Development of Cationic Solid Lipid Nanoparticles with Factorial Design-Based Studies for Topical Administration of Doxorubicin

Topical chemotherapy using doxorubicin, a powerful anticancer drug, can be used as an alternative with reduced systemic toxicity when treating skin cancer. The aim of the present work was to use factorial design-based studies to develop cationic solid lipid nanoparticles containing doxorubicin; further investigations into the influence of these particles on the drug's cytotoxicity and cellular uptake in B16F10 murine melanoma cells were performed. A 3(2) full factorial design was applied for two different lipid phases; one phase used stearic acid and the other used a 1:2 mixture of stearic acid and glyceryl behenate. The two factors investigated included the ratio between the lipid and the water phase and the ratio between the surfactant (poloxamer) and the co-surfactant (cetylpyridinium chloride). It was observed that the studied factors did not affect the mean diameter or the polydispersity of the obtained nanoparticles; however, they did significantly affect the zeta potential values. Optimised formulations with particle sizes ranging from 251 to 306 nm and positive zeta potentials were selected for doxorubicin incorporation. High entrapment efficiencies were achieved (97%) in formulations with higher amounts of stearic acid, suggesting that cationic charges on doxorubicin molecules may interact with the negative charges in stearic acid. Melanoma culture cell experiments showed that cationic solid lipid nanoparticles without drug were not cytotoxic to melanoma cells. The encapsulation of doxorubicin significantly increased cytotoxicity, indicating the potential of these nanoparticles for the treatment of skin cancer.

Structure-based drug design studies on a series of aldolase inhibitors

Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.