Wang Aoyi, Peng Haoyang, Wang Yingdong, Zhang Haoran, Cheng Caiping, Zhao Jinzhong, Zhang Wuxia, Chen Jianxin, Li Peng
Shanxi Key Lab for Modernization of TCVM, College of Basic Sciences, Shanxi Agricultural University, 1 Mingxian South Road, Taigu District, Jinzhong, 030801, China.
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, 11 North Third Ring Road East, Chaoyang District, Beijing 100029, China.
Brief Bioinform. 2024 Nov 22;26(1). doi: 10.1093/bib/bbaf078.
The biological targets of traditional Chinese medicine (TCM) are the core effectors mediating the interaction between TCM and the human body. Identification of TCM targets is essential to elucidate the chemical basis and mechanisms of TCM for treating diseases. Given the chemical complexity of TCM, both in silico high-throughput compound-target interaction predicting models and biological profile-based methods have been commonly applied for identifying TCM targets based on the structural information of TCM chemical components and biological information, respectively. However, the existing methods lack the integration of TCM chemical and biological information, resulting in difficulty in the systematic discovery of TCM action pathways. To solve this problem, we propose a novel target identification model NP-TCMtarget to explore the TCM target path by combining the overall chemical and biological profiles. First, NP-TCMtarget infers TCM effect targets by calculating associations between herb/disease inducible gene expression profiles and specific gene signatures for 8233 targets. Then, NP-TCMtarget utilizes a constructed binary classification model to predict binding targets of herbal ingredients. Finally, we can distinguish TCM direct and indirect targets by comparing the effect targets and binding targets to establish the action pathways of herbal component-direct target-indirect target by mapping TCM targets in the biological molecular network. We apply NP-TCMtarget to the formula XiaoKeAn to demonstrate the power of revealing the action pathways of herbal formula. We expect that this novel model could provide a systematic framework for exploring the molecular mechanisms of TCM at the target level. NP-TCMtarget is available at http://www.bcxnfz.top/NP-TCMtarget.
中药的生物学靶点是介导中药与人体相互作用的核心效应分子。确定中药靶点对于阐明中药治疗疾病的化学基础和作用机制至关重要。鉴于中药的化学复杂性，基于计算机的高通量化合物-靶点相互作用预测模型和基于生物学特征的方法已分别常用于根据中药化学成分的结构信息和生物学信息来确定中药靶点。然而，现有方法缺乏对中药化学和生物学信息的整合，导致难以系统地发现中药作用途径。为了解决这一问题，我们提出了一种新型的靶点识别模型NP-TCMtarget，通过结合整体化学和生物学特征来探索中药靶点路径。首先，NP-TCMtarget通过计算草药/疾病诱导基因表达谱与8233个靶点的特定基因特征之间的关联来推断中药效应靶点。然后，NP-TCMtarget利用构建的二元分类模型来预测草药成分的结合靶点。最后，我们可以通过比较效应靶点和结合靶点来区分中药直接和间接靶点，通过在生物分子网络中映射中药靶点来建立草药成分-直接靶点-间接靶点的作用途径。我们将NP-TCMtarget应用于消渴安方剂，以证明其揭示草药方剂作用途径的能力。我们期望这个新模型能够为在靶点水平探索中药分子机制提供一个系统的框架。NP-TCMtarget可在http://www.bcxnfz.top/NP-TCMtarget获取。
