• 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

药物设计中的伪受体模型:连接基于配体和受体的虚拟筛选

Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening.

作者信息

Tanrikulu Yusuf, Schneider Gisbert

机构信息

Institute of Organic Chemistry and Chemical Biology, Johann Wolfgang Goethe-University Frankfurt, Siesmayerstrasse 70, D-60323 Frankfurt, Germany.

出版信息

Nat Rev Drug Discov. 2008 Aug;7(8):667-77. doi: 10.1038/nrd2615. Epub 2008 Jul 18.

DOI:10.1038/nrd2615
PMID:18636071
Abstract

Rational drug design is based on explicit or implicit structure-activity relationship models. Typically, receptor-based or ligand-based strategies are pursued, depending on the information available about known ligands and the receptor structure. Pseudoreceptor models combine the advantages of these two strategies and represent a unifying concept for both receptor mapping and ligand matching. They can provide an entry point for structure-based modelling in drug discovery projects that lack a high-resolution structure of the target. Here, we review the field of pseudoreceptor modelling techniques along with recent hit and lead finding applications, and critically discuss prerequisites, advantages and limitations of the various approaches.

摘要

合理药物设计基于明确或隐含的构效关系模型。通常,根据有关已知配体和受体结构的可用信息,采用基于受体或基于配体的策略。虚拟受体模型结合了这两种策略的优点,为受体图谱绘制和配体匹配提供了一个统一的概念。它们可以为缺乏目标高分辨率结构的药物发现项目中的基于结构的建模提供切入点。在此,我们回顾虚拟受体建模技术领域以及最近的命中和先导化合物发现应用,并批判性地讨论各种方法的先决条件、优点和局限性。

相似文献

1
Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening.药物设计中的伪受体模型:连接基于配体和受体的虚拟筛选
Nat Rev Drug Discov. 2008 Aug;7(8):667-77. doi: 10.1038/nrd2615. Epub 2008 Jul 18.
2
Homology model adjustment and ligand screening with a pseudoreceptor of the human histamine H4 receptor.利用人组胺H4受体的伪受体进行同源性模型调整和配体筛选。
ChemMedChem. 2009 May;4(5):820-7. doi: 10.1002/cmdc.200800443.
3
Novel 2D fingerprints for ligand-based virtual screening.用于基于配体的虚拟筛选的新型二维指纹图谱。
J Chem Inf Model. 2006 Nov-Dec;46(6):2423-31. doi: 10.1021/ci060155b.
4
Virtual screening of biogenic amine-binding G-protein coupled receptors: comparative evaluation of protein- and ligand-based virtual screening protocols.生物胺结合型G蛋白偶联受体的虚拟筛选:基于蛋白质和基于配体的虚拟筛选方案的比较评估。
J Med Chem. 2005 Aug 25;48(17):5448-65. doi: 10.1021/jm050090o.
5
Towards improving compound selection in structure-based virtual screening.迈向改进基于结构的虚拟筛选中的化合物选择。
Drug Discov Today. 2008 Mar;13(5-6):219-26. doi: 10.1016/j.drudis.2007.12.002. Epub 2008 Feb 4.
6
Homology model-based virtual screening for GPCR ligands using docking and target-biased scoring.基于同源性模型,利用对接和靶点偏向性评分进行GPCR配体的虚拟筛选。
J Chem Inf Model. 2008 May;48(5):1104-17. doi: 10.1021/ci8000265. Epub 2008 Apr 26.
7
Development and virtual screening of target libraries.靶标库的开发与虚拟筛选
J Physiol Paris. 2006 Mar-May;99(2-3):232-44. doi: 10.1016/j.jphysparis.2005.12.084. Epub 2006 Feb 3.
8
Virtual screen for ligands of orphan G protein-coupled receptors.孤儿G蛋白偶联受体配体的虚拟筛选
J Chem Inf Model. 2005 Sep-Oct;45(5):1402-14. doi: 10.1021/ci050006d.
9
Discovery of novel HIV entry inhibitors for the CXCR4 receptor by prospective virtual screening.通过前瞻性虚拟筛选发现针对CXCR4受体的新型HIV进入抑制剂。
J Chem Inf Model. 2009 Apr;49(4):810-23. doi: 10.1021/ci800468q.
10
Computational chemistry approaches to drug discovery in signal transduction.信号转导中药物发现的计算化学方法。
Biotechnol J. 2008 Apr;3(4):452-70. doi: 10.1002/biot.200700259.

引用本文的文献

1
Artificial intelligence approaches for anti-addiction drug discovery.用于抗成瘾药物发现的人工智能方法。
Digit Discov. 2025 May 13. doi: 10.1039/d5dd00032g.
2
Discovery of novel drug-like antitubercular hits targeting the MEP pathway enzyme DXPS by strategic application of ligand-based virtual screening.通过基于配体的虚拟筛选策略应用,发现靶向MEP途径酶DXPS的新型类药物抗结核活性化合物。
Chem Sci. 2022 Aug 8;13(36):10686-10698. doi: 10.1039/d2sc02371g. eCollection 2022 Sep 21.
3
Machine Learning and Computational Chemistry for the Endocannabinoid System.
机器学习和计算化学在内源性大麻素系统中的应用。
Methods Mol Biol. 2023;2576:477-493. doi: 10.1007/978-1-0716-2728-0_39.
4
Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance.计算技术在抗癌研究中的新兴前景:概览
Bioengineering (Basel). 2022 Jul 25;9(8):335. doi: 10.3390/bioengineering9080335.
5
In Silico Drug Discovery for Treatment of Virus Diseases.病毒病治疗的计算药物发现。
Adv Exp Med Biol. 2022;1368:73-93. doi: 10.1007/978-981-16-8969-7_4.
6
Computational identification of potential chemoprophylactic agents according to dynamic behavior of peroxisome proliferator-activated receptor gamma.根据过氧化物酶体增殖物激活受体γ的动态行为对潜在化学预防剂进行计算识别。
RSC Adv. 2020 Dec 22;11(1):147-159. doi: 10.1039/d0ra09059j. eCollection 2020 Dec 21.
7
Synthetic inhibitor leads of human tropomyosin receptor kinase A (TrkA).人原肌球蛋白受体激酶A(TrkA)的合成抑制剂先导物。
RSC Med Chem. 2020 Jan 10;11(3):370-377. doi: 10.1039/c9md00554d. eCollection 2020 Mar 1.
8
Merging Ligand-Based and Structure-Based Methods in Drug Discovery: An Overview of Combined Virtual Screening Approaches.将基于配体和基于结构的方法合并用于药物发现:联合虚拟筛选方法概述。
Molecules. 2020 Oct 15;25(20):4723. doi: 10.3390/molecules25204723.
9
Computer-Aided Ligand Discovery for Estrogen Receptor Alpha.计算机辅助配体发现雌激素受体 α。
Int J Mol Sci. 2020 Jun 12;21(12):4193. doi: 10.3390/ijms21124193.
10
Epothilones: From discovery to clinical trials.埃坡霉素:从发现到临床试验。
Curr Top Med Chem. 2014;14(20):2312-21. doi: 10.2174/1568026614666141130095855.