• 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

基于粗粒度模型的蛋白质原子结构的计算重建

Computational reconstruction of atomistic protein structures from coarse-grained models.

作者信息

Badaczewska-Dawid Aleksandra E, Kolinski Andrzej, Kmiecik Sebastian

机构信息

Faculty of Chemistry, Biological and Chemical Research Center, University of Warsaw, Pasteura 1, 02-093 Warsaw, Poland.

出版信息

Comput Struct Biotechnol J. 2019 Dec 26;18:162-176. doi: 10.1016/j.csbj.2019.12.007. eCollection 2020.

DOI:10.1016/j.csbj.2019.12.007
PMID:31969975
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6961067/
Abstract

Three-dimensional protein structures, whether determined experimentally or theoretically, are often too low resolution. In this mini-review, we outline the computational methods for protein structure reconstruction from incomplete coarse-grained to all atomistic models. Typical reconstruction schemes can be divided into four major steps. Usually, the first step is reconstruction of the protein backbone chain starting from the C-alpha trace. This is followed by side-chains rebuilding based on protein backbone geometry. Subsequently, hydrogen atoms can be reconstructed. Finally, the resulting all-atom models may require structure optimization. Many methods are available to perform each of these tasks. We discuss the available tools and their potential applications in integrative modeling pipelines that can transfer coarse-grained information from computational predictions, or experiment, to all atomistic structures.

摘要

三维蛋白质结构,无论是通过实验还是理论确定的,其分辨率往往都很低。在这篇小型综述中,我们概述了从不完全的粗粒度模型到全原子模型进行蛋白质结构重建的计算方法。典型的重建方案可分为四个主要步骤。通常,第一步是从Cα迹线开始重建蛋白质主链。接下来是基于蛋白质主链几何结构重建侧链。随后,可以重建氢原子。最后,得到的全原子模型可能需要进行结构优化。有许多方法可用于执行这些任务中的每一项。我们讨论了可用的工具及其在整合建模流程中的潜在应用,这些流程可以将粗粒度信息从计算预测或实验转移到全原子结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb44/6961067/58165c01a0c7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb44/6961067/252f71b59f70/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb44/6961067/58165c01a0c7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb44/6961067/252f71b59f70/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cb44/6961067/58165c01a0c7/gr2.jpg

