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• W2070931567 abstract "Redox proteomics has yielded molecular insight into diseases of protein dysfunction attributable to oxidative stress, underscoring the need for robust detection of protein oxidation products. Additionally, oxidative protein surface mapping techniques utilize hydroxyl radicals to gain structural insight about solvent exposure. Interpretation of tandem mass spectral data is a critical challenge for such investigations, because reactive oxygen species target a wide breadth of amino acids. Additionally, oxidized peptides may be generated in a wide range of abundances since the reactivity of hydroxyl radicals with different amino acids spans 3 orders of magnitude. Taken together, these attributes of oxidative footprinting pose both experimental and computational challenges to detecting oxidized peptides that are naturally less abundant than their unoxidized counterparts. In this study, model proteins were oxidized electrochemically and analyzed at both the intact protein and peptide levels. A multidimensional chromatographic strategy was utilized to expand the dynamic range of oxidized peptide measurements. Peptide mass spectral data were searched by the “hybrid” software packages Inspect and Byonic, which incorporate de novo elements of spectral interpretation into a database search. This dynamic search capacity accommodates the challenge of searching for more than 40 oxidative mass shifts that can occur in a staggering variety of possible combinatorial occurrences. A prevailing set of oxidized residues was identified with this comparative approach, and evaluation of these sites was informed by solvent accessible surface area gleaned through molecular dynamics simulations. Along with increased levels of oxidation around highly reactive “hotspot” sites as expected, the enhanced sensitivity of these measurements uncovered a surprising level of oxidation on less reactive residues." @default.
• W2070931567 created "2016-06-24" @default.
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• W2070931567 date "2013-06-19" @default.
• W2070931567 modified "2023-09-27" @default.
• W2070931567 title "Comparative Informatics Analysis to Evaluate Site-Specific Protein Oxidation in Multidimensional LC–MS/MS Data" @default.
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• W2070931567 doi "https://doi.org/10.1021/pr400141p" @default.
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