prikaz prve stranice dokumenta Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study
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Scientific paper - Original scientific paper
Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study
BioImpacts, 13 (2023), 5; 24180. https://doi.org/10.34172/bi.2023.24180
Novak, Jurica; Zykova, Alena R.; Potemkin, Vladimir A.; Sharutin, Vladimir V.; Sharutina, Olga K.

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Novak, J., Zykova, A. R., Potemkin, V. A., Sharutin, V. V. & Sharutina, O. K. (2023). Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study. BioImpacts, 13. (5). doi: 10.34172/bi.2023.24180

Novak, Jurica, et al. "Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study." BioImpacts, vol. 13, no. 5, 2023. https://doi.org/10.34172/bi.2023.24180

Novak, Jurica, Alena R. Zykova, Vladimir A. Potemkin, Vladimir V. Sharutin and Olga K. Sharutina. "Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study." BioImpacts 13, no. 5 (2023). https://doi.org/10.34172/bi.2023.24180

Novak, J., et al. (2023) 'Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study', BioImpacts, 13(5). doi: 10.34172/bi.2023.24180

Novak J, Zykova AR, Potemkin VA, Sharutin VV, Sharutina OK. Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study. BioImpacts [Internet]. 2023 [cited 2024 May 08];13(5). doi: 10.34172/bi.2023.24180

J. Novak, A. R. Zykova, V. A. Potemkin, V. V. Sharutin and O. K. Sharutina, "Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study", BioImpacts, vol. 13, no. 5, 2023. [Online]. Available at: https://urn.nsk.hr/urn:nbn:hr:193:073539. [Accessed: 08 May 2024]

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Metadata
Title (english)Platinum(IV) compounds as potential drugs: a quantitative structure-activity relationship study
AuthorJurica Novak
AuthorAlena R. Zykova https://orcid.org/0000-0001-6333-5551
AuthorVladimir A. Potemkin https://orcid.org/0000-0002-5244-8718
AuthorVladimir V. Sharutin
AuthorOlga K. Sharutina
Author's institutionUniversity of Rijeka
(Faculty of Biotechnology and Drug Development)
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Chemistry
Theoretical Chemistry
Abstract (english)
Introduction: Machine learning methods, coupled with a tremendous increase in computer power in recent years, are promising tools in modern drug design and drug repurposing. Methods: Machine learning predictive models, publicly available at chemosophia.com, were used to predict the bioactivity of recently synthesized platinum(IV) complexes against different kinds of diseases and medical conditions. Two novel QSAR models based on the BiS algorithm are developed and validated, capable to predict activities against the SARS-CoV virus and its RNA dependent RNA polymerase. Results: The internal predictive power of the QSAR models was tested by 10-fold cross-validation, giving cross-R2 from 0.863 to 0.903. 38 different activities, ranging from antioxidant, antibacterial, and antiviral activities, to potential anti-inflammatory, anti-arrhythmic and anti-malarial activity were predicted for a series of eighteen platinum(IV) complexes. Conclusion: Complexes 1, 3 and 13 have high generalized optimality criteria and are predicted as potential SARS-CoV RNA dependent RNA polymerase inhibitors.
Keywords (english)
Languageenglish
Publication typeScientific paper - Original scientific paper
Publication statusPublished
Peer reviewPeer review - international
Publication versionPublished version
Journal titleBioImpacts
Numberingvol. 13, no. 5, 24180
p-ISSN2228-5660
e-ISSN2228-5652
DOIhttps://doi.org/10.34172/bi.2023.24180
URN:NBNurn:nbn:hr:193:073539
Publication2023
Document URLhttps://bi.tbzmed.ac.ir/Inpress/bi-24180
Type of resourceText
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-07-12 09:09:03