In silico evaluation of the antidiabetic activity of natural compounds from Hovenia dulcis Thunberg

Abstract Hovenia dulcis Thunberg is a medicinal plant from the Rhamnaceae family. There have been descriptions of some medicinal properties of H. dulcis, but the knowledge about their effects on biological mechanisms is scarce. Thus, the medicinal properties of H. dulcis were investigated using in silico analysis by a system biology approach. A systematic review of the chemical compounds of H. dulcis was performed in the PubMed database. Subnetworks of proteins and chemical compounds were created using the data mining tools STRING 10.0 and STITCH 5.0 and merged with Cytoscape 3.4.0. Cluster analysis and bioprocesses assessment were performed using the Complex Molecular Detection (MCODE) and the Biological Network Gene Ontology (BiNGO) tools, respectively. The centralities analysis was performed using CentiScaPe. The prospected network contained 210 nodes and 1586 edges. The cluster analysis indicated eight modules and the gene ontology analysis evidenced the following bioprocesses: glucan and glycogen biosynthetic processes regulation, response to insulin stimulus, and cytoskeleton organization. The results of the centralities analysis indicated AKT1 and GSK3β as important regulator nodes of bioprocesses. Based on the results, it is possible to propose a molecular model in which H. dulcis chemical compounds prevent the progression of type 2 diabetes mellitus associated with inflammation mechanisms. In this model, GSK3β inhibition is the key mechanism to avoid increased glucose blood levels and inflammatory responses.