The Effect of Liposomal Diallyl Disulfide and Oxaliplatin on Proliferation of Colorectal Cancer Cells: In Vitro and In Silico Analysis.
Faris A AlrumaihiMasood Alam KhanAli Yousif BabikerMohammed AlsaweedFaizul AzamKhaled S AllemailemAhmad A AlmatroudiSyed Rizwan AhamadNaif AlSuhaymiMahdi H AlsugoorAhmed N AlgefaryArif KhanPublished in: Pharmaceutics (2022)
Diallyl disulfide (DADS) is one of the main bioactive organosulfur compounds of garlic, and its potential against various cancer models has been demonstrated. The poor solubility of DADS in aqueous solutions limits its uses in clinical application. The present study aimed to develop a novel formulation of DADS to increase its bioavailability and therapeutic potential and evaluate its role in combination with oxaliplatin (OXA) in the colorectal cancer system. We prepared and characterized PEGylated, DADS (DCPDD), and OXA (DCPDO) liposomes. The anticancer potential of these formulations was then evaluated in HCT116 and RKO colon cancer cells by different cellular assays. Further, a molecular docking-based computational analysis was conducted to determine the probable binding interactions of DADS and OXA. The results revealed the size of the DCPDD and DCPDO to be 114.46 nm (95% EE) and 149.45 nm (54% EE), respectively. They increased the sensitivity of the cells and reduced the IC 50 several folds, while the combinations of them showed a synergistic effect and induced apoptosis by 55% in the cells. The molecular docking data projected several possible targets of DADS and OXA that could be evaluated more precisely by these novel formulations in detail. This study will direct the usage of DCPDD to augment the therapeutic potential of DCPDO against colon cancer in clinical settings.
Keyphrases
- molecular docking
- induced apoptosis
- endoplasmic reticulum stress
- signaling pathway
- acinetobacter baumannii
- molecular dynamics simulations
- oxidative stress
- klebsiella pneumoniae
- cell cycle arrest
- drug delivery
- photodynamic therapy
- cell death
- pi k akt
- drug resistant
- climate change
- escherichia coli
- squamous cell carcinoma
- papillary thyroid
- single cell
- young adults
- deep learning
- lymph node metastasis
- big data