Phytochemicals such as ‘Caffeine’ act as mood stimulants and has become part of daily routine for many people. It is also part of many drugs to cause therapeutic effects and has been used as model drug to study controlled and targeted release in intestine. We checked the feasibility of using in silico
molecular docking analysis as a screening step to choose the most suitable combination for encapsulation of caffeine-monomer. We also prepared microspheres with the predicted monomers and checked yield and drug release profile.
To test a screening approach for decision of a suitable Caffeine-monomer combination, we performed in silico rigid body molecular docking between Caffeine and 10 monomers using HexTM software. The best docked structures were energy minimized and compared for their stability. Caffeine loaded Chitosan-TPP polymer combinations were made using ionotropic-gelation method with different concentrations of Chitosan, TPP and Caffeine. The encapsulation time was also varied and all combinations were checked for drug encapsulation efficiency and drug release profile.
Molecular docking studies revealed that Chitosan-Caffeine combination has the most stable conformation (lowest energy) among natural polymers. Caffeine-loaded Chitosan-TPP microspheres made with 2% TPP, pH 7.5, 1 % Chitosan, 0.4 % Caffeine and 20 mins stirring time were found to be best in terms of high encapsulation efficiency (83%) and Caffeine release profile. They also showed no covalent interactions between Caffeine and Chitosan and perfect spherical surface of resultant microspheres.
In silico molecular docking analysis predicted that analysis drug-monomer complex can be used as a screening tool to choose appropriate final drug-polymer combinations. Chitosan-TPP microspheres emerged as an ideal system for controlled delivery of model drug Caffeine which was confirmed by experimental findings. Our study would be helpful in improving design of controlled release formulations for various small molecule drugs in natural biopolymers.
KS Singh, S Anand, D Aggrawal and JK Sharma. Knowledge-driven prediction and protective encapsulation of small molecules and phytochemicals. J Pharmacogn Phytochem 2018;7(2):2638-2642.