A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants
文献类型:期刊论文
作者 | Bi-Wen Chen1,2; Jing-Fei Huang2,3,5; Guang-Hui Wang1; Gong-Hua Li2,3; Jia-Qian Liu4; Jun-Juan Zheng2,3; Qian Wang2,3; Hui-Juan Li2,3; Shao-Xing Dai2,3 |
刊名 | PeerJ
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出版日期 | 2018 |
期号 | 6页码:e4756 |
关键词 | Alzheimer’s Disease Molecular Docking Candidate Drugs |
DOI | 10.7717/peerj.4756 |
英文摘要 | Background.Alzheimer’disease(AD)isanultimatelyfataldegenerativebraindisorderthat has an increasingly large burden on health and social care systems. There are onlyfive drugs for AD on the market, and no new effective medicines have been discoveredformanyyears.Chinesemedicinalplantshavebeenusedtotreatdiseasesforthousandsof years, and screening herbal remedies is a way to develop new drugs. Methods. We used molecular docking to screen 30,438 compounds from TraditionalChinese Medicine (TCM) against a comprehensive list of AD target proteins. TCMcompounds in the top 0.5% of binding affinity scores for each target protein wereselected as our research objects. Structural similarities between existing drugs fromDrugBank database and selected TCM compounds as well as the druggability of ourcandidate compounds were studied. Finally, we searched the CNKI database to obtainstudies on anti-AD Chinese plants from 2007 to 2017, and only clinical studies wereincluded. Results. A total of 1,476 compounds (top 0.5%) were selected as drug candidates. Mostof these compounds are abundantly found in plants used for treating AD in China,especiallytheplantsfromtwogeneraPanaxandMorus.Weclassifiedthecompoundsbysingle target and multiple targets and analyzed the interactions between target proteinsand compounds. Analysis of structural similarity revealed that 17 candidate anti-ADcompoundswerestructurallyidenticalto14existingapproveddrugs.MostofthemhavebeenreportedtohaveapositiveeffectinAD.Afterfilteringforcompounddruggability,we identified 11 anti-AD compounds with favorable properties, seven of which arefound in anti-AD Chinese plants. Of 11 anti-AD compounds, four compounds 5,862,5,863, 5,868, 5,869 have anti-inflammatory activity. The compound 28,814 mainly hasimmunoregulatory activity. The other six compounds have not yet been reported forany biology activity at present. Discussion.NaturalcompoundsfromTCMprovideabroadprospectforthescreeningof anti-AD drugs. In this work, we established networks to systematically study theconnections among natural compounds, approved drugs, TCM plants and AD targetproteinswiththegoalofidentifyingpromisingdrugcandidates.Wehopethatourstudywill facilitate in-depth research for the treatment of AD in Chinese medicine. |
语种 | 英语 |
源URL | [http://159.226.149.26:8080/handle/152453/12403] ![]() |
专题 | 昆明动物研究所_结构生物信息学 |
通讯作者 | Shao-Xing Dai |
作者单位 | 1.College of Pharmaceutical Sciences, Soochow University, Suzhou, Jiangsu, China 2.State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China 3.Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China 4.School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China 5.KIZ-SU Joint Laboratory of Animal Models and Drug Development, College of Pharmaceutical Sciences, Soochow University, Kunming, Yunnan, China |
推荐引用方式 GB/T 7714 | Bi-Wen Chen,Jing-Fei Huang,Guang-Hui Wang,et al. A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants[J]. PeerJ,2018(6):e4756. |
APA | Bi-Wen Chen.,Jing-Fei Huang.,Guang-Hui Wang.,Gong-Hua Li.,Jia-Qian Liu.,...&Shao-Xing Dai.(2018).A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants.PeerJ(6),e4756. |
MLA | Bi-Wen Chen,et al."A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants".PeerJ .6(2018):e4756. |
入库方式: OAI收割
来源:昆明动物研究所
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