2018
DOI: 10.1002/pmic.201800060
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Conformational Characterization and Classification of Intrinsically Disordered Proteins by Native Mass Spectrometry and Charge‐State Distribution Analysis

Abstract: Intrinsically disordered proteins (IDPs) are systematically under‐represented in structural proteomics studies. Their structural characterization implies description of the dynamic conformational ensembles populated by these polymers in solution, posing major challenges to biophysical methods. “Native” MS (native‐MS) has emerged as a central tool in this field, conjugating the unique MS analytical power with structurally meaningful descriptors, like solvent‐accessible surface area (SASA) and collisional cross … Show more

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Cited by 40 publications
(49 citation statements)
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“…[11] The review article by Santambrogio et al summarizes recent advances in application of native mass spectrometry (native-MS) to the structural analysis of IDPs. [12] Native-MS is a branch of biopolymer analysis by MS conducted using mild desolvation/ionization methods, such as nano-electrospray ionization (nanoESI) of samples at mild voltage and temperature (room temperature), that prevent backbone fragmentation and preserve non-covalent interactions and also using non-denaturing, volatile buffers. Although the authors compared the outputs of native-MS analysis with results of more traditional low-resolution methods for the characterization of protein structure in solution, their major focus was on utilization of charge-state-distribution (CSD) analysis for the conformational characterization of IDPs.…”
Section: Doi: 101002/pmic201900085mentioning
confidence: 99%
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“…[11] The review article by Santambrogio et al summarizes recent advances in application of native mass spectrometry (native-MS) to the structural analysis of IDPs. [12] Native-MS is a branch of biopolymer analysis by MS conducted using mild desolvation/ionization methods, such as nano-electrospray ionization (nanoESI) of samples at mild voltage and temperature (room temperature), that prevent backbone fragmentation and preserve non-covalent interactions and also using non-denaturing, volatile buffers. Although the authors compared the outputs of native-MS analysis with results of more traditional low-resolution methods for the characterization of protein structure in solution, their major focus was on utilization of charge-state-distribution (CSD) analysis for the conformational characterization of IDPs.…”
Section: Doi: 101002/pmic201900085mentioning
confidence: 99%
“…Although the authors compared the outputs of native-MS analysis with results of more traditional low-resolution methods for the characterization of protein structure in solution, their major focus was on utilization of charge-state-distribution (CSD) analysis for the conformational characterization of IDPs. [12] Sharma et al describe a computational tool OPAL+ for identification in IDPs/IDPRs-specific disorder-based binding regions, known as molecular recognition features (MoRFs). [13] This tool represents an improved MoRF predictor that uses multiple support vector machine (SVM) models, each trained using MoRFs of different lengths, utilizes evolutionary information of the ID-PRs, as well as incorporates the hidden Markov model (HMM) profiles and utilizes physicochemical properties of MoRFs and their flanking regions.…”
Section: Doi: 101002/pmic201900085mentioning
confidence: 99%
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“…Native mass spectrometry (native MS) has developed into a central tool for structural biology [23,24,25,26]. The analysis of charge states populated by globular and disordered proteins by native MS has shown effects of denaturants [27], stabilizers [28], metal binding [29], and protein–protein interactions [30], just to mention some examples.…”
Section: Introductionmentioning
confidence: 99%
“…A large amount of evidence suggests that the ionization patterns of globular and disordered proteins are similarly affected by conformational properties [23,39,40,41]. Native MS has described conformational responses of AS to alcohols, pH, and copper binding consistent with NMR and other solution methods [29,33].…”
Section: Introductionmentioning
confidence: 99%