RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.
CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.
METHODS: In an attempt to visualize the aggregation behavior of GA and its subsequent association with PTX, 100 ns molecular dynamics simulation of a 5 mM aqueous solution of GA with 10 molecules of PTX was conducted using GROMACS and an all-atom forcefield.
RESULTS: Aggregation of GA molecules was found to occur quickly at this level of saturation leading to two stable aggregates of 13 and 17 GA molecules with an effective radius of 10.17 nm to 10.92 nm. These aggregates form not in isolation, but together with PTX molecule embedded within the structures, which reduces the number of interactions and hydrogen-bonding with water.
CONCLUSION: GA aggregation occurs around PTX molecules in solution, forming co-joined GA-PTX cluster units at a ratio of 3:1. These clusters remain stable for the remainder of the 100ns simulation and serve to isolate and protect PTX from the aqueous environment.