Mass spectrometry as a readout of protein structure and function

Winston, Rachel L.; Fitzgerald, Michael C.

doi:10.1002/(sici)1098-2787(1997)16:4<165::aid-mas1>3.0.co;2-f

Cited by 115 publications

(64 citation statements)

References 82 publications

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“…Such effects can even be exploited for folding studies, but require at the same time accurately controlled conditions. The effects of temperature and cone voltage have been extensively documented [3,11,12,13,14,15]. As reported previously,…”

Section: Introductionmentioning

confidence: 86%

Interpreting conformational effects in protein nano-ESI-MS spectra

et al. 2003

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Nano-electrospray-ionization mass spectrometry (nano-ESI-MS) is employed here to describe equilibrium protein conformational transitions and to analyze the influence of instrumental settings, pH, and solvent surface tension on the charge-state distributions (CSD). A first set of experiments shows that high flow rates of N(2) as curtain gas can induce unfolding of cytochrome c (cyt c) and myoglobin (Mb), under conditions in which the stability of the native protein structure has already been reduced by acidification. However, it is possible to identify conditions under which the instrumental settings are not limiting factors for the conformational stability of the protein inside ESI droplets. Under such conditions, equilibrium unfolding transitions described by ESI-MS are comparable with those obtained by other established biophysical methods. Experiments with the very stable proteins ubiquitin (Ubq) and lysozyme (Lyz) enable testing of the influence of extreme pH changes on the ESI process, uncoupled from acid-induced unfolding. When HCl is used for acidification, Ubq and Lyz mass spectra do not change between pH~7 and pH 2.2, indicating that the CSD is highly characteristic of a given protein conformation and not directly affected by even large pH changes. Use of formic or acetic acid for acidification of Ubq solutions results in major spectral changes that can be interpreted in terms of protein unfolding as a result of the increased hydrophobicity of the solvent. On the other hand, Lyz, cyt c, and Mb enable direct comparison of protein CSD (corresponding to either the folded or the unfolded protein) in HCl or acetic acid solutions at low pH. The values of surface tension for these solutions differ significantly. Confirming indications already present in the literature, we observe very similar CSD under these solvent conditions for several proteins in either compact or disordered conformations. The same is true for comparison between water and water-acetic acid for folded cyt c and Lyz. Thus, protein CSD from water-acetic solutions do not seem to be limited by the low surface tension of acetic acid as previously suggested. This result could reflect a general lack of dependence of protein CSD on the surface tension of the solvent. However, it is also possible that the effect of acetic acid on the precursor ESI droplets is smaller than generally assumed.

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Section: Introductionmentioning

confidence: 86%

Interpreting conformational effects in protein nano-ESI-MS spectra

et al. 2003

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“…While the preservation of non-covalent interactions, in the form of salt and solvent bound to proteins, had been observed a few years previously, this detection of specific and biologically relevant complexes represented a major breakthrough [1,8,9]. …”

Section: The Development Of Ms For Structural Biologymentioning

confidence: 99%

“…These studies were soon followed by an array of other examples in which non-covalent interactions were maintained in the gas phase including the notable first measurement of a protein–protein assembly, the human immunodeficiency virus protease dimer [13]. These, and other, pioneering studies are described in a comprehensive review [1] and, together with the realization that proteins perform their cellular roles not in isolation but rather in complex with a multitude of other biomolecules, paved the way for MS in structural biology [8,9]. …”

Section: The Development Of Ms For Structural Biologymentioning

confidence: 99%

“…The reduced flow rate has the added benefit of producing smaller initial droplet sizes [24], which both increases sensitivity and salt tolerance [25], and crucially negates the need for organic co-solvents and high interface temperatures. In this way, the examination of proteins in neutral aqueous buffers in which their structure is preserved has become possible, in a strategy often termed ‘Native MS’ [9,26] (figure 2 a ).

Figure 2.Four example mass spectra of the same protein complex subjected to different experimental conditions.…”

Section: The Development Of Ms For Structural Biologymentioning

confidence: 99%

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Two decades of studying non-covalent biomolecular assemblies by means of electrospray ionization mass spectrometry

Hilton

Benesch

2012

J. R. Soc. Interface.

130

122

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Mass spectrometry (MS) is a recognized approach for characterizing proteins and the complexes they assemble into. This application of a long-established physico-chemical tool to the frontiers of structural biology has stemmed from experiments performed in the early 1990s. While initial studies focused on the elucidation of stoichiometry by means of simple mass determination, developments in MS technology and methodology now allow researchers to address questions of shape, inter-subunit connectivity and protein dynamics. Here, we chart the remarkable rise of MS and its application to biomolecular complexes over the last two decades.

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“…However, it is not the sole factor. Such factors involve, among others, the sample preparation methods [20], pH and composition of the solution [21][22][23][24], matrix composition [25], the characteristics of the MS apparatus [26][27][28] and characteristics of the analyzed sample (for example, sugar content [29,30], hydrophobicity [31], secondary structure [32], 3-D structure [33] and amino acid position in the sequence [34]). To generate theoretical models predicting the peak intensities of a PMF experiment, these factors should be taken into consideration.…”

Section: Introductionmentioning

confidence: 99%

Peptide mass fingerprinting peak intensity prediction: Extracting knowledge from spectra

et al. 2002

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Matrix-assisted laser desorption/ionization-time of flight mass spectrometry has become a valuable tool in proteomics. With the increasing acquisition rate of mass spectrometers, one of the major issues is the development of accurate, efficient and automatic peptide mass fingerprinting (PMF) identification tools. Current tools are mostly based on counting the number of experimental peptide masses matching with theoretical masses. Almost all of them use additional criteria such as isoelectric point, molecular weight, PTMs, taxonomy or enzymatic cleavage rules to enhance prediction performance. However, these identification tools seldom use peak intensities as parameter as there is currently no model predicting the intensities based on the physicochemical properties of peptides. In this work, we used standard datamining methods such as classification and regression methods to find correlations between peak intensities and the properties of the peptides composing a PMF spectrum. These methods were applied on a dataset comprising a series of PMF experiments involving 157 proteins. We found that the C4.5 method gave the more informative results for the classification task (prediction of the presence or absence of a peptide in a spectra) and M5' for the regression methods (prediction of the normalized intensity of a peptide peak). The C4.5 result correctly classified 88% of the theoretical peaks; whereas the M5' peak intensities had a correlation coefficient of 0.6743 with the experimental peak intensities. These methods enabled us to obtain decision and model trees that can be directly used for prediction and identification of PMF results. The work performed permitted to lay the foundations of a method to analyze factors influencing the peak intensity of PMF spectra. A simple extension of this analysis could lead to improve the accuracy of the results by using a larger dataset. Additional peptide characteristics or even PMF experimental parameters can also be taken into account in the datamining process to analyze their influence on the peak intensity. Furthermore, this datamining approach can certainly be extended to the tandem mass spectrometry domain or other mass spectrometry derived methods.

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Mass spectrometry as a readout of protein structure and function

Cited by 115 publications

References 82 publications

Interpreting conformational effects in protein nano-ESI-MS spectra

Interpreting conformational effects in protein nano-ESI-MS spectra

Two decades of studying non-covalent biomolecular assemblies by means of electrospray ionization mass spectrometry

Peptide mass fingerprinting peak intensity prediction: Extracting knowledge from spectra

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