• 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

调节剂如何影响变构结合口袋和正构结合口袋?

How Do Modulators Affect the Orthosteric and Allosteric Binding Pockets?

机构信息

Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.

National Center of Excellence for Computational Drug Abuse Research, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.

出版信息

ACS Chem Neurosci. 2022 Apr 6;13(7):959-977. doi: 10.1021/acschemneuro.1c00749. Epub 2022 Mar 17.

DOI:10.1021/acschemneuro.1c00749
PMID:35298129
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10496248/
Abstract

Allosteric modulators (AMs) that bind allosteric sites can exhibit greater selectivity than the orthosteric ligands and can either enhance agonist-induced receptor activity (termed positive allosteric modulator or PAM), inhibit agonist-induced activity (negative AM or NAM), or have no effect on activity (silent AM or SAM). Until now, it is not clear what the exact effects of AMs are on the orthosteric active site or the allosteric binding pocket(s). In the present work, we collected both the three-dimensional (3D) structures of receptor-orthosteric ligand and receptor-orthosteric ligand-AM complexes of a specific target protein. Using our novel algorithm toolset, molecular complex characterizing system (MCCS), we were able to quantify the key residues in both the orthosteric and allosteric binding sites along with potential changes of the binding pockets. After analyzing 21 pairs of 3D crystal or cryo-electron microscopy (cryo-EM) complexes, including 4 pairs of GPCRs, 5 pairs of ion channels, 11 pairs of enzymes, and 1 pair of transcription factors, we found that the binding of AMs had little impact on both the orthosteric and allosteric binding pockets. In return, given the accurately predicted allosteric binding pocket(s) of a drug target of medicinal interest, we can confidently conduct the virtual screening or lead optimization without concern that the huge conformational change of the pocket could lead to the low accuracy of virtual screening.

摘要

变构调节剂(AMs)与变构位点结合,可以比正位配体具有更高的选择性,并且可以增强激动剂诱导的受体活性(称为正变构调节剂或 PAM),抑制激动剂诱导的活性(负变构调节剂或 NAM),或对活性没有影响(沉默变构调节剂或 SAM)。到目前为止,还不清楚 AMs 对正位活性位点或变构结合口袋的确切影响。在本工作中,我们收集了特定靶蛋白的受体-正位配体和受体-正位配体-AM 复合物的三维(3D)结构。使用我们的新型算法工具集,分子复合物特征系统(MCCS),我们能够量化正位和变构结合位点的关键残基以及结合口袋的潜在变化。在分析了 21 对 3D 晶体或冷冻电镜(cryo-EM)复合物后,包括 4 对 GPCRs、5 对离子通道、11 对酶和 1 对转录因子,我们发现 AM 的结合对正位和变构结合口袋几乎没有影响。反过来,考虑到有医学意义的药物靶标变构结合口袋的准确预测,我们可以放心地进行虚拟筛选或先导优化,而不必担心口袋的巨大构象变化会导致虚拟筛选的准确性降低。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/9cf84b9f69b9/nihms-1904832-f0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/e9a6d84343bb/nihms-1904832-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/8b8c1f1d7b5b/nihms-1904832-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/1c2d17f2e1f1/nihms-1904832-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/b460cfbd0a42/nihms-1904832-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/f282f1fba2b7/nihms-1904832-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/d9c4423ddf33/nihms-1904832-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/6de9e27c3a8d/nihms-1904832-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/64e3d52b97aa/nihms-1904832-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/00d7dc8f119a/nihms-1904832-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/8cf32f4cb6b5/nihms-1904832-f0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/9cf84b9f69b9/nihms-1904832-f0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/e9a6d84343bb/nihms-1904832-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/8b8c1f1d7b5b/nihms-1904832-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/1c2d17f2e1f1/nihms-1904832-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/b460cfbd0a42/nihms-1904832-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/f282f1fba2b7/nihms-1904832-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/d9c4423ddf33/nihms-1904832-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/6de9e27c3a8d/nihms-1904832-f0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/64e3d52b97aa/nihms-1904832-f0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/00d7dc8f119a/nihms-1904832-f0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/8cf32f4cb6b5/nihms-1904832-f0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61a8/10496248/9cf84b9f69b9/nihms-1904832-f0012.jpg

