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评估四种理论方法预测晶体相和溶液中蛋白质柔性。

Assessment of Four Theoretical Approaches to Predict Protein Flexibility in the Crystal Phase and Solution.

机构信息

Faculty of Chemistry, University of Gdansk, ul. Wita-Stwosza 63, 80-308 Gdańsk, Poland.

School of Computational Sciences, Korea Institute for Advanced Study, 85 Hoegiro, Dongdaemun-gu, Seoul 02455, Republic of Korea.

出版信息

J Chem Theory Comput. 2024 Sep 10;20(17):7667-7681. doi: 10.1021/acs.jctc.4c00754. Epub 2024 Aug 22.

DOI:10.1021/acs.jctc.4c00754
PMID:39171852
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11391579/
Abstract

In this paper, we evaluated the ability of four coarse-grained methods to predict protein flexible regions with potential biological importance, UNRES-flex, UNRES-DSSP-flex (based on the united residue model of polypeptide chains without and with secondary structure restraints, respectively), CABS-flex (based on the C-α, C-β, and side chain model), and nonlinear rigid block normal mode analysis (NOLB) with a set of 100 protein structures determined by NMR spectroscopy or X-ray crystallography, with all secondary structure types. End regions with high fluctuations were excluded from analysis. The Pearson and Spearman correlation coefficients were used to quantify the conformity between the calculated and experimental fluctuation profiles, the latter determined from NMR ensembles and X-ray -factors, respectively. For X-ray structures (corresponding to proteins in a crowded environment), NOLB resulted in the best agreement between the predicted and experimental fluctuation profiles, while for NMR structures (corresponding to proteins in solution), the ranking of performance is CABS-flex > UNRES-DSSP-flex > UNRES-flex > NOLB; however, CABS-flex sometimes exaggerated the extent of small fluctuations, as opposed to UNRES-DSSP-flex.

摘要

在本文中,我们评估了四种粗粒化方法预测具有潜在生物学重要性的蛋白质柔性区域的能力,包括 UNRES-flex、UNRES-DSSP-flex(分别基于无二级结构约束和有二级结构约束的联合残基模型)、CABS-flex(基于 C-α、C-β 和侧链模型)以及非线性刚性块正则模态分析(NOLB)。我们使用了一组由 NMR 光谱或 X 射线晶体学确定的 100 种具有所有二级结构类型的蛋白质结构,排除了具有高波动的末端区域进行分析。Pearson 和 Spearman 相关系数用于量化计算和实验波动分布之间的一致性,后者分别通过 NMR 集合和 X 射线因子确定。对于 X 射线结构(对应于拥挤环境中的蛋白质),NOLB 导致预测和实验波动分布之间具有最佳的一致性,而对于 NMR 结构(对应于溶液中的蛋白质),性能的排序为 CABS-flex > UNRES-DSSP-flex > UNRES-flex > NOLB;然而,CABS-flex 有时会夸大小波动的程度,而 UNRES-DSSP-flex 则不会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/f33b8858a246/ct4c00754_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/00ed2cd07088/ct4c00754_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/369401834640/ct4c00754_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/6240cc4a46fb/ct4c00754_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/653414ffbb19/ct4c00754_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/ffb090e5f83a/ct4c00754_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/4f3f3feff607/ct4c00754_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/f33b8858a246/ct4c00754_0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/00ed2cd07088/ct4c00754_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/369401834640/ct4c00754_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/6240cc4a46fb/ct4c00754_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/653414ffbb19/ct4c00754_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/ffb090e5f83a/ct4c00754_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/4f3f3feff607/ct4c00754_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac40/11391579/f33b8858a246/ct4c00754_0007.jpg

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本文引用的文献

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2
Improvements and new functionalities of UNRES server for coarse-grained modeling of protein structure, dynamics, and interactions.用于蛋白质结构、动力学和相互作用粗粒度建模的UNRES服务器的改进及新功能。
Front Mol Biosci. 2022 Dec 14;9:1071428. doi: 10.3389/fmolb.2022.1071428. eCollection 2022.
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Optimization of parallel implementation of UNRES package for coarse-grained simulations to treat large proteins.
用于粗粒度模拟以处理大蛋白质的UNRES软件包并行实现的优化。
J Comput Chem. 2023 Feb 5;44(4):602-625. doi: 10.1002/jcc.27026. Epub 2022 Nov 15.
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B-factor accuracy in protein crystal structures.蛋白质晶体结构中的 B 因子精度。
Acta Crystallogr D Struct Biol. 2022 Jan 1;78(Pt 1):69-74. doi: 10.1107/S2059798321011736.
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Theory and Practice of Coarse-Grained Molecular Dynamics of Biologically Important Systems.生物重要体系的粗粒分子动力学的理论与实践。
Biomolecules. 2021 Sep 11;11(9):1347. doi: 10.3390/biom11091347.
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MEDUSA: Prediction of Protein Flexibility from Sequence.MEDUSA:从序列预测蛋白质柔性。
J Mol Biol. 2021 May 28;433(11):166882. doi: 10.1016/j.jmb.2021.166882. Epub 2021 Feb 20.
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Patterns in Protein Flexibility: A Comparison of NMR "Ensembles", MD Trajectories, and Crystallographic B-Factors.蛋白质灵活性模式:NMR“集合”、MD 轨迹和晶体学 B 因子的比较。
Molecules. 2021 Mar 9;26(5):1484. doi: 10.3390/molecules26051484.
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A method for validating the accuracy of NMR protein structures.一种验证 NMR 蛋白质结构准确性的方法。
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