相似文献

1
Computational reconstruction of atomistic protein structures from coarse-grained models.基于粗粒度模型的蛋白质原子结构的计算重建
Comput Struct Biotechnol J. 2019 Dec 26;18:162-176. doi: 10.1016/j.csbj.2019.12.007. eCollection 2020.
2
Template-Guided Protein Structure Prediction and Refinement Using Optimized Folding Landscape Force Fields.基于优化折叠景观力场的模板引导蛋白结构预测和精修。
J Chem Theory Comput. 2018 Nov 13;14(11):6102-6116. doi: 10.1021/acs.jctc.8b00683. Epub 2018 Oct 8.
3
Design of a rotamer library for coarse-grained models in protein-folding simulations.设计用于蛋白质折叠模拟的粗粒度模型的构象文库。
J Chem Inf Model. 2014 Jan 27;54(1):302-13. doi: 10.1021/ci4005833. Epub 2013 Dec 31.
4
Direct Mixing of Atomistic Solutes and Coarse-Grained Water.原子溶质与粗粒化水的直接混合。
J Chem Theory Comput. 2014 Oct 14;10(10):4684-93. doi: 10.1021/ct500065k. Epub 2014 Sep 10.
5
DiAMoNDBack: Diffusion-Denoising Autoregressive Model for Non-Deterministic Backmapping of Cα Protein Traces.DiAMoNDBack:用于 Cα 蛋白质轨迹非确定性反向映射的扩散去噪自回归模型。
J Chem Theory Comput. 2023 Nov 14;19(21):7908-7923. doi: 10.1021/acs.jctc.3c00840. Epub 2023 Oct 31.
6
MARTINI-Based Protein-DNA Coarse-Grained HADDOCKing.基于MARTINI的蛋白质-脱氧核糖核酸粗粒度对接
Front Mol Biosci. 2019 Oct 1;6:102. doi: 10.3389/fmolb.2019.00102. eCollection 2019.
7
A systematic procedure to build a relaxed dense-phase atomistic representation of a complex amorphous polymer using a coarse-grained modeling approach.一种使用粗粒度建模方法构建复杂无定形聚合物的松弛密相原子表示的系统程序。
Polymer (Guildf). 2009 Jul 31;50(16):4139-4149. doi: 10.1016/j.polymer.2009.06.055.
8
ESCASA: Analytical estimation of atomic coordinates from coarse-grained geometry for nuclear-magnetic-resonance-assisted protein structure modeling. I. Backbone and H protons.ESCASA:基于粗粒化结构的核磁共振辅助蛋白结构建模中原子坐标的解析估计。I. 主链和 H 质子。
J Comput Chem. 2021 Aug 15;42(22):1579-1589. doi: 10.1002/jcc.26695. Epub 2021 May 28.
9
Coarse-Graining of TIP4P/2005, TIP4P-Ew, SPC/E, and TIP3P to Monatomic Anisotropic Water Models Using Relative Entropy Minimization.使用相对熵最小化方法将TIP4P/2005、TIP4P-Ew、SPC/E和TIP3P粗粒化为单原子各向异性水模型。
J Chem Theory Comput. 2014 Sep 9;10(9):4104-20. doi: 10.1021/ct500487h. Epub 2014 Aug 1.
10
Going Backward: A Flexible Geometric Approach to Reverse Transformation from Coarse Grained to Atomistic Models.向后追溯:一种从粗粒度模型到原子模型反向转换的灵活几何方法。
J Chem Theory Comput. 2014 Feb 11;10(2):676-90. doi: 10.1021/ct400617g. Epub 2014 Jan 21.

引用本文的文献

1
Integrating AlphaFold pLDDT Scores into CABS-flex for enhanced protein flexibility simulations.将AlphaFold pLDDT分数整合到CABS-flex中以增强蛋白质柔性模拟。
Comput Struct Biotechnol J. 2024 Nov 30;23:4350-4356. doi: 10.1016/j.csbj.2024.11.047. eCollection 2024 Dec.
2
Sifting through the noise: A survey of diffusion probabilistic models and their applications to biomolecules.筛选噪音:扩散概率模型及其在生物分子中的应用综述
J Mol Biol. 2025 Mar 15;437(6):168818. doi: 10.1016/j.jmb.2024.168818. Epub 2024 Oct 9.
3
Exploring protein functions from structural flexibility using CABS-flex modeling.

