Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi'an, China.
Lab of Systems Pharmacology, Center of Bioinformatics, College of Life Science, Northwest A&F University, Yangling, China.
Sci Rep. 2017 Nov 27;7(1):16364. doi: 10.1038/s41598-017-16571-3.
Neuroinflammation is characterized by the elaborated inflammatory response repertoire of central nervous system tissue. The limitations of the current treatments for neuroinflammation are well-known side effects in the clinical trials of monotherapy. Drug combination therapies are promising strategies to overcome the compensatory mechanisms and off-target effects. However, discovery of synergistic drug combinations from herb medicines is rare. Encouraged by the successfully applied cases we move on to investigate the effective drug combinations based on system pharmacology among compounds from Cistanche tubulosa (SCHENK) R. WIGHT. Firstly, 63 potential bioactive compounds, the related 133 direct and indirect targets are screened out by Drug-likeness evaluation combined with drug targeting process. Secondly, Compound-Target network is built to acquire the data set for predicting drug combinations. We list the top 10 drug combinations which are employed by the algorithm Probability Ensemble Approach (PEA), and Compound-Target-Pathway network is then constructed by the 12 compounds of the combinations, targets, and pathways to unearth the corresponding pharmacological actions. Finally, an integrating pathway approach is developed to elucidate the therapeutic effects of the herb in different pathological features-relevant biological processes. Overall, the method may provide a productive avenue for developing drug combination therapeutics.
神经炎症的特征是中枢神经系统组织中精心设计的炎症反应谱。目前针对神经炎症的治疗方法存在局限性，在单药治疗的临床试验中存在已知的副作用。药物联合治疗是克服代偿机制和脱靶效应的有前途的策略。然而，从草药中发现协同药物组合的情况很少见。在成功应用案例的鼓舞下，我们继续研究基于系统药理学的有效药物组合，这些组合来自肉苁蓉（SCHENK）R.怀特。首先，通过药物相似性评估结合药物靶向过程筛选出 63 种潜在的生物活性化合物和相关的 133 个直接和间接靶点。其次，构建化合物-靶点网络，获取用于预测药物组合的数据集。我们列出了算法 Probability Ensemble Approach (PEA) 选用的前 10 种药物组合，然后通过组合、靶点和通路的 12 种化合物构建化合物-靶点-通路网络，以揭示相应的药理作用。最后，开发了一种整合途径方法来阐明该草药在不同病理特征相关生物过程中的治疗效果。总的来说，该方法可能为开发药物组合疗法提供了一条富有成效的途径。
