The Application of Connected QSRR and QSAR Strategies to Predict the Physicochemical Interaction of Acridinone Derivatives with DNA

Author(s): Paulina Szatkowska-Wandas, Marcin Koba, Agata Kuchcicka, Sylwia Kurek, Emilia Daghir-Wojtkowiak, Tomasz Baczek.

Journal Name: Combinatorial Chemistry & High Throughput Screening

Volume 17 , Issue 10 , 2014

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Abstract:

Acridinone derivatives as imidazoacridinones and triazoloacridinones are the new potent antitumor agents characterized by different mechanisms of action related to their ability to interact with DNA. The analysis undertaken in this study involves searching of QSAR (Quantitative Structure-Activity Relationship) and QSRR (Quantitative Structure- Retention Relationship) models, which would allow to predict the biological activity of acridinones expressed as the ability to stabilize the secondary structure of DNA (ΔT), based on their structural parameters and chromatographic retention data. For this purpose, 20 acridinone derivatives were subjected to chromatographic analyses and molecular modeling, followed by statistical analyses using multiple linear regression method (MLR). As a novelty aspect, except for RP-HPLC approach, hydrophilic interaction chromatography (HILIC) columns were tested. As a result of performed analysis, appropriate QSAR and QSRR models were obtained, and each model was analyzed in terms of prediction of acridinones’ ability to interact with DNA. Derived QSAR and QSRR models were characterized as one, with good prediction performance. Conclusively, the proposed connected QSAR and QSRR strategies allow to predict in silico the ability of acridinones to interact with DNA without the necessity of performing any biological experiments under in vitro and in vivo conditions.

Keywords: Acridinones, antitumor activity, physicochemical binding to DNA, QSAR (Quantitative Structure-Activity Relationship), QSRR (Quantitative Structure-Retention Relationship).

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Article Details

VOLUME: 17
ISSUE: 10
Year: 2014
Page: [820 - 826]
Pages: 7
DOI: 10.2174/1386207317666141112120743
Price: $58

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