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PACSAB 服务器:一种基于网络的工具,用于研究聚集和无序及折叠蛋白质的构象整体。

PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins.

机构信息

Department of Physics, Universitat Politècnica de Catalunya, B4-B5 Campus Nord, Jordi Girona 1-3, 08034 Barcelona, Spain.

出版信息

Int J Mol Sci. 2024 May 30;25(11):6021. doi: 10.3390/ijms25116021.

DOI:10.3390/ijms25116021
PMID:38892222
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11172606/
Abstract

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.

摘要

我们在本文中介绍了 PACSAB 服务器,该服务器旨在为分子生物学领域的研究人员提供有关稳定和无序蛋白质结构集合和相互作用的信息。使用此工具不需要任何计算技能,因为用户只需上传要研究的蛋白质结构即可;服务器使用 PACSAB 模型运行模拟,该模型是一种高度精确的粗粒度模型,对于探索多蛋白系统的构象空间,其效率远高于标准分子动力学。基于该模型的模拟生成的轨迹揭示了所研究蛋白质的聚集倾向,确定了在聚集过程中起核心作用的残基,并再现了无序蛋白质的整个构象空间。所有这些信息都显示在网页上,并可以下载。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/535e0b751c4a/ijms-25-06021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/84be05cddbd7/ijms-25-06021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/3d1ee6910597/ijms-25-06021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/1971d9adfa04/ijms-25-06021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/5a5b4a1d4399/ijms-25-06021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/2d50da2e335b/ijms-25-06021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/744cf0689e0a/ijms-25-06021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/535e0b751c4a/ijms-25-06021-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/84be05cddbd7/ijms-25-06021-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/3d1ee6910597/ijms-25-06021-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/1971d9adfa04/ijms-25-06021-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/5a5b4a1d4399/ijms-25-06021-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/2d50da2e335b/ijms-25-06021-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/744cf0689e0a/ijms-25-06021-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c15/11172606/535e0b751c4a/ijms-25-06021-g007.jpg

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本文引用的文献

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Computational methods to predict protein aggregation.预测蛋白质聚集的计算方法。
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Accurate Description of Protein-Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model.基于隐式溶剂的PACSAB蛋白质模型对蛋白质-蛋白质识别和蛋白质聚集的准确描述。
Polymers (Basel). 2021 Nov 29;13(23):4172. doi: 10.3390/polym13234172.
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Effect of the Water Model in Simulations of Protein-Protein Recognition and Association.
水模型在蛋白质-蛋白质识别与缔合模拟中的作用
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