ORIGINAL RESEARCH article

Front. Pharmacol.

Sec. Experimental Pharmacology and Drug Discovery

Volume 16 - 2025 | doi: 10.3389/fphar.2025.1594308

This article is part of the Research TopicIntelligent Computing for Integrating Multi-Omics Data in Disease Diagnosis and Drug DevelopmentView all 8 articles

Understanding the molecular basis of herbal medicines for cough variant asthma under the guidance of traditional herbal theories

Provisionally accepted
Rui  LiuRui Liu1Jiaqi  YaoJiaqi Yao1Yihang  SuiYihang Sui1Yinnan  ZhangYinnan Zhang1Seng  KhoSeng Kho1Yingli  ZhuYingli Zhu2Ninghua  TanNinghua Tan1Yinyin  WangYinyin Wang1*
  • 1China Pharmaceutical University, Nanjing, China
  • 2Beijing University of Chinese Medicine, Beijing, Beijing Municipality, China

The final, formatted version of the article will be published soon.

Despite of the obvious clinical efficacy of herbal formula Suhuang for cough variant asthma (CVA), the underlying mechanisms of action (MOAs) are not fully understood. As TCM is a unique system under the guide of traditional herbal theories for disease treatment, we here aimed to decipher the how herbal medicine play therapeutic effects on CVA disease under the guidance of TCM theories based on their transcriptional perturbation. To achieve this goal, we offer a new paradigm for understanding the molecular basis of herbal medicines by integrating gene perturbation data, GNN models, and network proximity methods within the framework of herbal medicine theories. We found that traditional herbal theories are closely related to their efficacy: 1) Meridian classifications of one herb are closely related to its gene perturbation distribution in different organs; 2) Herbal combination and their therapeutic effects are closely related to their target network proximity. Especially, network proximity analysis between molecular targets and disease-specific genes revealed the essence of "JUN-CHEN-ZUO-SHI" theory and lung-large intestine theories; 3) Using traditional herbal theories as features, we also developed two graph neural network models for herb-disease association and herb-herb combination prediction to identify potential active ingredients and combinations for CVA disease. In summary, our study offers a paradigm for understand the molecular basis of herbal medicines as well as their combinations for CVA disease with computational methods from the review of herbal theories.

Keywords: Herbal Medicine Theory, Graph neural networks, Meridian theory, Network proximity, Suhuang formula, Cough Variant Asthma (CVA) Abbreviations CVA: cough variant asthma, GNN: graph neural network, PIC: post-infectious cough

Received: 15 Mar 2025; Accepted: 05 May 2025.

Copyright: © 2025 Liu, Yao, Sui, Zhang, Kho, Zhu, Tan and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Yinyin Wang, China Pharmaceutical University, Nanjing, China

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