A Universal Score for Deconvolution of Intact Protein and Native Electrospray Mass Spectra

Marty, Michael T.

doi:10.1021/acs.analchem.9b05272

Cited by 28 publications

(38 citation statements)

References 28 publications

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“…Here, a scoring scheme was incorporated for each MS experiment to evaluate the deconvolution results and/or the mass assignment. For native MS, we integrated the UniScore for the simulation algorithm that evaluates the quality of the deconvolution with a universal score that is software-independent . After the mass assignment, each feature is reported with their scored mass error, DScore, UScore, FScore, CCScore, and MScore along with the global UniScore.…”

Section: Methodsmentioning

confidence: 99%

“…Regardless of the algorithm used for ESI deconvolution, the quality of the results is judged with a scoring system that is usually algorithm-dependent. Recently, a universal score (UniScore) based on the evaluation of critical steps during deconvolution has been released, promoting an unbiased scoring system to compare between multiple deconvolution algorithms …”

Section: Introductionmentioning

confidence: 99%

“…Recently, a universal score (UniScore) based on the evaluation of critical steps during deconvolution has been released, promoting an unbiased scoring system to compare between multiple deconvolution algorithms. 31 Protein/peptide database search and statistical modeling tools are well established in peptide-based bottom-up proteomics. Looking at finding new peptide-spectrum matches (PSMs) or integrating searching engine with scoring models has resulted in a variety of software, in addition to the commercial offerings Mascot 32 or SEQUEST.…”

Section: ■ Introductionmentioning

confidence: 99%

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Mass Spectrometry-Based Structural Analysis of Cysteine-Rich Metal-Binding Sites in Proteins with MetaOdysseus R Software

et al. 2020

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Identification of metal-binding sites in proteins and understanding metalcoupled protein folding mechanisms are aspects of high importance for the structure-tofunction relationship. Mass spectrometry (MS) has brought a powerful adjunct perspective to structural biology, obtaining from metal-to-protein stoichiometry to quaternary structure information. Currently, the different experimental and/or instrumental setups usually require the use of multiple data analysis software, and in some cases, they lack some of the main data analysis steps (MS processing, scoring, identification). Here, we present a comprehensive data analysis pipeline that addresses charge-state deconvolution, statistical scoring, and mass assignment for native MS, bottom-up, and native top-down with emphasis on metal−protein complexes. We have evaluated all of the approaches using assemblies of increasing complexity, including free and chemically labeled proteins, from low-to high-resolution MS. In all cases, the results have been compared with common software and proved how MetaOdysseus outperformed them.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: ■ Introductionmentioning

confidence: 99%

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Mass Spectrometry-Based Structural Analysis of Cysteine-Rich Metal-Binding Sites in Proteins with MetaOdysseus R Software

et al. 2020

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“…Deconvolution is the process by which pressures are assigned for each gas considered to be present in the MS. It is one of the most widely used techniques in the reconstruction and analysis of samples obtained by spectrometry and spectroscopy in many different areas of study, including Raman spectrometry for pediatric diagnoses [26], time-resolved fluorescence spectroscopy [27], nuclear instruments MS [28] and spectrometry analytics [29,30], among others.…”

Section: Iterative Deconvolutionmentioning

confidence: 99%

Reconstruction of Ultra-High Vacuum Mass Spectra Using Genetic Algorithms

et al. 2021

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In ultra-high vacuum systems, obtaining the composition of a mass spectrum is often a challenging task due to the highly overlapping nature of the individual profiles of the gas species that contribute to that spectrum, as well as the high differences in terms of degree of contribution (several orders of magnitude). This problem is even more complex when not only the presence but also a quantitative estimation of the contribution (partial pressure) of each species is required. This paper aims at estimating the relative contribution of each species in a target mass spectrum by combining a state-of-the-art machine learning method (multilabel classifier) to obtain a pool of candidate species based on a threshold applied to the probability scores given by the classifier with a genetic algorithm that aims at finding the partial pressure at which each one of the species contributes to the target mass spectrum. For this purpose, we use a dataset of synthetically generated samples. We explore different acceptance thresholds for the generation of initial populations, and we establish comparative metrics against the most novel method to date for automatically obtaining partial pressure contributions. Our results show a clear advantage in terms of the integral error metric (up to 112 times lower for simpler spectra) and computational times (up to 4 times lower for complex spectra) in favor of the proposed method, which is considered a substantial improvement for this task.

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“…A first study explored nanodiscs, bicelles and amphipols for native MS and showed that indeed the native oligomeric states of several integral membrane proteins were preserved in nanodiscs and bicelles while they differed from those obtained from detergent micelles or amphipols 112 . In particular, nanodiscs were therefore examined in detail; the complex and heterogeneous mass spectra further induced improvements in spectral deconvolution, 113–116 sample preparation 117–119 and method optimisation 119,120 . These improvements allowed, for instance, monitoring the insertion and oligomer assembly in the lipid bilayer 120,121 …”

Section: Unravelling the Architecture Of Membrane Protein Assemblies mentioning

confidence: 99%

Native mass spectrometry—A valuable tool in structural biology

Barth

Schmidt

2020

J Mass Spectrom

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Proteins and the complexes they form with their ligands are the players of cellular action. Their function is directly linked with their structure making the structural analysis of protein-ligand complexes essential. Classical techniques of structural biology include X-ray crystallography, nuclear magnetic resonance spectroscopy and recently distinguished cryo-electron microscopy. However, protein-ligand complexes are often dynamic and heterogeneous and consequently challenging for these techniques. Alternative approaches are therefore needed and gained importance during the last decades. One alternative is native mass spectrometry, which is the analysis of intact protein complexes in the gas phase. To achieve this, sample preparation and instrument conditions have to be optimised. Native mass spectrometry then reveals stoichiometry, protein interactions and topology of protein assemblies. Advanced techniques such as ion mobility and high-resolution mass spectrometry further add to the range of applications and deliver information on shape and microheterogeneity of the complexes. In this tutorial, we explain the basics of native mass spectrometry including sample requirements, instrument modifications and interpretation of native mass spectra. We further discuss the developments of native mass spectrometry and provide example spectra and applications.

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A Universal Score for Deconvolution of Intact Protein and Native Electrospray Mass Spectra

Cited by 28 publications

References 28 publications

Mass Spectrometry-Based Structural Analysis of Cysteine-Rich Metal-Binding Sites in Proteins with MetaOdysseus R Software

Mass Spectrometry-Based Structural Analysis of Cysteine-Rich Metal-Binding Sites in Proteins with MetaOdysseus R Software

Reconstruction of Ultra-High Vacuum Mass Spectra Using Genetic Algorithms

Native mass spectrometry—A valuable tool in structural biology

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