Identifying ligands directly interacting with target protein in medicinal herbs by metabolomic analysis of T2-filtered HSQC spectra.

ABSTRACT

A protocol for efficiently identifying ligands directly interacting with a target protein in complex extracts of medicinal herbs was proposed by combining an adapted 2D perfect-echo Carr-Purcell-Meiboom-Gill heteronuclear single quantum correlation (PE-CPMG HSQC) spectrum with metabolomic analysis. PE-CPMG HSQC can suppress the signal interference from the target protein, allowing more accurate peak quantification than conventional HSQC. Inspired from untargeted metabolomics, regions of interest (ROIs) are constructed and quantified for the mixture or complex extract samples with and without a target protein, and then a binding index (BI) of each ROI is determined. ROIs or corresponding peaks significantly perturbed by the presence of the target protein (BI ≥1.5) are detected as differential features, and potential binding ligands identified from the differential features can be equated with bioactive markers associated with the 'treatment' of the target protein. Quantifying ROI can inclusively report the ligand bindings to a target protein in fast, intermediate and slow exchange regimes on nuclear magnetic resonance (NMR) time scale. The approach was successfully implemented and identified Angoroside C, Cinnamic acid and Harpagoside from the extract of Scrophularia ningpoensis Hemsl. as ligands binding to peroxisome proliferator-activated receptor γ. The proposed 2D NMR-based approach saves excess steps for sample processing and has a higher chance of detecting the weaker ligands in the complex extracts of medicinal herbs. We expect that this approach can be applied as an alternative to mining the potential ligands binding to a variety of target proteins from traditional Chinese medicines and herbal extracts.