Preprint / Version 1

Network-based modeling of herb combinations in traditional Chinese medicine

Authors

  • Yinyin Wang University of Helsinki, Finland
  • Hongbin Yang Department of Chemistry, University of Cambridge, Cambridge, UK
  • Linxiao Chen Department of Mathematics and Statistics, University of Helsinki, Finland
  • Mohieddin Jafari University of Helsinki, Finland
  • Jing Tang Faculty of Medicine of the University of Helsinki and Group Leader of Network Pharmacology for Precision Medicine group, Finland

Keywords:

natural products, herb combinations, network modeling, Traditional Chinese medicine (TCM), formulae, network pharmacology

Abstract

Traditional Chinese medicine (TCM) has been practiced for thousands of years for treating human diseases. In comparison to modern medicine, one of the advantages of TCM is the principle of herb compatibility, known as TCM formulae. A TCM formula usually consists of multiple herbs to achieve the maximum treatment effects, where their interactions are believed to elicit the therapeutic effects. Despite being a fundamental component of TCM, the rationale of combining specific herb combinations remains unclear. In this study, we proposed a network-based method to quantify the interactions in herb pairs. We constructed a protein–protein interaction network for a given herb pair by retrieving the associated ingredients and protein targets, and determined multiple network-based distances including the closest, shortest, center, kernel, and separation, both at the ingredient and at the target levels. We found that the frequently used herb pairs tend to have shorter distances compared to random herb pairs, suggesting that a therapeutic herb pair is more likely to affect neighboring proteins in the human interactome. Furthermore, we found that the center distance determined at the ingredient level improves the discrimination of top-frequent herb pairs from random herb pairs, suggesting the rationale of considering the topologically important ingredients for inferring the mechanisms of action of TCM. Taken together, we have provided a network pharmacology framework to quantify the degree of herb interactions, which shall help explore the space of herb combinations more effectively to identify the synergistic compound interactions based on network topology. Keywords: natural products, herb combinations, network modeling, Traditional Chinese medicine (TCM), formulae, network pharmacology