In silico-based screen synergistic drug combinations from herb medicines: a case using Cistanche tubulosa

Autor: Fengxia Shen, Chunli Zheng, Ziyin Wu, Jianling Liu, Jun Xue, Wei Xiao, Jinglin Zhu, Jingjing Liu, Xiaogang Li, Yonghua Wang, Zonghui Qin, Xuetong Chen
Jazyk: angličtina
Rok vydání: 2017
Předmět:
Zdroj: Scientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
Scientific Reports
ISSN: 2045-2322
DOI: 10.1038/s41598-017-16571-3
Popis: 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.
Databáze: OpenAIRE
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