Introduction: In drug discovery, bioassay-guided isolation is a well-established procedure, and still the basic approach for the discovery of natural products with desired biological properties. However, in these procedures, the most laborious and time-consuming step is the isolation of the bioactive constituents. A prior identification of the compounds that contribute to the demonstrated activity of the fractions would enable the selection of proper chromatographic techniques and lead to targeted isolation.
Objective: The development of an integrated HPTLC-based methodology for the rapid tracing of the bioactive compounds during bioassay-guided processes, using multivariate statistics. Materials and Methods - The methanol extract of Morus alba was fractionated employing CPC. Subsequently, fractions were assayed for tyrosinase inhibition and analyzed with HPTLC. PLS-R algorithm was performed in order to correlate the analytical data with the biological response of the fractions and identify the compounds with the highest contribution. Two methodologies were developed for the generation of the dataset; one based on manual peak picking and the second based on chromatogram binning. Results and Discussion - Both methodologies afforded comparable results and were able to trace the bioactive constituents (e.g. oxyresveratrol, trans-dihydromorin, 2,4,3'-trihydroxydihydrostilbene). The suggested compounds were compared in terms of Rf values and UV spectra with compounds isolated from M. alba using typical bioassay-guided process.
Conclusion: Chemometric tools supported the development of a novel HPTLC-based methodology for the tracing of tyrosinase inhibitors in M. alba extract. All steps of the experimental procedure implemented techniques that afford essential key elements for application in high-throughput screening procedures for drug discovery purposes. Copyright © 2017 John Wiley & Sons, Ltd.
Keywords: HPTLC; Morus alba; PLS-regression; chemometrics; tyrosinase inhibition.
Copyright © 2017 John Wiley & Sons, Ltd.