• 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

针对蛋白质-蛋白质相互作用的药物发现的热点分析。

Hot-spot analysis for drug discovery targeting protein-protein interactions.

机构信息

a Department of Life Sciences , Barcelona Supercomputing Center (BSC) , Barcelona , Spain.

b Structural Biology Unit , Institut de Biologia Molecular de Barcelona (IBMB), CSIC , Barcelona , Spain.

出版信息

Expert Opin Drug Discov. 2018 Apr;13(4):327-338. doi: 10.1080/17460441.2018.1430763. Epub 2018 Jan 29.

DOI:10.1080/17460441.2018.1430763
PMID:29376444
Abstract

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

摘要

蛋白质-蛋白质相互作用对于生物过程和病理情况非常重要,是药物发现的有吸引力的靶点。然而,针对蛋白质-蛋白质相互作用的合理药物设计仍然极具挑战性。热点残基被视为靶向此类相互作用的最佳选择,但它们的鉴定需要详细的结构和能量特征描述,而这仅适用于一小部分蛋白质相互作用。

涵盖内容

在这篇综述中,作者介绍了多种已报道的计算方法,这些方法可用于搜索热点并对接蛋白质-蛋白质复合物进行结构建模,以对具有治疗意义的蛋白质-蛋白质界面的小分子抑制剂进行合理化发现。计算分析和对接有助于定位界面,分子动力学可用于寻找合适的腔,热点预测可集中搜索蛋白质-蛋白质相互作用的抑制剂。

专家意见

将合理药物设计方法应用于蛋白质-蛋白质相互作用的主要困难在于,在大多数情况下,复合物结构不可用。幸运的是,计算对接可以补充实验数据。未来值得探索的一个有趣方面是将这些针对 PPI 的策略与大规模突变分析相结合。

相似文献

1
Hot-spot analysis for drug discovery targeting protein-protein interactions.针对蛋白质-蛋白质相互作用的药物发现的热点分析。
Expert Opin Drug Discov. 2018 Apr;13(4):327-338. doi: 10.1080/17460441.2018.1430763. Epub 2018 Jan 29.
2
Computational prediction of protein hot spot residues.蛋白质热点残基的计算预测。
Curr Pharm Des. 2012;18(9):1255-65. doi: 10.2174/138161212799436412.
3
Hot spots in protein-protein interfaces: towards drug discovery.蛋白质-蛋白质相互作用界面的热点:迈向药物发现
Prog Biophys Mol Biol. 2014 Nov-Dec;116(2-3):165-73. doi: 10.1016/j.pbiomolbio.2014.06.003. Epub 2014 Jul 2.
4
Structural Prediction of Protein-Protein Interactions by Docking: Application to Biomedical Problems.蛋白质-蛋白质相互作用的对接结构预测:在生物医学问题中的应用。
Adv Protein Chem Struct Biol. 2018;110:203-249. doi: 10.1016/bs.apcsb.2017.06.003. Epub 2017 Aug 31.
5
Protein-protein docking and hot-spot prediction for drug discovery.蛋白质-蛋白质对接和药物发现中的热点预测。
Curr Pharm Des. 2012;18(30):4607-18. doi: 10.2174/138161212802651599.
6
Modeling Binding Affinity of Pathological Mutations for Computational Protein Design.用于计算蛋白质设计的病理突变结合亲和力建模
Methods Mol Biol. 2017;1529:139-159. doi: 10.1007/978-1-4939-6637-0_6.
7
Protein-protein interaction inhibitors: advances in anticancer drug design.蛋白质-蛋白质相互作用抑制剂:抗癌药物设计的进展。
Expert Opin Drug Discov. 2016 Oct;11(10):957-68. doi: 10.1080/17460441.2016.1223038. Epub 2016 Sep 2.
8
Protein-Protein Docking in Drug Design and Discovery.药物设计与发现中的蛋白质-蛋白质对接
Methods Mol Biol. 2018;1762:285-305. doi: 10.1007/978-1-4939-7756-7_15.
9
Computational approaches for the design of modulators targeting protein-protein interactions.针对靶向蛋白质-蛋白质相互作用的调节剂设计的计算方法。
Expert Opin Drug Discov. 2023 Mar;18(3):315-333. doi: 10.1080/17460441.2023.2171396. Epub 2023 Feb 23.
10
Docking-based identification of small-molecule binding sites at protein-protein interfaces.基于对接的蛋白质-蛋白质界面小分子结合位点鉴定
Comput Struct Biotechnol J. 2020;18:3750-3761. doi: 10.1016/j.csbj.2020.11.029. Epub 2020 Nov 21.

