Profiling of Ubiquitination Modification Sites in Talin in Colorectal Carcinoma by Mass Spectrometry

PseAraUbi: predicting arabidopsis ubiquitination sites by incorporating the physico-chemical and structural features

We makes three kinds of important features from Arabidopsis thaliana: protein secondary structure based on the Chou-Fasman parameter, amino acids hydrophobicity and polarity information, and analyze their properties. Ubiquitination modification is an important post-translational modification of proteins, which participates in the regulation of many important life activities in cells. At present, ubiquitination proteomics research is mostly concentrated in animals and yeasts, while relatively few studies have been carried out in plants. It can be said that the calculation and prediction of Arabidopsis thaliana ubiquitination sites is still in its infancy. Based on this, we describe a calculation method, PseAraUbi (Prediction of Arabidopsis thaliana ubiquitination sites using pseudo amino acid composition), that can effectively detect ubiquitination sites on Arabidopsis thaliana using support vector machine learning classifiers. Based on protein sequence information, extract features from the Chou-Fasman parameter, amino acids hydrophobicity features, polarity information and selected for classification with the Boruta algorithm. PseAraUbi achieves promising performances with an AUC score of 0.953 with fivefold cross-validation on the training dataset, which are significantly better than that of the pioneer Arabidopsis thaliana ubiquitination sites method. We also proved the ability of our proposed method on independent test sets, thus gaining a competitive advantage. In addition, we also in-depth analyzed the physicochemical properties of amino acids in the region adjacent to the ubiquitination site. To facilitate the community, the source code, optimal feature subset, ubiquitination sites dataset in the Arbidopsis proteome are available at GitHub ( https://github.com/HNUBioinformatics/PseAraUbi.git ) for interest users.

Affinity capture in bottom-up protein analysis - Overview of current status of proteolytic peptide capture using antibodies and molecularly imprinted polymers

Antibody-based affinity capture has become the gold standard in sample preparation for determination of low-abundance protein biomarkers in biological matrices prior to liquid chromatography-mass spectrometry (LC-MS) determination. This comprises both capture of intact proteins prior to the digestion step and capture of proteolytic peptides after digestion of the sample. The latter can be performed both using antibodies specifically developed to capture target proteolytic peptides, as well as by the less explored use of anti-protein antibodies to capture the proteolytic epitope peptide. Molecularly imprinted polymers (MIPs), also called plastic antibodies are another affinity-based approach emerging as sample preparation technique in LC-MS based protein biomarker analysis. The current review gives a critical and comprehensive overview of proteolytic peptide capture using antibodies and MIPs in LC-MS based protein biomarker determination during the last five years. The main emphasis is on capture of non-modified peptides, while a brief overview of affinity capture of peptides containing post-translational modifications (PTMs) is provided.