Preparation and Cytotoxic Evaluation of PGV-1 Derivative, CCA-1.1, as a New Curcumin Analog with Improved-Physicochemical and Pharmacological Properties.
Rohmad Yudi UtomoFebri WulandariDhania NovitasariBeni LestariRatna Asmah SusidartiRiris Istighfari Istighfari JenieJun-Ya KatoSardjiman SardjimanEdy MeiyantoPublished in: Advanced pharmaceutical bulletin (2021)
Purpose: This study aimed to challenge the anticancer potency of pentagamavunone-1 (PGV- 1) and obtain a new compound (Chemoprevention-Curcumin Analog 1.1, CCA-1.1) with improved chemical and pharmacological properties. Methods: CCA-1.1 was prepared by changing the ketone group of PGV-1 into a hydroxyl group with NaBH 4 as the reducing agent. The product was purified under preparative layer chromatography and confirmed with HPLC to show about 93% purity. It was tested for its solubility, stability, and cytotoxic activities on several cancer cells. The structure of the product was characterized using 1 HNMR, 13 C-NMR, FT-IR, and HR-mass spectroscopy. Results: Molecular docking analysis showed that CCA-1.1 performed similar or better interaction to NF-κB pathway-related signaling proteins (HER2, EGFR, IKK, ER-alpha, and ER-beta) and reactive oxygen species (ROS) metabolic enzymes (NQO1, NQO2, GSTP1, AKC1R1, and GLO1) compared with PGV-1, indicating that CCA-1.1 exhibits the same or better anticancer activity than PGV-1. CCA-1.1 also showed better solubility and stability than PGV-1 in aqueous solution at pH 1.0-7.4 under light exposure at room temperature. The cytotoxic activities of CCA-1.1 against several (10) cancer cell lines revealed the same or better potency than PGV-1. Conclusion: In conclusion, CCA-1.1 performs better chemical and anticancer properties than PGV-1 and shows promise as an anticancer agent with high selectivity.
Keyphrases
- pi k akt
- signaling pathway
- molecular docking
- room temperature
- reactive oxygen species
- high resolution
- mass spectrometry
- small cell lung cancer
- aqueous solution
- magnetic resonance
- dna damage
- immune response
- cell death
- ionic liquid
- tyrosine kinase
- squamous cell carcinoma
- oxidative stress
- deep learning
- single cell
- tandem mass spectrometry
- machine learning
- young adults
- big data
- breast cancer cells
- artificial intelligence
- nuclear factor
- water soluble