There are a vast number biologically active natural products out there with the potential to cure any number of rather nasty diseases. But searching for them and identifying their therapeutic targets can seem like a bewilderingly large task. In this interesting paper Weidong Zhang and colleagues from several institutes in Shanghai have combined knowledge from traditional Chinese medicine with computational chemical biology to rapidly identify novel targets for natural products derived from plants.
The authors selected Bacopa monnieri (L.) Wettst (BMW) and Daphne odora Thunb. var. marginata (DOT) – which are used in traditional medicine for the treatment of diabetes and inflammation – and screened 19 compounds isolated from the plants against a potential drug target database using a reverse docking approach. Based on these results and the clinical indication of the plants the DPP-IV protein (a therapeutic target for type II diabetes) was chosen for experimental validation. When tested in vitro, 5 of the 19 compounds showed moderate inhibition of DPP-IV. Then, from these five compounds analogues from an in-house library were screened, almost half of which again showed the ability to moderately inhibit the protein.
The authors emphasise that further work must be done to identify the synergistic pathways that result in the overall efficacy of traditional Chinese medicinal treatments, but this paper does demonstrate how it is possible to use natural products derived from clinically effective, but poorly understood, traditional treatments as a starting point for rapidly and successfully identifying new therapeutic targets.
Fast and effective identification of the bioactive compounds and their targets from medicinal plants via computational chemical biology approach
Shoude Zhang, Weiqiang Lu, Xiaofeng Liu, Yanyan Diao, Fang Bai, Liyan Wang, Lei Shan, Jin Huang, Honglin Li and Weidong Zhang
Med. Chem. Commun., 2011, Advance Article