• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用生物途径阐明药物发现。

Illuminating drug discovery with biological pathways.

作者信息

Apic Gordana, Ignjatovic Tijana, Boyer Scott, Russell Robert B

机构信息

Cambridge Cell Networks, William Gates Building, Cambridge CB3 0FD, UK.

出版信息

FEBS Lett. 2005 Mar 21;579(8):1872-7. doi: 10.1016/j.febslet.2005.02.023.

DOI:10.1016/j.febslet.2005.02.023
PMID:15763566
Abstract

Systems biology promises to impact significantly on the drug discovery process. One of its ultimate goals is to provide an understanding of the complete set of molecular mechanisms describing an organism. Although this goal is a long way off, many useful insights can already come from currently available information and technology. One of the biggest challenges in drug discovery today is the high attrition rate: many promising candidates prove ineffective or toxic owing to a poor understanding of the molecular mechanisms of biological systems they target. A "systems" approach can help identify pathways related to a disease and can suggest secondary effects of drugs that might cause these problems and thus ultimately improve the drug discovery pipeline.

摘要

系统生物学有望对药物发现过程产生重大影响。其最终目标之一是深入了解描述生物体的全套分子机制。尽管这一目标仍遥不可及,但目前可用的信息和技术已能带来许多有用的见解。当今药物发现面临的最大挑战之一是高损耗率:由于对所靶向生物系统的分子机制了解不足,许多有潜力的候选药物被证明无效或有毒。“系统”方法有助于识别与疾病相关的途径,并能提示可能导致这些问题的药物副作用,从而最终改进药物研发流程。

相似文献

1
Illuminating drug discovery with biological pathways.用生物途径阐明药物发现。
FEBS Lett. 2005 Mar 21;579(8):1872-7. doi: 10.1016/j.febslet.2005.02.023.
2
Systems biology in drug discovery.药物研发中的系统生物学
Nat Biotechnol. 2004 Oct;22(10):1253-9. doi: 10.1038/nbt1017.
3
[Development of antituberculous drugs: current status and future prospects].[抗结核药物的研发:现状与未来前景]
Kekkaku. 2006 Dec;81(12):753-74.
4
Towards a molecular characterisation of pathological pathways.
FEBS Lett. 2008 Apr 9;582(8):1259-65. doi: 10.1016/j.febslet.2008.02.014. Epub 2008 Feb 20.
5
Understanding mechanisms of toxicity: insights from drug discovery research.理解毒性机制:来自药物发现研究的见解
Toxicol Appl Pharmacol. 2008 Mar 1;227(2):163-78. doi: 10.1016/j.taap.2007.10.022. Epub 2007 Nov 4.
6
Protease proteomics: revealing protease in vivo functions using systems biology approaches.蛋白酶组学:运用系统生物学方法揭示蛋白酶的体内功能
Mol Aspects Med. 2008 Oct;29(5):339-58. doi: 10.1016/j.mam.2008.04.003. Epub 2008 May 1.
7
Exploiting complexity and the robustness of network architecture for drug discovery.利用网络架构的复杂性和稳健性进行药物发现。
J Pharmacol Exp Ther. 2008 Apr;325(1):1-9. doi: 10.1124/jpet.107.131276. Epub 2008 Jan 17.
8
Interactome: gateway into systems biology.相互作用组:通往系统生物学的大门。
Hum Mol Genet. 2005 Oct 15;14 Spec No. 2:R171-81. doi: 10.1093/hmg/ddi335. Epub 2005 Sep 14.
9
Interaction networks: from protein functions to drug discovery. A review.相互作用网络:从蛋白质功能到药物发现。综述。
Pathol Biol (Paris). 2009 Jun;57(4):324-33. doi: 10.1016/j.patbio.2008.10.004. Epub 2008 Dec 13.
10
Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery.走向定量生物学:整合生物信息以阐明疾病途径并指导药物发现。
Biotechnol Annu Rev. 2005;11:1-68. doi: 10.1016/S1387-2656(05)11001-1.

引用本文的文献

1
BPP: a platform for automatic biochemical pathway prediction.BPP:一个用于自动生化途径预测的平台。
Brief Bioinform. 2024 Jul 25;25(5). doi: 10.1093/bib/bbae355.
2
Identifying patterns to uncover the importance of biological pathways on known drug repurposing scenarios.识别模式以揭示生物途径对已知药物再利用场景的重要性。
BMC Genomics. 2024 Jan 9;25(1):43. doi: 10.1186/s12864-023-09913-1.
3
Protein-Protein Interaction Network Analysis Using NetworkX.使用 NetworkX 进行蛋白质-蛋白质相互作用网络分析。
Methods Mol Biol. 2023;2690:457-467. doi: 10.1007/978-1-0716-3327-4_35.
4
Protein-protein interaction (PPI) network analysis reveals important hub proteins and sub-network modules for root development in rice (Oryza sativa).蛋白质-蛋白质相互作用(PPI)网络分析揭示了水稻(Oryza sativa)根系发育过程中的重要枢纽蛋白和子网模块。
J Genet Eng Biotechnol. 2023 May 29;21(1):69. doi: 10.1186/s43141-023-00515-8.
5
Natural radioprotectors and their impact on cancer drug discovery.天然辐射防护剂及其对癌症药物研发的影响。
Radiat Oncol J. 2018 Dec;36(4):265-275. doi: 10.3857/roj.2018.00381. Epub 2018 Dec 31.
6
Discriminate the response of Acute Myeloid Leukemia patients to treatment by using proteomics data and Answer Set Programming.利用蛋白质组学数据和 Answer Set 编程来区分急性髓系白血病患者对治疗的反应。
BMC Bioinformatics. 2018 Mar 8;19(Suppl 2):59. doi: 10.1186/s12859-018-2034-4.
7
Drug Metabolism in Preclinical Drug Development: A Survey of the Discovery Process, Toxicology, and Computational Tools.临床前药物研发中的药物代谢:发现过程、毒理学及计算工具综述
Curr Drug Metab. 2017;18(6):556-565. doi: 10.2174/1389200218666170316093301.
8
The Combination of Three Components Derived from Sheng MaiSan Protects Myocardial Ischemic Diseases and Inhibits Oxidative Stress via Modulating MAPKs and JAK2-STAT3 Signaling Pathways Based on Bioinformatics Approach.
Front Pharmacol. 2017 Jan 31;8:21. doi: 10.3389/fphar.2017.00021. eCollection 2017.
9
An integrated pathway interaction network for the combination of four effective compounds from ShengMai preparations in the treatment of cardio-cerebral ischemic diseases.生脉制剂中四种有效化合物联合治疗心脑血管缺血性疾病的整合通路相互作用网络
Acta Pharmacol Sin. 2015 Nov;36(11):1337-48. doi: 10.1038/aps.2015.70. Epub 2015 Oct 12.
10
Generation of stable ARE- driven reporter system for monitoring oxidative stress.用于监测氧化应激的稳定ARE驱动报告系统的构建
Daru. 2015 Aug 1;23(1):38. doi: 10.1186/s40199-015-0122-9.