Could multivariate statistics exploit HPTLC and NMR data to reveal bioactive compounds? The case of Paeonia mascula

Publication date: Available online 23 March 2017 Source:Phytochemistry Letters Author(s): Vasiliki-Ioanna Boka, Konstantina Stathopoulou, Dimitra Benaki, Evangelos Gikas, Nektarios Aligiannis, Emmanuel Mikros, Alexios-Leandros Skaltsounis Bioassay screening or pharmacological evaluation is a common approach to guide the isolation process towards the pure bioactive component. Nevertheless, plenteous time is wasted on isolation, purification and structural elucidation of already known compounds. The tendency over the last years for implementation of high-throughput screening (HTS) technologies leads to the prior identification of the compounds that contribute to the demonstrated activity, avoiding the constant re-isolation of known compounds, reducing workload and cost. The extract of Paeonia mascula ssp. hellenica, which was discriminated for its tyrosinase inhibition among other extracts from Greek flora, was fractionated by FCPC and the resulted fractions were assayed for tyrosinase inhibition potential and further analyzed by HPTLC and NMR. An integrated HPTLC-based procedure for the tracing of compounds that contributed to tyrosinase inhibitory effect in active fractions was established with the use of multivariate data analysis. Additionally, NMR spectral data were correlated with the activity towards tyrosinase resulting in the identification of bioactive compounds through the combination of the Heterocovariance approach (HetCA) and the statistical total correla...

Source: Phytochemistry Letters - May 3, 2017 Category: Chemistry Source Type: research