• 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

迈向基于物理学的精准医学:利用蛋白质动力学设计新的治疗方法和解释变体。

Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants.

机构信息

Department of Biochemistry and Molecular Biophysics, Washington University in St. Louis, St. Louis, Missouri, USA.

Medical Scientist Training Program, Washington University in St. Louis, St. Louis, Missouri, USA.

出版信息

Protein Sci. 2024 Mar;33(3):e4902. doi: 10.1002/pro.4902.

DOI:10.1002/pro.4902
PMID:38358129
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10868452/
Abstract

The goal of precision medicine is to utilize our knowledge of the molecular causes of disease to better diagnose and treat patients. However, there is a substantial mismatch between the small number of food and drug administration (FDA)-approved drugs and annotated coding variants compared to the needs of precision medicine. This review introduces the concept of physics-based precision medicine, a scalable framework that promises to improve our understanding of sequence-function relationships and accelerate drug discovery. We show that accounting for the ensemble of structures a protein adopts in solution with computer simulations overcomes many of the limitations imposed by assuming a single protein structure. We highlight studies of protein dynamics and recent methods for the analysis of structural ensembles. These studies demonstrate that differences in conformational distributions predict functional differences within protein families and between variants. Thanks to new computational tools that are providing unprecedented access to protein structural ensembles, this insight may enable accurate predictions of variant pathogenicity for entire libraries of variants. We further show that explicitly accounting for protein ensembles, with methods like alchemical free energy calculations or docking to Markov state models, can uncover novel lead compounds. To conclude, we demonstrate that cryptic pockets, or cavities absent in experimental structures, provide an avenue to target proteins that are currently considered undruggable. Taken together, our review provides a roadmap for the field of protein science to accelerate precision medicine.

摘要

精准医学的目标是利用我们对疾病分子病因的了解,更好地诊断和治疗患者。然而,与精准医学的需求相比,食品和药物管理局(FDA)批准的药物和注释编码变体的数量存在着实质性的不匹配。这篇综述介绍了基于物理的精准医学的概念,这是一个可扩展的框架,有望提高我们对序列-功能关系的理解,并加速药物发现。我们表明,通过计算机模拟来解释蛋白质在溶液中采用的结构组合,可以克服许多假设单一蛋白质结构所带来的限制。我们强调了蛋白质动力学的研究和最近用于分析结构组合的方法。这些研究表明,构象分布的差异可以预测蛋白质家族内和变体之间的功能差异。由于新的计算工具为我们提供了前所未有的获取蛋白质结构组合的途径,这种洞察力可能使整个变体库的变体致病性的准确预测成为可能。我们进一步表明,通过明确考虑蛋白质组合,例如通过自由能计算或对接马尔可夫状态模型,可以发现新的先导化合物。总之,我们证明了隐藏口袋或实验结构中不存在的腔隙为靶向目前被认为不可成药的蛋白质提供了一种途径。总的来说,我们的综述为蛋白质科学领域提供了一条加速精准医学的路线图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/20a2c90041a0/PRO-33-e4902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/cfb1a2463fb1/PRO-33-e4902-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/7c9c13c1364d/PRO-33-e4902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/5da22d3563fe/PRO-33-e4902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/20a2c90041a0/PRO-33-e4902-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/cfb1a2463fb1/PRO-33-e4902-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/7c9c13c1364d/PRO-33-e4902-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/5da22d3563fe/PRO-33-e4902-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b56/10868452/20a2c90041a0/PRO-33-e4902-g001.jpg

