Fast and effective identification of the bioactive compounds and their targets from medicinal plants via computational chemical biology approach

Abstract

The potential drug target database (PDTD) was searched by the TarFisDock server, a reverse docking approach, to identify putative targets for a collection of 19 natural products derived from two medicinal plants Bacopa monnieri (L.) Wettst (BMW) and Daphne odora Thunb. var. marginata (DOT), which are both used for the treatment of diabetes and inflammation in Traditional Chinese Medicine (TCM). Out of the top 5% of target candidates, dipeptidyl peptidase IV (DPP-IV) was the most frequent potential target and the predicted results were subsequently confirmed by in vitroenzyme assay. As a result, five natural products show moderate inhibitory activities against DPP-IV with IC₅₀ values ranging from 14.13 μM to 113.76 μM. Subsequently, thirteen analogues of active compounds out of our in-house natural products database (NPD) were also identified with inhibitory activity against DPP-IV, with IC₅₀ values ranging from 26.92 μM to 87.72 μM. The results indicate that the computational chemical biology approach is a good complement to the experimental target identification strategies for elucidating the mechanism of the natural products, especially for those components without unambiguous binding targets whilst having some traditional efficacy in TCM.