Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers

Acrylic acid derivatives are extensively utilized as initial monomers in dental materials. Nevertheless, these substances exhibit cytotoxicity towards different cell types, a phenomenon that must be reduced in future materials. The primary objective of this research is to establish a QSAR model for...

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Main Authors: Bošković Mirjana, Stanković Saša, Živković Jelena V., Veselinović Aleksandar M.
Format: Article
Language:English
Published: Serbian Chemical Society 2025-01-01
Series:Journal of the Serbian Chemical Society
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Online Access:https://doiserbia.nb.rs/img/doi/0352-5139/2025/0352-51392400057B.pdf
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author Bošković Mirjana
Stanković Saša
Živković Jelena V.
Veselinović Aleksandar M.
author_facet Bošković Mirjana
Stanković Saša
Živković Jelena V.
Veselinović Aleksandar M.
author_sort Bošković Mirjana
collection DOAJ
description Acrylic acid derivatives are extensively utilized as initial monomers in dental materials. Nevertheless, these substances exhibit cytotoxicity towards different cell types, a phenomenon that must be reduced in future materials. The primary objective of this research is to establish a QSAR model for the prediction of cytotoxic effects and to identify molecular fragments and descriptors with mechanistic interpretations that play a role in cytotoxic effects. The Monte Carlo optimization technique employed QSAR models that are not reliant on conformation. These models utilized both molecular graph-based and SMILES-based descriptors. By employing a variety of statistical methodologies, an assessment of the predictive capabilities and resilience of the established QSAR models was achieved. The demonstrated numerical values used for their validation underscore the strong suitability of these QSAR models. The Monte Carlo optimization technique effectively identified molecular fragments represented in QSAR modeling through the use of SMILES notation, elucidating their impact on cytotoxicity, both positively and negatively. Given that the majority of molecular databases adhere to this molecular structure conformation, the featured QSAR models can serve as a rapid and precise screening tool for novel dental monomers.
format Article
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issn 0352-5139
1820-7421
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publishDate 2025-01-01
publisher Serbian Chemical Society
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series Journal of the Serbian Chemical Society
spelling doaj-art-2586845b174f441583bed0cae367d1fe2025-08-20T02:56:36ZengSerbian Chemical SocietyJournal of the Serbian Chemical Society0352-51391820-74212025-01-019019510710.2298/JSC240301057B0352-51392400057BMonte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomersBošković Mirjana0https://orcid.org/0000-0001-6192-6016Stanković Saša1https://orcid.org/0000-0001-7239-6110Živković Jelena V.2https://orcid.org/0000-0002-1130-2173Veselinović Aleksandar M.3https://orcid.org/0000-0001-9291-6654Department for Prosthetic Dentistry, Faculty of Medicine, University of Niš, Niš, SerbiaDepartment for Prosthetic Dentistry, Faculty of Medicine, University of Niš, Niš, SerbiaDepartmant of Chemistry, Faculty of Medicine, University of Niš, Niš, SerbiaDepartmant of Chemistry, Faculty of Medicine, University of Niš, Niš, SerbiaAcrylic acid derivatives are extensively utilized as initial monomers in dental materials. Nevertheless, these substances exhibit cytotoxicity towards different cell types, a phenomenon that must be reduced in future materials. The primary objective of this research is to establish a QSAR model for the prediction of cytotoxic effects and to identify molecular fragments and descriptors with mechanistic interpretations that play a role in cytotoxic effects. The Monte Carlo optimization technique employed QSAR models that are not reliant on conformation. These models utilized both molecular graph-based and SMILES-based descriptors. By employing a variety of statistical methodologies, an assessment of the predictive capabilities and resilience of the established QSAR models was achieved. The demonstrated numerical values used for their validation underscore the strong suitability of these QSAR models. The Monte Carlo optimization technique effectively identified molecular fragments represented in QSAR modeling through the use of SMILES notation, elucidating their impact on cytotoxicity, both positively and negatively. Given that the majority of molecular databases adhere to this molecular structure conformation, the featured QSAR models can serve as a rapid and precise screening tool for novel dental monomers.https://doiserbia.nb.rs/img/doi/0352-5139/2025/0352-51392400057B.pdfqsarcytotoxicitydental materialcomposite resinsmilesmonte carlo optimization
spellingShingle Bošković Mirjana
Stanković Saša
Živković Jelena V.
Veselinović Aleksandar M.
Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
Journal of the Serbian Chemical Society
qsar
cytotoxicity
dental material
composite resin
smiles
monte carlo optimization
title Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
title_full Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
title_fullStr Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
title_full_unstemmed Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
title_short Monte Carlo optimization based QSAR modeling of the cytotoxicity of acrylic acid-based dental monomers
title_sort monte carlo optimization based qsar modeling of the cytotoxicity of acrylic acid based dental monomers
topic qsar
cytotoxicity
dental material
composite resin
smiles
monte carlo optimization
url https://doiserbia.nb.rs/img/doi/0352-5139/2025/0352-51392400057B.pdf
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AT zivkovicjelenav montecarlooptimizationbasedqsarmodelingofthecytotoxicityofacrylicacidbaseddentalmonomers
AT veselinovicaleksandarm montecarlooptimizationbasedqsarmodelingofthecytotoxicityofacrylicacidbaseddentalmonomers