Exploring polypharmacology of some natural products using similarity search target fishing approach

I. Almasri
{"title":"Exploring polypharmacology of some natural products using similarity search target fishing approach","authors":"I. Almasri","doi":"10.1504/IJCBDD.2018.096126","DOIUrl":null,"url":null,"abstract":"Natural products have long been considered as important sources for drug discovery due to the diversity of their chemical structures and broad range of biological activities attained by modulation of different biological targets. Therefore, the identification of the molecular targets of natural products is a milestone step in rational design of more potent and safer compounds. In this work, we explored the polypharmacology of three natural products having pleiotropic health beneficial effects: resveratrol, curcumin and berberine, using a ligand-based target fishing approach. The fishing protocol was started with the generation of a chemogenomic database that links individual targets with specific target ligands or group of drugs. Targets profile was then generated using ROCS software. The applied method was able not only to retrieve known targets within the top-ranked list for the natural compounds but also identified off-targets which were found by docking simulation to be potential targets and were consistent with recently identified bioactivities of these compounds.","PeriodicalId":13612,"journal":{"name":"Int. J. Comput. Biol. Drug Des.","volume":"28 1","pages":"295-309"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Comput. Biol. Drug Des.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJCBDD.2018.096126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Natural products have long been considered as important sources for drug discovery due to the diversity of their chemical structures and broad range of biological activities attained by modulation of different biological targets. Therefore, the identification of the molecular targets of natural products is a milestone step in rational design of more potent and safer compounds. In this work, we explored the polypharmacology of three natural products having pleiotropic health beneficial effects: resveratrol, curcumin and berberine, using a ligand-based target fishing approach. The fishing protocol was started with the generation of a chemogenomic database that links individual targets with specific target ligands or group of drugs. Targets profile was then generated using ROCS software. The applied method was able not only to retrieve known targets within the top-ranked list for the natural compounds but also identified off-targets which were found by docking simulation to be potential targets and were consistent with recently identified bioactivities of these compounds.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用相似搜索靶标垂钓法探索一些天然产物的多药理学
天然产物由于其化学结构的多样性和通过调节不同的生物靶点而获得的广泛的生物活性,一直被认为是药物发现的重要来源。因此,鉴定天然产物的分子靶点是合理设计更有效和更安全的化合物的里程碑式的一步。在这项工作中,我们探索了三种具有多效健康益处的天然产物:白藜芦醇、姜黄素和小檗碱的多药理学,采用基于配体的靶捕鱼方法。捕鱼协议开始于化学基因组数据库的生成,该数据库将单个靶标与特定靶标配体或药物组联系起来。然后使用ROCS软件生成目标配置文件。所应用的方法不仅能够检索到天然化合物排名靠前的已知靶点,而且能够识别出通过对接模拟发现的潜在靶点,并且与这些化合物最近鉴定的生物活性一致的非靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Random forest with SMOTE and ensemble feature selection for cervical cancer diagnosis A review on speech organ diseases and cancer detection using artificial intelligence In silico phytochemical repurposing of natural molecules as entry inhibitors against RBD of the spike protein of SARS-CoV-2 using molecular docking studies Generation of 2D-QSAR and pharmacophore models for fishing better anti-leishmanial therapeutics Computational identification of personal genetic variants in an identical twin sisters' family
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1