引用本文的文献

1
Hot-Spot-Guided Generative Deep Learning for Drug-Like PPI Inhibitor Design.用于类药物蛋白质-蛋白质相互作用抑制剂设计的热点引导生成式深度学习
Interdiscip Sci. 2025 Sep 2. doi: 10.1007/s12539-025-00756-w.
2
Druggability assessments of small peptides as protein-protein interaction inhibitors targeting EED-EZH2 binding within the Polycomb Repressive Complex 2 (PRC2), an epigenetic regulator.小肽作为靶向多梳抑制复合物2(PRC2,一种表观遗传调控因子)中EED-EZH2结合的蛋白质-蛋白质相互作用抑制剂的成药潜力评估。
Mol Divers. 2025 Aug 15. doi: 10.1007/s11030-025-11321-4.
3
Structural insights into Beclin 1 interactions with it's regulators for autophagy modulation.
对Beclin 1与其自噬调节因子相互作用的结构见解。
Comput Struct Biotechnol J. 2025 Jul 7;27:3005-3035. doi: 10.1016/j.csbj.2025.06.044. eCollection 2025.
4
Mycobacterium susceptibility to ivermectin by inhibition of eccD3, an ESX-3 secretion system component.通过抑制ESX-3分泌系统组分eccD3检测分枝杆菌对伊维菌素的敏感性
PLoS Comput Biol. 2025 Apr 17;21(4):e1012936. doi: 10.1371/journal.pcbi.1012936. eCollection 2025 Apr.
5
Prediction of protein interactions with function in protein (de-)phosphorylation.蛋白质(去)磷酸化过程中具有功能的蛋白质相互作用预测。
PLoS One. 2025 Mar 3;20(3):e0319084. doi: 10.1371/journal.pone.0319084. eCollection 2025.
6
Deep learning identification of novel autophagic protein-protein interactions and experimental validation of Beclin 2-Ubiquilin 1 axis in triple-negative breast cancer.深度学习识别新型自噬蛋白-蛋白相互作用及三阴性乳腺癌中Beclin 2-泛素连接蛋白1轴的实验验证
Oncol Res. 2024 Dec 20;33(1):67-81. doi: 10.32604/or.2024.055921. eCollection 2025.
7
New insights into protein-protein interaction modulators in drug discovery and therapeutic advance.药物发现与治疗进展中蛋白质-蛋白质相互作用调节剂的新见解。
Signal Transduct Target Ther. 2024 Dec 6;9(1):341. doi: 10.1038/s41392-024-02036-3.
8
PPI-hotspot for detecting protein-protein interaction hot spots from the free protein structure.用于从游离蛋白质结构中检测蛋白质-蛋白质相互作用热点的PPI热点。
Elife. 2024 Sep 16;13:RP96643. doi: 10.7554/eLife.96643.
9
Blocker-SELEX: a structure-guided strategy for developing inhibitory aptamers disrupting undruggable transcription factor interactions.阻断剂-SELEX:一种用于开发破坏不可成药转录因子相互作用的抑制性适配体的结构导向策略。
Nat Commun. 2024 Aug 8;15(1):6751. doi: 10.1038/s41467-024-51197-w.
10
DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.DDMut-PPI:基于图的深度学习预测突变对蛋白质-蛋白质相互作用的影响。
Nucleic Acids Res. 2024 Jul 5;52(W1):W207-W214. doi: 10.1093/nar/gkae412.