• 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

源自单一蛋白质结构内堆积几何形状的熵。

Entropies Derived from the Packing Geometries within a Single Protein Structure.

作者信息

Khade Pranav M, Jernigan Robert L

机构信息

Bioinformatics and Computational Biology Program and Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, Iowa 50011, United States.

出版信息

ACS Omega. 2022 Jun 9;7(24):20719-20730. doi: 10.1021/acsomega.2c00999. eCollection 2022 Jun 21.

DOI:10.1021/acsomega.2c00999
PMID:35755337
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9219053/
Abstract

A fast, simple, yet robust method to calculate protein entropy from a single protein structure is presented here. The focus is on the atomic packing details, which are calculated by combining Voronoi diagrams and Delaunay tessellations. Even though the method is simple, the entropies computed exhibit an extremely high correlation with the entropies previously derived by other methods based on quasi-harmonic motions, quantum mechanics, and molecular dynamics simulations. These packing-based entropies account directly for the local freedom and provide entropy for any individual protein structure that could be used to compute free energies directly during simulations for the generation of more reliable trajectories and also for better evaluations of modeled protein structures. Physico-chemical properties of amino acids are compared with these packing entropies to uncover the relationships with the entropies of different residue types. A public packing entropy web server is provided at packing-entropy.bb.iastate.edu, and the application programing interface is available within the PACKMAN (https://github.com/Pranavkhade/PACKMAN) package.

摘要

本文介绍了一种从单个蛋白质结构计算蛋白质熵的快速、简单且稳健的方法。重点在于原子堆积细节,通过结合Voronoi图和Delaunay三角剖分来计算。尽管该方法简单,但计算出的熵与先前通过基于准谐运动、量子力学和分子动力学模拟的其他方法得出的熵具有极高的相关性。这些基于堆积的熵直接考虑了局部自由度,并为任何单个蛋白质结构提供熵,可用于在模拟过程中直接计算自由能,以生成更可靠的轨迹,还可用于更好地评估建模的蛋白质结构。将氨基酸的物理化学性质与这些堆积熵进行比较,以揭示与不同残基类型熵的关系。在packing - entropy.bb.iastate.edu提供了一个公共的堆积熵网络服务器,并且在PACKMAN(https://github.com/Pranavkhade/PACKMAN)软件包中提供了应用程序编程接口。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/280c61ae1be7/ao2c00999_0013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/1c15830784fa/ao2c00999_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/de66ef7902cb/ao2c00999_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/6d81f463bba2/ao2c00999_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/9cacc082277e/ao2c00999_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/07e97415dbde/ao2c00999_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/dbfb79f0140b/ao2c00999_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/c2f0add84538/ao2c00999_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/98e2a78ff72a/ao2c00999_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/5197930f1ec2/ao2c00999_0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/b6b9aac6ab50/ao2c00999_0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/364927c9cc98/ao2c00999_0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/280c61ae1be7/ao2c00999_0013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/1c15830784fa/ao2c00999_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/de66ef7902cb/ao2c00999_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/6d81f463bba2/ao2c00999_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/9cacc082277e/ao2c00999_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/07e97415dbde/ao2c00999_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/dbfb79f0140b/ao2c00999_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/c2f0add84538/ao2c00999_0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/98e2a78ff72a/ao2c00999_0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/5197930f1ec2/ao2c00999_0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/b6b9aac6ab50/ao2c00999_0011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/364927c9cc98/ao2c00999_0012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68a3/9219053/280c61ae1be7/ao2c00999_0013.jpg

