Safety, Stability, and Therapeutic Efficacy of Long-Circulating TQ-Incorporated Liposomes: Implication in the Treatment of Lung Cancer.
Arif KhanMohammed A AlsahliMohammad Abdullah AljasirHamzah MaswadehMugahid A MobarkFaizul AzamKhaled S AllemailemFaris A AlrumaihiFahad A AlhumaydhiAmeen S S AlwashmiAhmad A AlmatroudiMahdi H AlsugoorMasood Alam KhanPublished in: Pharmaceutics (2022)
Thymoquinone (TQ), which is one of the main bioactive constituents of Nigella sativa seeds, has demonstrated its potential against various cancer models. The poor solubility of TQ in aqueous solution limits its uses in clinical application. The present study aimed to develop a novel formulation of TQ to increase its bioavailability and therapeutic potential with minimal toxicity. Polyethylene glycol (PEG)-coated DSPC/cholesterol comprising TQ liposomes (PEG-Lip-TQ) were prepared and characterized on various aspects. A computational investigation using molecular docking was used to assess the possible binding interactions of TQ with 12 prospective anticancer drug targets. The in vitro anticancer activity was assessed in A549 and H460 lung cancer cells in a time- and dose-dependent manner, while the oral acute toxicity assay was evaluated in silico as well as in vivo in mice. TQ docked to the Hsp90 target had the lowest binding energy of -6.05 kcal/mol, whereas caspase 3 was recognized as the least likely target for TQ with a binding energy of -1.19 kcal/mol. The results showed 96% EE with 120 nm size, and -10.85 mv, ζ-potential of PEG-Lip-TQ, respectively. The cell cytotoxicity data demonstrated high sensitivity of PEG-Lip-TQ and a several fold decrease in the IC 50 while comparing free TQ. The cell cycle analysis showed changes in the distribution of cells with doses. The in vivo data revealed an ~9-fold increase in the LD 50 of PEG-Lip-TQ on free TQ as an estimated 775 and 89.5 mg/kg b.w, respectively. This study indicates that the pharmacological and efficacy profile of PEG-lip-TQ is superior to free TQ, which will pave the way for an exploration of the effect of TQ formulation in the treatment of lung cancer in clinical settings.
Keyphrases
- drug delivery
- molecular docking
- cell cycle
- oxidative stress
- emergency department
- squamous cell carcinoma
- machine learning
- single cell
- deep learning
- photodynamic therapy
- stem cells
- transcription factor
- hepatitis b virus
- heat shock protein
- artificial intelligence
- extracorporeal membrane oxygenation
- mechanical ventilation
- data analysis