相似文献

1
Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants.迈向基于物理学的精准医学:利用蛋白质动力学设计新的治疗方法和解释变体。
Protein Sci. 2024 Mar;33(3):e4902. doi: 10.1002/pro.4902.
2
Macromolecular crowding: chemistry and physics meet biology (Ascona, Switzerland, 10-14 June 2012).大分子拥挤现象:化学与物理邂逅生物学(瑞士阿斯科纳,2012年6月10日至14日)
Phys Biol. 2013 Aug;10(4):040301. doi: 10.1088/1478-3975/10/4/040301. Epub 2013 Aug 2.
3
Identifying novel drug targets with computational precision.以计算精度识别新型药物靶点。
Adv Pharmacol. 2025;103:231-263. doi: 10.1016/bs.apha.2025.01.003. Epub 2025 Feb 6.
4
Molecular Dynamics: New Frontier in Personalized Medicine.分子动力学:个性化医疗的新前沿。
Adv Protein Chem Struct Biol. 2016;102:181-224. doi: 10.1016/bs.apcsb.2015.09.004. Epub 2015 Nov 14.
5
EnGens: a computational framework for generation and analysis of representative protein conformational ensembles.EnGens:用于生成和分析代表性蛋白质构象集合的计算框架。
Brief Bioinform. 2023 Jul 20;24(4). doi: 10.1093/bib/bbad242.
6
Detecting Functional Dynamics in Proteins with Comparative Perturbed-Ensembles Analysis.利用比较扰动系综分析检测蛋白质中的功能动力学。
Acc Chem Res. 2019 Dec 17;52(12):3455-3464. doi: 10.1021/acs.accounts.9b00485. Epub 2019 Dec 3.
7
PopShift: A Thermodynamically Sound Approach to Estimate Binding Free Energies by Accounting for Ligand-Induced Population Shifts from a Ligand-Free Markov State Model.PopShift:一种热力学上合理的方法,通过从配体自由 Markov 态模型中考虑配体诱导的种群位移来估计结合自由能。
J Chem Theory Comput. 2024 Feb 13;20(3):1036-1050. doi: 10.1021/acs.jctc.3c00870. Epub 2024 Jan 31.
8
Assessing AF2's ability to predict structural ensembles of proteins.评估 AF2 预测蛋白质结构集合的能力。
Structure. 2024 Nov 7;32(11):2147-2159.e2. doi: 10.1016/j.str.2024.09.001. Epub 2024 Sep 26.
9
Cryptic binding sites on proteins: definition, detection, and druggability.蛋白质上的隐匿结合位点:定义、检测和可成药性。
Curr Opin Chem Biol. 2018 Jun;44:1-8. doi: 10.1016/j.cbpa.2018.05.003. Epub 2018 May 23.
10
How much can physics do for protein design?物理学能在多大程度上助力蛋白质设计?
Curr Opin Struct Biol. 2022 Feb;72:46-54. doi: 10.1016/j.sbi.2021.07.011. Epub 2021 Aug 27.

引用本文的文献

1
Opening and closing of a cryptic pocket in VP35 toggles it between two different RNA-binding modes.VP35中一个隐蔽口袋的打开和关闭使其在两种不同的RNA结合模式之间切换。
Elife. 2025 Sep 2;14:RP104514. doi: 10.7554/eLife.104514.
2
Pathogenic Mutations Disrupt Allosteric Control by .致病突变破坏了由……引起的变构调控。
J Phys Chem B. 2025 Aug 7;129(31):7922-7931. doi: 10.1021/acs.jpcb.5c03653. Epub 2025 Jul 29.
3
Pathogenic mutations disrupt allosteric control by .致病突变破坏了由……引起的变构调控。