相似文献

1
Entropies Derived from the Packing Geometries within a Single Protein Structure.源自单一蛋白质结构内堆积几何形状的熵。
ACS Omega. 2022 Jun 9;7(24):20719-20730. doi: 10.1021/acsomega.2c00999. eCollection 2022 Jun 21.
2
Configurational entropies of lipids in pure and mixed bilayers from atomic-level and coarse-grained molecular dynamics simulations.通过原子水平和粗粒度分子动力学模拟得到的纯脂双层和混合脂双层中脂质的构象熵
J Phys Chem B. 2006 Aug 10;110(31):15602-14. doi: 10.1021/jp061627s.
3
Multibasin Quasi-Harmonic Approach for the Calculation of the Configurational Entropy of Small Molecules in Solution.多盆地准谐方法计算溶液中小分子的构象熵。
J Chem Theory Comput. 2021 Feb 9;17(2):1133-1142. doi: 10.1021/acs.jctc.0c00978. Epub 2021 Jan 7.
4
Knowledge-based entropies improve the identification of native protein structures.基于知识的熵改进了天然蛋白质结构的识别。
Proc Natl Acad Sci U S A. 2017 Mar 14;114(11):2928-2933. doi: 10.1073/pnas.1613331114. Epub 2017 Mar 6.
5
Develop and test a solvent accessible surface area-based model in conformational entropy calculations.开发并测试一种基于溶剂可及表面积的构象熵计算模型。
J Chem Inf Model. 2012 May 25;52(5):1199-212. doi: 10.1021/ci300064d. Epub 2012 Apr 24.
6
Free energies for coarse-grained proteins by integrating multibody statistical contact potentials with entropies from elastic network models.通过将多体统计接触势与弹性网络模型的熵相结合来计算粗粒度蛋白质的自由能。
J Struct Funct Genomics. 2011 Jul;12(2):137-47. doi: 10.1007/s10969-011-9113-3. Epub 2011 Jun 15.
7
Protein sequence entropy is closely related to packing density and hydrophobicity.蛋白质序列熵与堆积密度和疏水性密切相关。
Protein Eng Des Sel. 2005 Feb;18(2):59-64. doi: 10.1093/protein/gzi009. Epub 2005 Mar 23.
8
Characterizing and Predicting Protein Hinges for Mechanistic Insight.蛋白质铰链的特征化和预测:深入了解其机制。
J Mol Biol. 2020 Jan 17;432(2):508-522. doi: 10.1016/j.jmb.2019.11.018. Epub 2019 Nov 29.
9
Absolute hydration entropies of alkali metal ions from molecular dynamics simulations.通过分子动力学模拟得到的碱金属离子的绝对水合熵
J Phys Chem B. 2009 Jul 30;113(30):10255-60. doi: 10.1021/jp900818z.
10
Toward Reliable and Insightful Entropy Calculations on Flexible Molecules.实现柔性分子可靠且有见地的熵计算。
J Chem Theory Comput. 2022 Dec 13;18(12):7166-7178. doi: 10.1021/acs.jctc.2c00858. Epub 2022 Nov 25.

引用本文的文献

1
Computational design of α-amylase from to increase its activity and stability at high temperatures.α-淀粉酶的计算设计以提高其在高温下的活性和稳定性。
Comput Struct Biotechnol J. 2024 Feb 13;23:982-989. doi: 10.1016/j.csbj.2024.02.005. eCollection 2024 Dec.
2
Glycosylation and Crowded Membrane Effects on Influenza Neuraminidase Stability and Dynamics.糖基化和拥挤的细胞膜对流感神经氨酸酶稳定性和动力学的影响。
J Phys Chem Lett. 2023 Nov 9;14(44):9926-9934. doi: 10.1021/acs.jpclett.3c02524. Epub 2023 Oct 30.

本文引用的文献

1
Enhancing computational enzyme design by a maximum entropy strategy.通过最大熵策略增强计算酶设计。
Proc Natl Acad Sci U S A. 2022 Feb 15;119(7). doi: 10.1073/pnas.2122355119.
2
Entropy of Proteins Using Multiscale Cell Correlation.利用多尺度细胞相关性计算蛋白质的熵。
J Chem Inf Model. 2020 Nov 23;60(11):5540-5551. doi: 10.1021/acs.jcim.0c00611. Epub 2020 Sep 29.
3
Structural compliance: A new metric for protein flexibility.结构顺应性:蛋白质柔性的新指标。
Proteins. 2020 Nov;88(11):1482-1492. doi: 10.1002/prot.25968. Epub 2020 Jul 14.
4
Characterizing and Predicting Protein Hinges for Mechanistic Insight.蛋白质铰链的特征化和预测:深入了解其机制。
J Mol Biol. 2020 Jan 17;432(2):508-522. doi: 10.1016/j.jmb.2019.11.018. Epub 2019 Nov 29.
5
Are crystallographic B-factors suitable for calculating protein conformational entropy?晶体学 B 因子是否适合计算蛋白质构象熵?
Phys Chem Chem Phys. 2019 Aug 21;21(33):18149-18160. doi: 10.1039/c9cp02504a.
6
Self-Consistent Framework Connecting Experimental Proxies of Protein Dynamics with Configurational Entropy.自洽框架将蛋白质动力学的实验代理与构象熵联系起来。
J Chem Theory Comput. 2018 Jul 10;14(7):3796-3810. doi: 10.1021/acs.jctc.8b00100. Epub 2018 Jun 8.
7
Prediction of Protein Configurational Entropy (Popcoen).蛋白质构象熵的预测(Popcoen)
J Chem Theory Comput. 2018 Mar 13;14(3):1811-1819. doi: 10.1021/acs.jctc.7b01079. Epub 2018 Feb 16.
8
Measuring Entropy in Molecular Recognition by Proteins.蛋白质分子识别中的熵测量。
Annu Rev Biophys. 2018 May 20;47:41-61. doi: 10.1146/annurev-biophys-060414-034042. Epub 2018 Jan 18.
9
Testing the mutual information expansion of entropy with multivariate Gaussian distributions.测试多元高斯分布下的熵的互信息扩展。
J Chem Phys. 2017 Dec 14;147(22):224102. doi: 10.1063/1.4996847.
10
Analysis of Large-Scale Mutagenesis Data To Assess the Impact of Single Amino Acid Substitutions.分析大规模诱变数据以评估单个氨基酸取代的影响。
Genetics. 2017 Sep;207(1):53-61. doi: 10.1534/genetics.117.300064. Epub 2017 Jul 27.