Comprehensive QSRR modeling as a starting point in characterization and further development of anticancer drugs based on 17α-picolyl and 17(E)-picolinylidene androstane structures
The selection of the most promising anticancer compounds from the pool of the huge number of synthesized molecules is a quite complex task. There are many compounds characterization approaches which can suggest the best structural features of a molecule with the highest antiproliferative effect on t...
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Veröffentlicht in: | European journal of pharmaceutical sciences 2016-10, Vol.93, p.1-10 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The selection of the most promising anticancer compounds from the pool of the huge number of synthesized molecules is a quite complex task. There are many compounds characterization approaches which can suggest the best structural features of a molecule with the highest antiproliferative effect on the certain type of cancer cell lines. One of these approaches is the lipophilicity determination of compounds and the analysis of its correlation with the anticancer activity. Since the importance of the lipophilicity is underlined in many earlier studies, this study is focused on determination of lipophilicity of previously synthesized 17α-picolyl and 17(E)-picolinylidene androstane derivatives by using reversed-phase high performance liquid chromatography (RP-HPLC) as a very fast, effective and relatively cheap method. Determination of the chromatographic lipophilicity of the studied androstanes can be considered as the part of their physicochemical characterization, which is a very important step in their further selection as drug candidates. The present study does not neglect the in silico approach. The determined chromatographic lipophilicity was analyzed by quantitative structure-retention relationship (QSRR) approach in order to reveal which molecular characteristics contribute mostly to the typical behavior of the androstanes in the applied chromatographic system, and thus to their lipophilicity. Classical statistical approach and Sum of Ranking Differences method were used for selection of the best QSRR models which should be used in prediction of chromatographic lipophilicity of studied androstane derivatives.
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ISSN: | 0928-0987 1879-0720 |
DOI: | 10.1016/j.ejps.2016.07.008 |