本文引用的文献

1
PopShift: A Thermodynamically Sound Approach to Estimate Binding Free Energies by Accounting for Ligand-Induced Population Shifts from a Ligand-Free Markov State Model.PopShift:一种热力学上合理的方法,通过从配体自由 Markov 态模型中考虑配体诱导的种群位移来估计结合自由能。
J Chem Theory Comput. 2024 Feb 13;20(3):1036-1050. doi: 10.1021/acs.jctc.3c00870. Epub 2024 Jan 31.
2
Open science discovery of potent noncovalent SARS-CoV-2 main protease inhibitors.开发针对 SARS-CoV-2 主蛋白酶的高效非共价抑制剂的开放科学发现。
Science. 2023 Nov 10;382(6671):eabo7201. doi: 10.1126/science.abo7201.
3
Accurate proteome-wide missense variant effect prediction with AlphaMissense.
bioRxiv. 2025 Jun 10:2025.06.07.658438. doi: 10.1101/2025.06.07.658438.
4
Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery.G蛋白偶联受体的功能动力学揭示了药物发现的新途径。
Nat Rev Drug Discov. 2025 Apr;24(4):251-275. doi: 10.1038/s41573-024-01083-3. Epub 2025 Jan 2.
5
The G protein inhibitor YM-254890 is an allosteric glue.G蛋白抑制剂YM-254890是一种变构胶。
bioRxiv. 2024 Nov 28:2024.11.25.625299. doi: 10.1101/2024.11.25.625299.
6
Opening and closing of a cryptic pocket in VP35 toggles it between two different RNA-binding modes.VP35中一个隐蔽口袋的打开和关闭使其在两种不同的RNA结合模式之间切换。
bioRxiv. 2024 Oct 17:2024.08.22.609218. doi: 10.1101/2024.08.22.609218.
7
SGLT2 inhibitors activate pantothenate kinase in the human heart.钠-葡萄糖协同转运蛋白2抑制剂激活人类心脏中的泛酸激酶。
bioRxiv. 2024 Jul 27:2024.07.26.605401. doi: 10.1101/2024.07.26.605401.
使用 AlphaMissense 进行精确的全蛋白质错义变异效应预测。
Science. 2023 Sep 22;381(6664):eadg7492. doi: 10.1126/science.adg7492.
4
The landscape of tolerated genetic variation in humans and primates.人类和灵长类动物中可耐受遗传变异的景观。
Science. 2023 Jun 2;380(6648):eabn8153. doi: 10.1126/science.abn8197.
5
AlphaFold2-RAVE: From Sequence to Boltzmann Ranking.AlphaFold2-RAVE:从序列到玻尔兹曼排序
J Chem Theory Comput. 2023 Jul 25;19(14):4351-4354. doi: 10.1021/acs.jctc.3c00290. Epub 2023 May 12.
6
Discovery of a cryptic pocket in the AI-predicted structure of PPM1D phosphatase explains the binding site and potency of its allosteric inhibitors.在PPM1D磷酸酶的人工智能预测结构中发现一个隐秘口袋,这解释了其变构抑制剂的结合位点和效力。
Front Mol Biosci. 2023 Apr 18;10:1171143. doi: 10.3389/fmolb.2023.1171143. eCollection 2023.
7
Predicting the pathogenicity of missense variants using features derived from AlphaFold2.利用源自 AlphaFold2 的特征预测错义变异的致病性。
Bioinformatics. 2023 May 4;39(5). doi: 10.1093/bioinformatics/btad280.
8
Mutagenesis and structural analysis reveal the CTX-M β-lactamase active site is optimized for cephalosporin catalysis and drug resistance.突变和结构分析揭示 CTX-M 型β-内酰胺酶的活性位点经过优化,有利于头孢菌素的催化和耐药性。
J Biol Chem. 2023 May;299(5):104630. doi: 10.1016/j.jbc.2023.104630. Epub 2023 Mar 22.
9
Accelerating Cryptic Pocket Discovery Using AlphaFold.利用 AlphaFold 加速隐秘口袋的发现。
J Chem Theory Comput. 2023 Jul 25;19(14):4355-4363. doi: 10.1021/acs.jctc.2c01189. Epub 2023 Mar 22.
10
Folding@home: Achievements from over 20 years of citizen science herald the exascale era.Folding@home:超过 20 年的公民科学成就预示着 exascale 时代的到来。
Biophys J. 2023 Jul 25;122(14):2852-2863. doi: 10.1016/j.bpj.2023.03.028. Epub 2023 Mar 21.