相似文献

1
How Do Modulators Affect the Orthosteric and Allosteric Binding Pockets?调节剂如何影响变构结合口袋和正构结合口袋?
ACS Chem Neurosci. 2022 Apr 6;13(7):959-977. doi: 10.1021/acschemneuro.1c00749. Epub 2022 Mar 17.
2
Molecular Modeling Study of a Receptor-Orthosteric Ligand-Allosteric Modulator Signaling Complex.受体-变构配体-变构调节剂信号复合物的分子建模研究。
ACS Chem Neurosci. 2023 Feb 1;14(3):418-434. doi: 10.1021/acschemneuro.2c00554. Epub 2023 Jan 24.
3
Negative allosteric modulators of cannabinoid receptor 2: protein modeling, binding site identification and molecular dynamics simulations in the presence of an orthosteric agonist.大麻素受体 2 的负变构调节剂:正构激动剂存在下的蛋白建模、结合位点鉴定和分子动力学模拟。
J Biomol Struct Dyn. 2020 Jan;38(1):32-47. doi: 10.1080/07391102.2019.1567384. Epub 2019 Feb 5.
4
In Silico Prediction and Validation of CB2 Allosteric Binding Sites to Aid the Design of Allosteric Modulators.计算机辅助预测和验证 CB2 变构结合位点,以辅助变构调节剂的设计。
Molecules. 2022 Jan 11;27(2):453. doi: 10.3390/molecules27020453.
5
Binding Characterization of GPCRs-Modulator by Molecular Complex Characterizing System (MCCS).用分子复合物特征系统(MCCS)对 GPCRs-调节剂的结合特性进行分析。
ACS Chem Neurosci. 2020 Oct 21;11(20):3333-3345. doi: 10.1021/acschemneuro.0c00457. Epub 2020 Oct 7.
6
Development of allosteric modulators of GPCRs for treatment of CNS disorders.开发变构调节剂以治疗中枢神经系统疾病。
Neurobiol Dis. 2014 Jan;61:55-71. doi: 10.1016/j.nbd.2013.09.013. Epub 2013 Sep 27.
7
Impact of allosteric modulation: Exploring the binding kinetics of glutamate and other orthosteric ligands of the metabotropic glutamate receptor 2.变构调节的影响:探索代谢型谷氨酸受体 2 的谷氨酸和其他变构配体的结合动力学。
Biochem Pharmacol. 2018 Sep;155:356-365. doi: 10.1016/j.bcp.2018.07.014. Epub 2018 Jul 17.
8
Allosteric activation of metabotropic glutamate receptor 5.变构激活代谢型谷氨酸受体 5。
J Biomol Struct Dyn. 2020 Jun;38(9):2624-2632. doi: 10.1080/07391102.2019.1638302. Epub 2019 Jul 17.
9
Harnessing the druggability at orthosteric and allosteric sites of PD-1 for small molecule discovery by an integrated in silico pipeline.通过集成的计算管道,利用 PD-1 的正构和变构结合部位的成药性进行小分子药物的发现。
Comput Biol Chem. 2023 Dec;107:107965. doi: 10.1016/j.compbiolchem.2023.107965. Epub 2023 Sep 27.
10
Probing the metabotropic glutamate receptor 5 (mGlu₅) positive allosteric modulator (PAM) binding pocket: discovery of point mutations that engender a "molecular switch" in PAM pharmacology.探究代谢型谷氨酸受体 5(mGlu₅)正变构调节剂(PAM)结合口袋:发现导致 PAM 药理学中“分子开关”的点突变。
Mol Pharmacol. 2013 May;83(5):991-1006. doi: 10.1124/mol.112.083949. Epub 2013 Feb 26.

