Objective: Propolis is highly recommended in aphthous stomatitis, a condition that requires a proper delivery tool to achieve an efficient treatment. For this indication, a buccal patch that provides prolonged mucosal contact and protection would be beneficial. Accordingly, in this study, we designed propolis-loaded buccal patches, composed of three polymers (alginate, carboxymethylcellulose, and polyvinylpyrrolidone) of complementary properties, and the proper combination of them to produce the patch of optimum properties. Material and Method: Nine patches of different polymer ratios were prepared by casting method and evaluated by assessing their swelling, adhesion time and strength, and dissolution rate. Then the patches properties were correlated using artificial neural network analysis. Result and Discussion: The results showed that all patches were smooth, translucent, and flexible with surface pH between 6.5 and 7.4. The correlation between polymer composition and measured properties was complex and non-linear. Therefore, an artificial neural network was used to analyze these properties and optimize them. The model of this analysis provides higher weights for favorable tensile and adhesion strengths while considering swelling, rigidity, and fast dissolution rate as unfavorable. According to summation analysis, the combination of CMC% and PVP% of 15.5 and 13, respectively, provides the best score of 3.5.

Modulation of disease progression is frequently started by identifying biochemical pathway catalyzed by biomolecule that is prone to inhibition by small molecular weight ligands. Such ligands (leads) can be obtained from natural resources or synthetic libraries. However de novo design based on fragments assembly and optimization is showing increasing success. In this research, fragment-based approaches were used to design molecules that can fit glutathione (GSH) binding site of Plasmodium falciparum GST (PfGST). The involved approaches build molecules from fragments that are either isosteric to GSH sub-moieties (ligand-based) or successfully docked to GSH binding sub-pockets (structure-based). Selected fragments are joined to create ligands that were explored using molecular docking, Cartesian coordinate’s optimization, and simplified free energy determination as well as MD simulation and MMPBSA calculations. Compared to reference GST inhibitor of S-hexyl GSH, ligands with improved rigidity, synthetic accessibility and affinity to receptor were successfully designed.

In the context of drug design and development, phytochemical and synthetic libraries are starting places for searching leads. However, knowing crystal structure of receptor may help scratching molecules that complements available interaction sites using de novo molecular design approaches. This research describes the implementation of genetic algorithm optimization technique for construction of molecular scaffold composed from sp2 carbon, oxygen and nitrogen atoms. Using Matlab, functions for molecule construction, crossover, mutation and fitness measurement were individually programmed. Fitness function was derived from AutoDock3.05 function which calculates molecular interaction energy with protein using grid map. The approach was successfully applied to design glutathione-S-transferase inhibitory molecule at sub-site of the binding pocket that is originally occupied by g-glutamyl and cysteinyl moieties of glutathione substrate. Starting from scratches, the approach was able to design molecular scaffolds complementarily filling the pocket.