Abstract
Qingdai, a traditional Chinese medicine (TCM) used for the treatment of chronic myeloid leukemia (CML) with good efficacy, has been used in China for decades. However, due to the complexity of traditional Chinese medicinal compounds, the pharmacological mechanism of Qingdai needs further research. In this study, we investigated the pharmacological mechanisms of Qingdai in the treatment of CML using network pharmacology approaches. First, components in Qingdai that were selected by pharmacokinetic profiles and biological activity predicted putative targets based on a combination of 2D and 3D similarity measures with known ligands. Then, an interaction network of Qingdai putative targets and known therapeutic targets for the treatment of chronic myeloid leukemia was constructed. By calculating the 4 topological features (degree, betweenness, closeness, and coreness) of each node in the network, we identified the candidate Qingdai targets according to their network topological importance. The composite compounds of Qingdai and the corresponding candidate major targets were further validated by a molecular docking simulation. Seven components in Qingdai were selected and 32 candidate Qingdai targets were identified; these were more frequently involved in cytokine-cytokine receptor interaction, cell cycle, p53 signaling pathway, MAPK signaling pathway, and immune system-related pathways, which all play important roles in the progression of CML. Finally, the molecular docking simulation showed that 23 pairs of chemical components and candidate Qingdai targets had effective binding. This network-based pharmacology study suggests that Qingdai acts through the regulation of candidate targets to interfere with CML and thus regulates the occurrence and development of CML.