本文引用的文献

1
Protocols for All-Atom Reconstruction and High-Resolution Refinement of Protein-Peptide Complex Structures.全原子重建和蛋白质-肽复合物结构高分辨率精修的方案。
Methods Mol Biol. 2020;2165:273-287. doi: 10.1007/978-1-0716-0708-4_16.
2
Advances in protein structure prediction and design.蛋白质结构预测和设计的进展。
Nat Rev Mol Cell Biol. 2019 Nov;20(11):681-697. doi: 10.1038/s41580-019-0163-x. Epub 2019 Aug 15.
3
OPUS-Rota2: An Improved Fast and Accurate Side-Chain Modeling Method.OPUS-Rota2:一种改进的快速准确的侧链建模方法。
利用 CABS-flex 建模探索蛋白质结构柔性的功能。
Protein Sci. 2024 Sep;33(9):e5090. doi: 10.1002/pro.5090.
4
ABC2A: A Straightforward and Fast Method for the Accurate Backmapping of RNA Coarse-Grained Models to All-Atom Structures.ABC2A:一种将 RNA 粗粒模型准确映射回全原子结构的简单快速方法。
Molecules. 2024 Mar 11;29(6):1244. doi: 10.3390/molecules29061244.
5
Physics-Informed Deep Learning Approach for Reintroducing Atomic Detail in Coarse-Grained Configurations of Multiple Poly(lactic acid) Stereoisomers.基于物理信息的深度学习方法在多种聚乳酸立体异构体的粗粒构象中重新引入原子细节。
J Chem Inf Model. 2024 Mar 25;64(6):1853-1867. doi: 10.1021/acs.jcim.3c01870. Epub 2024 Mar 1.
6
Structure prediction of linear and cyclic peptides using CABS-flex.使用 CABS-flex 进行线性和环状肽的结构预测。
Brief Bioinform. 2024 Jan 22;25(2). doi: 10.1093/bib/bbae003.
7
An end-to-end deep learning method for protein side-chain packing and inverse folding.一种端到端的深度学习方法,用于蛋白质侧链堆积和逆折叠。
Proc Natl Acad Sci U S A. 2023 Jun 6;120(23):e2216438120. doi: 10.1073/pnas.2216438120. Epub 2023 May 30.
8
Multiscale modelling of claudin-based assemblies: A magnifying glass for novel structures of biological interfaces.基于紧密连接蛋白的组装体的多尺度建模:生物界面新结构的放大镜
Comput Struct Biotechnol J. 2022 Oct 28;20:5984-6010. doi: 10.1016/j.csbj.2022.10.038. eCollection 2022.
9
Bottom-up Coarse-Graining: Principles and Perspectives.自底向上粗粒化:原理与展望。
J Chem Theory Comput. 2022 Oct 11;18(10):5759-5791. doi: 10.1021/acs.jctc.2c00643. Epub 2022 Sep 7.
10
Implementation of residue-level coarse-grained models in GENESIS for large-scale molecular dynamics simulations.在GENESIS中实现用于大规模分子动力学模拟的残基级粗粒度模型。
PLoS Comput Biol. 2022 Apr 5;18(4):e1009578. doi: 10.1371/journal.pcbi.1009578. eCollection 2022 Apr.
J Chem Theory Comput. 2019 Sep 10;15(9):5154-5160. doi: 10.1021/acs.jctc.9b00309. Epub 2019 Aug 26.
4
Determining protein structures using deep mutagenesis.利用深度突变技术确定蛋白质结构。
Nat Genet. 2019 Jul;51(7):1177-1186. doi: 10.1038/s41588-019-0431-x. Epub 2019 Jun 17.
5
Inferring protein 3D structure from deep mutation scans.从深度突变扫描中推断蛋白质 3D 结构。
Nat Genet. 2019 Jul;51(7):1170-1176. doi: 10.1038/s41588-019-0432-9. Epub 2019 Jun 17.
6
Forging tools for refining predicted protein structures.锻造工具以精炼预测蛋白质结构。
Proc Natl Acad Sci U S A. 2019 May 7;116(19):9400-9409. doi: 10.1073/pnas.1900778116. Epub 2019 Apr 18.
7
Refinement of protein structures using a combination of quantum-mechanical calculations with neutron and X-ray crystallographic data.利用量子力学计算与中子和 X 射线晶体学数据相结合来改进蛋白质结构。
Acta Crystallogr D Struct Biol. 2019 Apr 1;75(Pt 4):368-380. doi: 10.1107/S205979831900175X. Epub 2019 Mar 28.
8
CABS-dock standalone: a toolbox for flexible protein-peptide docking.CABS-dock 独立版:用于灵活蛋白质-肽对接的工具箱。
Bioinformatics. 2019 Oct 15;35(20):4170-4172. doi: 10.1093/bioinformatics/btz185.
9
refineD: improved protein structure refinement using machine learning based restrained relaxation.refineD:基于机器学习的约束松弛改进蛋白质结构精修。
Bioinformatics. 2019 Sep 15;35(18):3320-3328. doi: 10.1093/bioinformatics/btz101.
10
Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields.使用蒙特卡罗模拟和基于知识的统计力场对无序蛋白质结构进行建模。
Int J Mol Sci. 2019 Jan 31;20(3):606. doi: 10.3390/ijms20030606.