Identification of active compounds from medicinal plant extracts using gas chromatography-mass spectrometry and multivariate data analysis

Conventional methods of drug discovery from natural products include bioassay-guided fractionation, which is tedious and has low efficiency. The aim of this work is to develop a platform method to rapidly identify bioactive compounds from crude plant extracts and their partially purified fractions using multivariate data analysis (MVDA). Soxhlet extraction and liquid-liquid fractionation were used to prepare different extracts and fractions from the leaves of a medicinal plant, Ardisia elliptica. The extracts and fractions were analysed chemically using GC-MS, and their ability to inhibit platelet aggregation was investigated. Two MVDA methods were developed and optimised to analyse the results. In the first method, compounds with the highest contribution scores for biological activity calculated by different models were listed as potential antiplatelet compounds. For the second MVDA method, a correlation of the concentrations of constituents and biological activities in the various extracts and fractions for each compound was done. Compounds with the highest correlation coefficients were identified as potential antiplatelet compounds. One of the predicted components was isolated, purified and confirmed to possess antiplatelet effects. This platform method can be developed and optimised for other plant extracts and biological activities, thus reducing time and cost of drug discovery while improving efficiency.