Hierarchical Superposition Framework Reveals the Complex Effects of Natural Medicine Formulas

This study introduces the hierarchical superposition pharmacodynamic model (HSPM), a novel approach to understanding the complex effects of natural medicine formulas, particularly in traditional Chinese medicine. The HSPM uses human protein–protein interaction networks to quantify interactions between drug targets and disease proteins, assessing the impact of drugs and their combinations on diseases. It calculates pharmacodynamic action scores to account for drug effect transmission across hierarchical levels, considering decay rates and node degree values. Validated against extensive datasets, HSPM differentiates between known effective and unknown/ineffective drug–disease pairs, highlighting its predictive modeling potential. Applied to traditional Chinese medicine, HSPM reveals synergistic effects and identifies new drug combinations with therapeutic potential, such as against hepatocellular carcinoma. Cellular experiments confirm the model's predictions, enhancing the efficacy of specific drug combinations. This research bridges physics and pharmacology, offering a promising framework for comprehending drug combination effects and guiding new therapeutic strategies for complex diseases.