A new method on functional orientation of Moringa leaves based on text mining and molecular docking was explored in the study. First, PubMedplus was used to analyze research data on Moringa leaves collected in PubMed and the indications of Moringa leaves were screened along with the hotspots and development tendency of Moringa leaves. Second, Arrowsmith was used to obtain the biological targets of Moringa leaves. Third, active candidate components of Moringa leaves were filtered by SwissADME analyzing on chemical data collected from literatures. Subsequently, molecular docking between active candidate component and target was studied by systemsDock to forecast the potential active components and their possible effective targets, and GO functional annotation of the potential targets was performed by DAVID database. According to the results, tumor, diabetes and digestive diseases were suggested to be indications of Moringa leaves, correlated with 25 active components and 12 potential effective targets possibly by adjusting G protein-coupled receptor and affecting on inflammatory reaction. The new method on functional orientation by combining text mining with molecular docking was successfully practiced on Moringa leaves as a case study,which provides a useful reference for the ultilization of foreign medicinal resource.
Keywords: Moringa leaves; functional orientation; molecular docking; new resources of traditional Chinese medicine; text mining.