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一种基于网络药理学的方法来研究针对亨廷顿舞蹈病的新型中药配方，并通过支持向量机模型进行验证。

A Network Pharmacology-Based Approach to Investigate the Novel TCM Formula against Huntington's Disease and Validated by Support Vector Machine Model.

作者信息

Dai Wenjie, Chen Hsin-Yi, Chen Calvin Yu-Chian

机构信息

School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen 510275, China.

Department of Medical Research, China Medical University Hospital, Taichung 40447, Taiwan.

出版信息

Evid Based Complement Alternat Med. 2018 Dec 11;2018:6020197. doi: 10.1155/2018/6020197. eCollection 2018.

DOI:10.1155/2018/6020197
PMID:30643534
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6311282/
Abstract

Several pathways are crucial in Huntington's disease (HD). Based on the concept of multitargets, network pharmacology-based analysis was employed to find out related proteins in disease network. The network target method aims to find out related mechanism of efficacy substances in rational design way. Traditional Chinese medicine prescriptions would be used for research and development against HD. Virtual screening was performed to obtain drug molecules with high binding capacity from traditional Chinese medicine (TCM) database@Taiwan. Quantitative structure-activity relationship (QSAR) models were conducted by MLR, SVM, CoMFA, and CoMSIA, constructed to predict the bioactivities of candidates. The compounds with high-dock score were further analyzed compared with control. Traditional Chinese medicine reported in the literature could be the training set provided for constructing novel formula by SVM model. We tried to find a novel formula that can bind well with these targets at the same time, which indicates our design could be highly related to the HD. Additionally, the candidates would validate by a long-term molecular dynamics (MD) simulation, 5 microseconds. Thus, we suggested the herbs , etc. which contained active compounds might be a novel medicine formula toward Huntington's disease.

摘要

在亨廷顿舞蹈症（HD）中，有几条途径至关重要。基于多靶点概念，采用基于网络药理学的分析方法来找出疾病网络中的相关蛋白质。网络靶点方法旨在以合理设计的方式找出有效物质的相关机制。将使用中药方剂来研发抗HD药物。通过虚拟筛选从台湾中药数据库中获取具有高结合能力的药物分子。通过多元线性回归（MLR）、支持向量机（SVM）、比较分子场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）构建定量构效关系（QSAR）模型，以预测候选物的生物活性。将高对接分数的化合物与对照进行进一步分析比较。文献中报道的中药可作为支持向量机模型构建新方剂的训练集。我们试图找到一种能同时与这些靶点良好结合的新方剂，这表明我们的设计可能与HD高度相关。此外，候选物将通过5微秒的长期分子动力学（MD）模拟进行验证。因此，我们认为含有活性化合物的草药等可能是一种针对亨廷顿舞蹈症的新型药物配方。

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