scholarly journals Evaluation of Mass Spectrometry-based Proteomic Search Algorithms: Parent Protein Profiling of 22 MS/MS Experiments in Saccharomyces cerevisiae

2013 ◽  
Author(s):  
Miin Sophia Lin
Keyword(s):  
Mass Spectrometry ◽  
Saccharomyces Cerevisiae ◽  
Search Algorithms ◽  
Protein Profiling ◽  
Parent Protein

scholarly journals Assessment of MS/MS Search Algorithms with Parent-Protein Profiling

2014 ◽  
Vol 13 (4) ◽  
pp. 1823-1832 ◽  
Author(s):  
Miin S. Lin ◽  
Justin J. Cherny ◽  
Claire T. Fournier ◽  
Samuel J. Roth ◽  
Danny Krizanc ◽  
...  
Keyword(s):  
Search Algorithms ◽  
Protein Profiling ◽  
Parent Protein ◽  
Ms Search

Suzuki–Miyaura cross-coupling for chemoproteomic applications

2020 ◽  
Author(s):  
Jian Cao ◽  
Ernest Armenta ◽  
Lisa Boatner ◽  
Heta Desai ◽  
Neil Chan ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cross Coupling ◽  
Protein Profiling ◽  
Protein Labeling ◽  
Caspase 8 ◽  
Complex Cell ◽  
Bioorthogonal Chemistry ◽  
Reaction Conditions ◽  
Target Deconvolution ◽  
Palladium Catalyzed

Bioorthogonal chemistry is a mainstay of chemoproteomic sample preparation workflows. While numerous transformations are now available, chemoproteomic studies still rely overwhelmingly on copper-catalyzed azide –alkyne cycloaddition (CuAAC) or 'click' chemistry. Here we demonstrate that gel-based activity-based protein profiling (ABPP) and mass-spectrometry-based chemoproteomic profiling can be conducted using Suzuki–Miyaura cross-coupling. We identify reaction conditions that proceed in complex cell lysates and find that Suzuki –Miyaura cross-coupling and CuAAC yield comparable chemoproteomic coverage. Importantly, Suzuki–Miyaura is also compatible with chemoproteomic target deconvolution, as demonstrated using structurally matched probes tailored to react with the cysteine protease caspase-8. Uniquely enabled by the observed orthogonality of palladium-catalyzed cross-coupling and CuAAC, we combine both reactions to achieve dual protein labeling.

scholarly journals Skimmer CID‒ion trap mass spectrometry of phosphotyrosine‒containing peptides

2004 ◽  
Vol 18 (3) ◽  
pp. 441-451
Author(s):  
Melissa D. Zolodz ◽  
Karl V. Wood
Keyword(s):  
Mass Spectrometry ◽  
Ion Trap ◽  
Phosphorylation Site ◽  
Ion Trap Mass Spectrometry ◽  
Cellular Functions ◽  
Factors Affecting ◽  
Parent Protein ◽  
Phosphorylated Peptides ◽  
Phosphorylated Peptide ◽  
Analytical Tools

Proteomic analysis is becoming a popular field in science. Analysis of protein modifications is useful in deciphering cellular functions and errors in pathways that can result in disease. There has been increased interest in the phosphotyrosine proteome. Due to the difficulty in finding the location of the tyrosine phosphorylation site in the tyrosine phosphorylated peptide or even to verify that the parent protein is a phosphotyrosyl‒protein, new analytical tools are being developed. The phosphotyrosine immonium ion can be produced via skimmer CID for detection via ion trap mass spectrometry and is a useful marker for the indication of the presence of a phosphotyrosine residue. Skimmer CID analysis can also be used to differentiate phosphotyrosine‒containing peptides from other phosphorylated peptides. In this study, phosphotyrosine‒containing peptides were analyzed by skimmer CID in an ion trap mass spectrometer. The factors affecting the signal abundance of the phosphotyrosine immonium ion were investigated.

Comparison of Supervised Classification Methods for Protein Profiling in Cancer Diagnosis

2007 ◽  
Vol 3 ◽  
pp. 117693510700300 ◽  
Author(s):  
Nadège Dossat ◽  
Alain Mangé ◽  
Jérôme Solassol ◽  
William Jacot ◽  
Ludovic Lhermitte ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Supervised Classification ◽  
Protein Profiling ◽  
Clinical Proteomics ◽  
High Dimensional ◽  
Classification Methods ◽  
Linear Discriminant ◽  
Supervised Classification Methods

A key challenge in clinical proteomics of cancer is the identification of biomarkers that could allow detection, diagnosis and prognosis of the diseases. Recent advances in mass spectrometry and proteomic instrumentations offer unique chance to rapidly identify these markers. These advances pose considerable challenges, similar to those created by microarray-based investigation, for the discovery of pattern of markers from high-dimensional data, specific to each pathologic state (e.g. normal vs cancer). We propose a three-step strategy to select important markers from high-dimensional mass spectrometry data using surface enhanced laser desorption/ionization (SELDI) technology. The first two steps are the selection of the most discriminating biomarkers with a construction of different classifiers. Finally, we compare and validate their performance and robustness using different supervised classification methods such as Support Vector Machine, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Neural Networks, Classification Trees and Boosting Trees. We show that the proposed method is suitable for analysing high-throughput proteomics data and that the combination of logistic regression and Linear Discriminant Analysis outperform other methods tested.

Nanoprobe-Based Affinity Mass Spectrometry for Cancer Marker Protein Profiling

2007 ◽  
Author(s):  
Li-Shing Huang ◽  
Yuh-Yih Chien ◽  
Shu-Hua Chen ◽  
Po-Chiao Lin ◽  
Kai-Yi Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Profiling ◽  
Marker Protein ◽  
Cancer Marker

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

2019 ◽  
Vol 25 (13) ◽  
pp. 1536-1553 ◽  
Author(s):  
Jing Tang ◽  
Yunxia Wang ◽  
Yi Li ◽  
Yang Zhang ◽  
Runyuan Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Information Sources ◽  
Protein Quantification ◽  
Protein Profiling ◽  
Label Free ◽  
Dynamic Information ◽  
Data Repositories ◽  
Research Directions ◽  
Technological Advances ◽  
Recent Trends

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

scholarly journals Protein Profiling in Brain Tumors Using Mass Spectrometry

2004 ◽  
Vol 10 (3) ◽  
pp. 981-987 ◽  
Author(s):  
Sarah A. Schwartz ◽  
Robert J. Weil ◽  
Mahlon D. Johnson ◽  
Steven A. Toms ◽  
Richard M. Caprioli
Keyword(s):  
Mass Spectrometry ◽  
Brain Tumors ◽  
Protein Profiling
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