Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/13853
Title: The evaluation of the anticancer activity of the Biginelli hybrids and pharmacokinetic profiling based on their retention parameters
Authors: Trifunović Ristovski J.
Minorics, Renata
Bartha S.
Janković, Nenad
Zupkó, István
Issue Date: 2022
Abstract: The present investigation gives an insight into the evaluation and analysis of the anticancer activity of the library of the Biginelli hybrids using the appropriate QSRR approach. Using the RP TLC method retention parameters of tested compounds were obtained and examined to measure of lipophilicity of investigated molecules. The compounds were examined in seven different cancer cell lines and their IC50 and% of inhibition of cell proliferation at 100 µM were established. These experimental values as well as appropriate molecular descriptors are included in QSRR analysis. For this purpose, the variable selection was made, PCA and HCA were carried out, nine MR models were developed and ranked. The quality of the established models was confirmed through internal and external statistical validation. The goal was to define the main differences and similarities between three groups of the tested Biginelli hybrids to -find out which molecular features affect lipophilicity the most and which are crucial for the development of high-quality QSRR models. Tetrahydropyrimidines with butyl (11) and benzyl fragment (19) possess the best anticancer activity and selectivity. Nowadays modern design of an active pharmaceutical ingredient includes specific requirements of rationalization to adapt physicochemical characteristics, pharmacological activity, and safety through structural changes of the molecule. We believe that the developed profile is a step forward in Biginelli chemistry and could be useful in the future synthesis of novel Biginelli-based compounds with significantly improved activities.
URI: https://scidar.kg.ac.rs/handle/123456789/13853
Type: article
DOI: 10.1016/j.molstruc.2022.132373
ISSN: 0022-2860
SCOPUS: 2-s2.0-85123002320
Appears in Collections:Institute for Information Technologies, Kragujevac

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