Synthesis and Anti-Breast Cancer Potency of Mono- and Bis-(pyrazolyl[1,2,4]triazolo[3,4- b ][1,3,4]thiadiazine) Derivatives as EGFR/CDK-2 Target Inhibitors.
Mostafa E SalemEsraa M MahrousEman A RagabMohamed S NafieKamal M DawoodPublished in: ACS omega (2023)
The target mono- and bis-(6-pyrazolyltriazolo-thiadiazine) derivatives 4a-c and 6a-d were synthesized using a straightforward protocol via reaction of 3-bromoacetylpyrazole 2 with 4-amino- s -triazole-3-thiols 3a-c and bis(4-amino-5-mercapto- s -triazol-3-yl)alkanes 5a-d , respectively. The bis(6-pyrazolyl- s -triazolo[3,4- b ][1,3,4]thiadiazine) derivatives 8a , b and 10 were also constructed by reaction of the triazolo[3,4- b ][1,3,4]thiadiazine-3-thiol 4c with the proper dibromo compounds 7a , b and 9 , respectively. Structures of the new substances were determined by spectroscopic and analytical data. Compounds 4b , 4c , and 6a showed potent cytotoxicity against MCF-7 (IC 50 = 3.16, 2.74, and 0.39 μM, respectively) and were safe against the MCF-10A cells. Compounds 4b , 4c , and 6a also showed promising dual EGFR and CDK-2 inhibition activities, particularly 6a was the most effective (IC 50 = 19.6 and 87.9 nM, respectively), better than Erlotinib and Roscovitine. Compound 6a treatment induced EGFR and CDK-2 enzyme inhibition by 97.18% and 94.11%, respectively, at 10 μM (the highest concentration). Compound 6a notably induced cell apoptosis in MCF-7 cells, increasing the cell population by total apoptosis 43.3% compared to 1.29% for the untreated control group, increasing the cell population at the S-phase by 39.2% compared to 18.6% (control).
Keyphrases
- cell cycle arrest
- epidermal growth factor receptor
- small cell lung cancer
- induced apoptosis
- ionic liquid
- breast cancer cells
- tyrosine kinase
- cell cycle
- endoplasmic reticulum stress
- cell death
- diabetic rats
- single cell
- oxidative stress
- high glucose
- cell therapy
- randomized controlled trial
- cell proliferation
- pi k akt
- photodynamic therapy
- high resolution
- stem cells
- wastewater treatment
- machine learning
- mass spectrometry
- liquid chromatography