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Synthesis, Anticancer Evaluation and Structure-Activity Analysis of Novel (E)- 5-(2-Arylvinyl)-1,3,4-oxadiazol-2-yl)benzenesulfonamides

To learn more about the structure–activity relationships of (E)-3-(5-styryl-1,3,4-oxadiazol-2-yl)benzenesulfonamide derivatives, which in our previous research displayed promising in vitro anticancer activity, we have synthesized a group of novel (E)-5-[(5-(2-arylvinyl)-1,3,4-oxadiazol-2-yl)]-4-chlo...

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Detalles Bibliográficos
Autores principales: Szafrański, Krzysztof, Sławiński, Jarosław, Tomorowicz, Łukasz, Kawiak, Anna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139731/
https://www.ncbi.nlm.nih.gov/pubmed/32210190
http://dx.doi.org/10.3390/ijms21062235
Descripción
Sumario:To learn more about the structure–activity relationships of (E)-3-(5-styryl-1,3,4-oxadiazol-2-yl)benzenesulfonamide derivatives, which in our previous research displayed promising in vitro anticancer activity, we have synthesized a group of novel (E)-5-[(5-(2-arylvinyl)-1,3,4-oxadiazol-2-yl)]-4-chloro-2-R(1)-benzenesulfonamides 7–36 as well as (E)-4-[5-styryl1,3,4-oxadiazol-2-yl]benzenesulfonamides 47–50 and (E)-2-(2,4-dichlorophenyl)-5-(2-arylvinyl)-1,3,4-oxadiazols 51–55. All target derivatives were evaluated for their anticancer activity on HeLa, HCT-116, and MCF-7 human tumor cell lines. The obtained results were analyzed in order to explain the influence of a structure of the 2-aryl-vinyl substituent and benzenesulfonamide scaffold on the anti-tumor activity. Compound 31, bearing 5-nitrothiophene moiety, exhibited the most potent anticancer activity against the HCT-116, MCF-7, and HeLa cell lines, with IC50 values of 0.5, 4, and 4.5 µM, respectively. Analysis of structure-activity relationship showed significant differences in activity depending on the substituent in position 3 of the benzenesulfonamide ring and indicated as the optimal meta position of the sulfonamide moiety relative to the oxadizole ring. In the next stage, chemometric analysis was performed basing on a set of computed molecular descriptors. Hierarchical cluster analysis was used to examine the internal structure of the obtained data and the quantitative structure–activity relationship (QSAR) analysis with multiple linear regression (MLR) method allowed for finding statistically significant models for predicting activity towards all three cancer cell lines.