10.3390/ph15070791}, chapter = {791}, keywords = {pharmaceuticals, antioxidative activity, DPPH, HPLC, QSAR prediction}, journal = {Pharmaceuticals}, doi = {10.3390/ph15070791}, volume = {15}, number = {7}, issn = {1424-8247}, title = {Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy}, keyword = {pharmaceuticals, antioxidative activity, DPPH, HPLC, QSAR prediction}, chapternumber = {791} }
@article{article, author = {Jeli\v{c}i\'{c}, Mario-Livio and Kova\v{c}i\'{c}, Jelena and Cvetni\'{c}, Matija and Mornar, Ana and Amid\v{z}i\'{c} Klari\'{c}, Daniela}, year = {2022}, pages = {13}, DOI = {10.3390/ph15070791}, chapter = {791}, keywords = {pharmaceuticals, antioxidative activity, DPPH, HPLC, QSAR prediction}, journal = {Pharmaceuticals}, doi = {10.3390/ph15070791}, volume = {15}, number = {7}, issn = {1424-8247}, title = {Antioxidant activity of pharmaceuticals: Predictive QSAR modeling for potential therapeutic strategy}, keyword = {pharmaceuticals, antioxidative activity, DPPH, HPLC, QSAR prediction}, chapternumber = {791} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Uključenost u ostale bibliografske baze podataka::


  • CA Search (Chemical Abstracts)


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