Recipe for uncovering the bioactive components in herbal medicine

Abstract

Using whole chromatographic profiles and measurements of total bioactivity as input, a quantitative pattern-activity relationship (QPAR) approach is proposed as a general method for providing two pieces of crucial information about complex bioactive mixtures available: (i) a model for predicting total bioactivity from the chromatographic fingerprint and (ii) the features in the chromatographic profile responsible for the bioactivity. While the first piece of information is already available through existing approaches, the second one results from our ability to remove dominant features in the chromatographic fingerprints which mask the components specifically related to pharmacological activity. Our targeted approach makes information about bioactivity available at the molecular level and provides possibilities for assessment of herbal medicine (HM) possible beyond just authentication and total bioactivity. As an example, the antioxidant property of the HM Radix Puerariae lobatae is measured through its reducing power toward a ferric ion complex. A partial least-squares (PLS) model is created to predict the antioxidant activity from the chromatographic fingerprint. Using the antioxidant activity as a target, the most discriminatory projection in the multivariate space spanned by the chromatographic profiles is revealed. From this target-projected component, the chromatographic regions most strongly connected to antioxidant activity are identified using the so-called selectivity ratio (SR) plot. The results are validated by prediction of samples not included in the modeling step.