A Strategy Based on GC-MS/MS, UPLC-MS/MS and Virtual Molecular Docking for Analysis and Prediction of Bioactive Compounds in Leaves.

The discovery of medicinal plants is crucial for drug development. leaves are used as a traditional medicine in many areas of world due to herbicidal and insecticidal activity. While natural products are difficult to be separated and activity assayed, a new approach is needed to predict the active ingredients therein. In this study, a new method for screening active compounds extracted from leaves was developed by GC-MS/MS and UPLC-MS/MS combined with molecular docking technology. Predicted compounds with high activity were proposed. Firstly, 35 volatile compounds and 34 aqueous extracted compounds were extracted from leaves, and identified by GC-MS/MS and UPLC-MS/MS. The herbicidal receptor (1BX9) was then docked with the identified compounds by docking software, evaluated by docking models and seven scoring functions. The results showed that gallic acid had a strong inhibitory activity of 1BX9, which was speculated to be the main reason for the inhibitory effect of leaves. Finally, allelopathic tests of gallic acid, citric acid, and isopulegol were carried out on grass seeds to verify its inhibitory activity against herbicide receptor 1BX9. The results show that the method can screen compounds with specific activity from a complex system of medicinal plants, which is very important for the screening of new active ingredients, confirmation of new medicinal ingredients, and the in-depth development of animal and plant medicines.