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塞尔马特拉:用于质谱蛋白质分析的网络应用程序。

Selymatra: A web application for protein-profiling analysis of mass spectra.

机构信息

Department of Science and Technology, University of Naples Parthenope, Naples, Italy.

Institute of Biochemistry and Cellular Biology, National Research Council, Naples, 80131, Italy.

出版信息

Biotechnol Appl Biochem. 2022 Oct;69(5):1821-1829. doi: 10.1002/bab.2249. Epub 2021 Sep 20.

Abstract

Surface enhanced laser desorption/ionization-time of flight (SELDI-TOF) mass spectrometry is a variant of the matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. It is used in many cases especially for the analysis of protein profiling and for preliminary screening of biomarkers in complex samples. Unfortunately, these analyses are time consuming and protein identification is generally strictly limited. SELDI-TOF analysis of mass spectra (SELYMATRA) is a web application (WA) developed to reduce these limitations by (i) automating the identification processes and (ii) introducing the possibility to predict proteins in complex mixtures from cells and tissues. The WA architectural pattern is the model-view-controller, commonly used in software development. The WA compares the mass value between two mass spectra (sample vs. control) to extract differences, and, according to the set parameters, it queries a local database to predict most likely proteins based on their masses and different expression amplification. The WA was validated in a cellular model overexpressing a tagged NURR1 receptor, being able to recognize the tagged protein in the profiling of transformed cells. A help page, including a description of parameters for WA use, is available on the website.

摘要

表面增强激光解吸/电离飞行时间(SELDI-TOF)质谱是基质辅助激光解吸/电离飞行时间(MALDI-TOF)质谱的一种变体。它在许多情况下都有应用,特别是用于分析蛋白质谱和对复杂样本中的生物标志物进行初步筛选。不幸的是,这些分析耗时且蛋白质鉴定通常受到严格限制。SELYMATRA 是一种用于减少这些限制的网络应用程序(WA),它通过(i)自动化鉴定过程和(ii)引入从细胞和组织中预测复杂混合物中蛋白质的可能性来实现。WA 的架构模式是模型-视图-控制器,这在软件开发中很常用。WA 比较两个质谱(样本与对照)之间的质量值以提取差异,并根据设置的参数查询本地数据库,根据它们的质量和不同的表达放大来预测最可能的蛋白质。该 WA 在过表达标记 NURR1 受体的细胞模型中进行了验证,能够在转化细胞的分析中识别标记蛋白。在网站上提供了一个帮助页面,其中包括 WA 使用参数的说明。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8fce/9912196/875369e95906/BAB-69-1821-g002.jpg

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