引用本文的文献

1
To activate a G protein-coupled receptor permanently with cell surface photodynamic action in the gastrointestinal tract.通过胃肠道中的细胞表面光动力作用永久激活G蛋白偶联受体。
World J Gastroenterol. 2025 Mar 28;31(12):102423. doi: 10.3748/wjg.v31.i12.102423.
2
Metabotropic Glutamate Receptor 5: A Potential Target for Neuropathic Pain Treatment.代谢型谷氨酸受体5:神经性疼痛治疗的潜在靶点。
Curr Neuropharmacol. 2025;23(3):276-294. doi: 10.2174/1570159X23666241011163035.
3
The NERP-4-SNAT2 axis regulates pancreatic β-cell maintenance and function.

本文引用的文献

1
Presynaptic AMPA Receptors in Health and Disease.突触前 AMPA 受体在健康和疾病中的作用。
Cells. 2021 Aug 31;10(9):2260. doi: 10.3390/cells10092260.
2
Integrated Multi-Class Classification and Prediction of GPCR Allosteric Modulators by Machine Learning Intelligence.基于机器学习智能的 G 蛋白偶联受体变构调节剂的综合多类分类和预测。
Biomolecules. 2021 Jun 11;11(6):870. doi: 10.3390/biom11060870.
3
Binding Characterization of Agonists and Antagonists by MCCS: A Case Study from Adenosine A Receptor.通过 MCCS 对激动剂和拮抗剂的结合特性进行表征:以腺苷 A 受体为例。
NERP-4-SNAT2 轴调节胰腺β细胞的维持和功能。
Nat Commun. 2023 Dec 9;14(1):8158. doi: 10.1038/s41467-023-43976-8.
4
Molecular Modeling Study of a Receptor-Orthosteric Ligand-Allosteric Modulator Signaling Complex.受体-变构配体-变构调节剂信号复合物的分子建模研究。
ACS Chem Neurosci. 2023 Feb 1;14(3):418-434. doi: 10.1021/acschemneuro.2c00554. Epub 2023 Jan 24.
ACS Chem Neurosci. 2021 May 5;12(9):1606-1620. doi: 10.1021/acschemneuro.1c00082. Epub 2021 Apr 15.
4
The effects of the general anesthetic sevoflurane on neurotransmission: an experimental and computational study.全身麻醉药七氟醚对神经递质传递的影响:一项实验和计算研究。
Sci Rep. 2021 Feb 22;11(1):4335. doi: 10.1038/s41598-021-83714-y.
5
The Z-Drugs Zolpidem, Zaleplon, and Eszopiclone Have Varying Actions on Human GABA Receptors Containing γ1, γ2, and γ3 Subunits.唑吡坦、扎来普隆和艾司佐匹克隆这几种Z类药物对含有γ1、γ2和γ3亚基的人γ-氨基丁酸(GABA)受体有不同作用。
Front Neurosci. 2020 Nov 19;14:599812. doi: 10.3389/fnins.2020.599812. eCollection 2020.
6
Rapid, accurate, precise and reproducible ligand-protein binding free energy prediction.快速、准确、精确且可重复的配体-蛋白质结合自由能预测。
Interface Focus. 2020 Dec 6;10(6):20200007. doi: 10.1098/rsfs.2020.0007. Epub 2020 Oct 16.
7
MCCS: a novel recognition pattern-based method for fast track discovery of anti-SARS-CoV-2 drugs.MCCS:一种基于新型识别模式的快速发现抗 SARS-CoV-2 药物的方法。
Brief Bioinform. 2021 Mar 22;22(2):946-962. doi: 10.1093/bib/bbaa260.
8
MCCS, a novel characterization method for protein-ligand complex.MCCS,一种用于蛋白质-配体复合物的新型表征方法。
Brief Bioinform. 2021 Jul 20;22(4). doi: 10.1093/bib/bbaa239.
9
Binding Characterization of GPCRs-Modulator by Molecular Complex Characterizing System (MCCS).用分子复合物特征系统(MCCS)对 GPCRs-调节剂的结合特性进行分析。
ACS Chem Neurosci. 2020 Oct 21;11(20):3333-3345. doi: 10.1021/acschemneuro.0c00457. Epub 2020 Oct 7.
10
On Calculating Free Energy Differences Using Ensembles of Transition Paths.关于使用过渡路径系综计算自由能差
Front Mol Biosci. 2020 Jun 5;7:106. doi: 10.3389/fmolb.2020.00106. eCollection 2020.