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一种用于理解肽聚集的成对偏好相互作用模型。

A Pairwise Preferential Interaction Model for Understanding Peptide Aggregation.

作者信息

Kang Myungshim, Smith Paul Edward

机构信息

Department of Chemistry, Kansas State University, 213 CBC Building, Manhattan, KS 66506-0401, USA.

出版信息

Int J Thermophys. 2010 May 1;31(4-5):793-804. doi: 10.1007/s10765-009-0694-z.

Abstract

A pairwise preferential interaction model (PPIM), based on Kirkwood-Buff integrals, is developed to quantify and characterize the interactions between some of the functional groups commonly observed in peptides. The existing experimental data are analyzed to determine the preferential interaction (PI) parameters for different amino acid and small peptide systems in aqueous solutions. The PIs between the different functional groups present in the peptides are then isolated and quantified by assuming simple pairwise additivity. The PPIM approach provides consistent estimates for the pair interactions between the same functional groups obtained from different solute molecules. Furthermore, these interactions appear to be chemically intuitive. It is argued that this type of approach can provide valuable information concerning specific functional group correlations which could give rise to peptide aggregation.

摘要

基于柯克伍德-布夫积分开发了一种成对优先相互作用模型(PPIM),以量化和表征肽中常见的一些官能团之间的相互作用。分析现有实验数据以确定不同氨基酸和小肽系统在水溶液中的优先相互作用(PI)参数。然后通过假设简单的成对加和性来分离和量化肽中存在的不同官能团之间的PI。PPIM方法为从不同溶质分子获得的相同官能团之间的成对相互作用提供了一致的估计。此外,这些相互作用在化学上似乎是直观的。有人认为,这种方法可以提供有关可能导致肽聚集的特定官能团相关性的有价值信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e545/2914330/0072c595fe10/nihms187239f1.jpg

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