KIZ OpenIR  > 结构生物信息学
A strategy to find novel candidate anti-Alzheimer’s disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants
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
2018
发表期刊PeerJ
期号6页码:e4756
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.

关键词Alzheimer’s Disease Molecular Docking Candidate Drugs
DOI10.7717/peerj.4756
语种英语
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.kiz.ac.cn/handle/152453/12403
专题结构生物信息学
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
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Bi-Wen Chen,Jing-Fei Huang,Guang-Hui Wang,等. 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.
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