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利用集合模型从圆二色性估计肽的螺旋性。

Estimation of Peptide Helicity from Circular Dichroism Using the Ensemble Model.

机构信息

Department of Physical Chemistry, Faculty of Chemistry and Chemical Technology, University of Ljubljana, 1000 Ljubljana, Slovenia.

出版信息

J Phys Chem B. 2024 Mar 21;128(11):2652-2663. doi: 10.1021/acs.jpcb.3c07511. Epub 2024 Mar 12.

DOI:10.1021/acs.jpcb.3c07511
PMID:38470351
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10961730/
Abstract

An established method for the quantitation of the helix content in peptides using circular dichroism (CD) relies on the linear spectroscopic model. This model assumes an average value of the helix-length correction for all peptide conformers, irrespective of the length of the helical segment. Here we assess the validity of this approximation and introduce a more physically realistic ensemble-based analysis of the CD signal in which the length correction is assigned specifically to each ensemble conformer. We demonstrate that the linear model underestimates peptide helicity, with the difference depending on the ensemble composition. We developed a computer program that implements the ensemble model to estimate the peptide helicity. Using this model and the CD data set covering a broad range of helicities, we recalibrate CD baseline parameters and redetermine helix-coil parameters for the alanine-rich peptide. We show that the ensemble model leverages small differences in signal between conformers to extract more information from the experimental data, enabling the determination of several poorly defined quantities, such as the nucleation constant and heat capacity change associated with helix folding. Overall, the presented ensemble-based treatment of the CD signal, together with the recalibrated values of the spectroscopic baseline parameters, provides a coherent framework for the analysis of the peptide helix content.

摘要

一种利用圆二色性(CD)定量测定肽中螺旋含量的成熟方法依赖于线性光谱模型。该模型假设所有肽构象的螺旋长度校正平均值,而不考虑螺旋段的长度。在这里,我们评估了这种近似的有效性,并引入了一种更符合物理现实的基于集合的 CD 信号分析方法,其中长度校正专门分配给每个集合构象。我们证明了线性模型低估了肽的螺旋度,其差异取决于集合的组成。我们开发了一个计算机程序来实现集合模型以估计肽的螺旋度。使用该模型和涵盖广泛螺旋度范围的 CD 数据集,我们重新校准 CD 基线参数,并重新确定富含丙氨酸的肽的螺旋-卷曲参数。我们表明,集合模型利用构象之间信号的微小差异从实验数据中提取更多信息,从而能够确定几个定义不明确的量,例如与螺旋折叠相关的成核常数和热容变化。总体而言,所提出的基于集合的 CD 信号处理方法以及光谱基线参数的重新校准值为分析肽螺旋含量提供了一个连贯的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/9b90cd04ffc0/jp3c07511_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/cb6a3588beac/jp3c07511_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/f5aa2bd72e7c/jp3c07511_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/b73dd60b369e/jp3c07511_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/dab69b72c15b/jp3c07511_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/0e2d9ab20d6b/jp3c07511_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/9b90cd04ffc0/jp3c07511_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/cb6a3588beac/jp3c07511_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/f5aa2bd72e7c/jp3c07511_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/b73dd60b369e/jp3c07511_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/dab69b72c15b/jp3c07511_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/0e2d9ab20d6b/jp3c07511_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4919/10961730/9b90cd04ffc0/jp3c07511_0006.jpg

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