Predicting in Silico which mixtures of the natural products of plants might most effectively kill human leukemia cells?

Abstract

The aim of the analysis of just 13 natural products of plants was to predict the most likely effective artificial mixtures of 2-3 most effective natural products on leukemia cells from over 364 possible mixtures. The natural product selected included resveratrol, honokiol, chrysin, limonene, cholecalciferol, cerulenin, aloe emodin, and salicin and had over 600 potential protein targets. Target profiling used the Ontomine set of tools for literature searches of potential binding proteins, binding constant predictions, binding site predictions, and pathway network pattern analysis. The analyses indicated that 6 of the 13 natural products predicted binding proteins which were important targets for established cancer treatments. Improvements in effectiveness were predicted for artificial combinations of 2 or 3 natural products. That effect might be attributed to drug synergism rather than increased numbers of binding proteins bound (dose effects). Among natural products, the combinations of aloe emodin with mevinolin and honokiol were predicted to be the most effective combination for AML-related predicted binding proteins. Therefore, plant extracts may in future provide more effective medicines than the single purified natural products of modern medicine, in some cases. © 2013 Hany A. El-Shemy et al.