(1)H NMR-MS-based heterocovariance as a drug discovery tool for fishing bioactive compounds out of a complex mixture of structural analogues

Chemometric methods and correlation of spectroscopic or spectrometric data with bioactivity results are known to improve dereplication in classical bio-guided isolation approaches. However, in drug discovery from natural sources the isolation of bioactive constituents from a crude extract containing close structural analogues remains a significant challenge. This study is a (1)H NMR-MS workflow named ELINA (Eliciting Nature’s Activities) which is based on statistical heterocovariance analysis (HetCA) of (1)H NMR spectra detecting chemical features that are positively (“hot”) or negatively (“cold”) correlated with bioactivity prior to any isolation. ELINA is exemplified in the discovery of steroid sulfatase (STS) inhibiting lanostane triterpenes (LTTs) from a complex extract of the polypore fungus Fomitopsis pinicola.