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基于知识的神经内分泌免疫调节(NIM)分子网络构建及其应用。

Knowledge-Based Neuroendocrine Immunomodulation (NIM) Molecular Network Construction and Its Application.

机构信息

Beijing Institute of Pharmacology and Toxicology, Beijing 100850, China.

State Key Laboratory of Toxicology and Medical Countermeasures, Beijing 100850, China.

出版信息

Molecules. 2018 May 30;23(6):1312. doi: 10.3390/molecules23061312.

Abstract

Growing evidence shows that the neuroendocrine immunomodulation (NIM) network plays an important role in maintaining and modulating body function and the homeostasis of the internal environment. The disequilibrium of NIM in the body is closely associated with many diseases. In the present study, we first collected a core dataset of NIM signaling molecules based on our knowledge and obtained 611 NIM signaling molecules. Then, we built a NIM molecular network based on the MetaCore database and analyzed the signaling transduction characteristics of the core network. We found that the endocrine system played a pivotal role in the bridge between the nervous and immune systems and the signaling transduction between the three systems was not homogeneous. Finally, employing the forest algorithm, we identified the molecular hub playing an important role in the pathogenesis of rheumatoid arthritis (RA) and Alzheimer's disease (AD), based on the NIM molecular network constructed by us. The results showed that , , , , , , and might be the key molecules for RA, while , , , and might be the key molecules for AD. The molecular hub may be a potentially druggable target for these two complex diseases based on the literature. This study suggests that the NIM molecular network in this paper combined with the forest algorithm might provide a useful tool for predicting drug targets and understanding the pathogenesis of diseases. Therefore, the NIM molecular network and the corresponding online tool will not only enhance research on complex diseases and system biology, but also promote the communication of valuable clinical experience between modern medicine and Traditional Chinese Medicine (TCM).

摘要

越来越多的证据表明,神经内分泌免疫调节(NIM)网络在维持和调节身体功能以及内环境稳态方面发挥着重要作用。体内 NIM 的失衡与许多疾病密切相关。在本研究中,我们首先基于我们的知识收集了一个 NIM 信号分子的核心数据集,并获得了 611 个 NIM 信号分子。然后,我们基于 MetaCore 数据库构建了一个 NIM 分子网络,并分析了核心网络的信号转导特征。我们发现内分泌系统在神经系统和免疫系统之间的桥梁中起着关键作用,并且三个系统之间的信号转导并非均匀的。最后,我们采用森林算法,根据我们构建的 NIM 分子网络,确定了在类风湿关节炎(RA)和阿尔茨海默病(AD)发病机制中起重要作用的分子枢纽。结果表明,、、、、、、可能是 RA 的关键分子,而、、、和可能是 AD 的关键分子。基于文献,该分子枢纽可能是这两种复杂疾病潜在的可药物治疗靶点。本研究表明,本文构建的 NIM 分子网络结合森林算法,可能为预测药物靶点和理解疾病发病机制提供有用的工具。因此,NIM 分子网络及其相应的在线工具不仅将增强对复杂疾病和系统生物学的研究,还将促进现代医学与传统医学(TCM)之间有价值的临床经验交流。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d83b/6099962/846721a2bd11/molecules-23-01312-g001.jpg

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