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Wang CR, McFarlane LO, Pukala TL. Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions. Toxicon 2024; 247:107841. [PMID: 38950738 DOI: 10.1016/j.toxicon.2024.107841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/03/2024]
Abstract
Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.
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Affiliation(s)
- C Ruth Wang
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Lewis O McFarlane
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Tara L Pukala
- Discipline of Chemistry, School of Physics, Chemistry and Earth Sciences, The University of Adelaide, Adelaide, 5005, Australia.
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2
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Voeten RLC, Majeed HA, Bos TS, Somsen GW, Haselberg R. Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry. JOURNAL OF MASS SPECTROMETRY : JMS 2024; 59:e5021. [PMID: 38605451 DOI: 10.1002/jms.5021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 10/13/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.
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Affiliation(s)
- Robert L C Voeten
- Division of BioAnalytical Chemistry, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
- TI-COAST, Amsterdam, The Netherlands
| | - Hany A Majeed
- Division of BioAnalytical Chemistry, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Tijmen S Bos
- Division of BioAnalytical Chemistry, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Govert W Somsen
- Division of BioAnalytical Chemistry, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
| | - Rob Haselberg
- Division of BioAnalytical Chemistry, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute of Molecular and Life Sciences (AIMMS), Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, The Netherlands
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3
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Turzo SMBA, Seffernick JT, Lyskov S, Lindert S. Predicting ion mobility collision cross sections using projection approximation with ROSIE-PARCS webserver. Brief Bioinform 2023; 24:bbad308. [PMID: 37609950 PMCID: PMC10516336 DOI: 10.1093/bib/bbad308] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/03/2023] [Accepted: 08/08/2023] [Indexed: 08/24/2023] Open
Abstract
Ion mobility coupled to mass spectrometry informs on the shape and size of protein structures in the form of a collision cross section (CCSIM). Although there are several computational methods for predicting CCSIM based on protein structures, including our previously developed projection approximation using rough circular shapes (PARCS), the process usually requires prior experience with the command-line interface. To overcome this challenge, here we present a web application on the Rosetta Online Server that Includes Everyone (ROSIE) webserver to predict CCSIM from protein structure using projection approximation with PARCS. In this web interface, the user is only required to provide one or more PDB files as input. Results from our case studies suggest that CCSIM predictions (with ROSIE-PARCS) are highly accurate with an average error of 6.12%. Furthermore, the absolute difference between CCSIM and CCSPARCS can help in distinguishing accurate from inaccurate AlphaFold2 protein structure predictions. ROSIE-PARCS is designed with a user-friendly interface, is available publicly and is free to use. The ROSIE-PARCS web interface is supported by all major web browsers and can be accessed via this link (https://rosie.graylab.jhu.edu).
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Affiliation(s)
- S M Bargeen Alam Turzo
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH 43210, USA
| | - Justin T Seffernick
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH 43210, USA
| | - Sergey Lyskov
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH 43210, USA
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4
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Panda A, Brown C, Gupta K. Studying Membrane Protein-Lipid Specificity through Direct Native Mass Spectrometric Analysis from Tunable Proteoliposomes. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1917-1927. [PMID: 37432128 PMCID: PMC10932607 DOI: 10.1021/jasms.3c00110] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
Native mass spectrometry (nMS) has emerged as a key analytical tool to study the organizational states of proteins and their complexes with both endogenous and exogenous ligands. Specifically, for membrane proteins, it provides a key analytical dimension to determine the identity of bound lipids and to decipher their effects on the observed structural assembly. We recently developed an approach to study membrane proteins directly from intact and tunable lipid membranes where both the biophysical properties of the membrane and its lipid compositions can be customized. Extending this, we use our liposome-nMS platform to decipher the lipid specificity of membrane proteins through their multiorganelle trafficking pathways. To demonstrate this, we used VAMP2 and reconstituted it in the endoplasmic reticulum (ER), Golgi, synaptic vesicle (SV), and plasma membrane (PM) mimicking liposomes. By directly studying VAMP2 from these customized liposomes, we show how the same transmembrane protein can bind to different sets of lipids in different organellar-mimicking membranes. Considering that the cellular trafficking pathway of most eukaryotic integral membrane proteins involves residence in multiple organellar membranes, this study highlights how the lipid-specificity of the same integral membrane protein may change depending on the membrane context. Further, leveraging the capability of the platform to study membrane proteins from liposomes with curated biophysical properties, we show how we can disentangle chemical versus biophysical properties, of individual lipids in regulating membrane protein assembly.
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Affiliation(s)
- Aniruddha Panda
- Nanobiology Institute, Yale University, West Haven, Connecticut 06516, United States
- Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06520, United States
| | - Caroline Brown
- Nanobiology Institute, Yale University, West Haven, Connecticut 06516, United States
- Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06520, United States
| | - Kallol Gupta
- Nanobiology Institute, Yale University, West Haven, Connecticut 06516, United States
- Department of Cell Biology, Yale University School of Medicine, New Haven, Connecticut 06520, United States
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5
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Eaton RM, Zercher BP, Wageman A, Bush MF. A Flexible, Modular Platform for Multidimensional Ion Mobility of Native-like Ions. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:1175-1185. [PMID: 37171243 PMCID: PMC10548348 DOI: 10.1021/jasms.3c00112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Native ion mobility (IM) mass spectrometry (MS) is used to probe the size, shape, and assembly of biomolecular complexes. IM-IM-MS can increase the amount of information available in structural studies by isolating subpopulations of structures for further analysis. Previously, IM-IM-MS has been implemented using the Structures for Lossless Ion Manipulations (SLIM) architecture to probe the structural stability of gas-phase protein ions. Here, a new multidimensional IM instrument constructed from SLIM devices is characterized using multiple operational modes. In this new design, modular devices are used to perform all ion manipulations, including initial accumulation, injection, separation, selection, and trapping. Using single-dimension IM, collision cross section (Ω) values are determined for a set of native-like ions. These Ω values are within 3% of those reported previously based on measurements using RF-confining drift cells. Tandem IM experiments are performed on a sample of ubiquitin ions that contains both compact and partially unfolded structures, demonstrating that this platform can isolate subpopulations of structures. Finally, additional modes of analysis, including multiplexed IM and inverse IM, are demonstrated using this platform. The ability of this platform to quickly switch between different modes of IM analysis makes it a highly flexible tool for studying protein structures and dynamics.
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Affiliation(s)
- Rachel M. Eaton
- University of Washington, Department of Chemistry, Box 351700, Seattle, WA 98195-1700
| | - Benjamin P. Zercher
- University of Washington, Department of Chemistry, Box 351700, Seattle, WA 98195-1700
| | - AnneClaire Wageman
- University of Washington, Department of Chemistry, Box 351700, Seattle, WA 98195-1700
| | - Matthew F. Bush
- University of Washington, Department of Chemistry, Box 351700, Seattle, WA 98195-1700
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6
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Turzo SMBA, Seffernick JT, Rolland AD, Donor MT, Heinze S, Prell JS, Wysocki VH, Lindert S. Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction. Nat Commun 2022; 13:4377. [PMID: 35902583 PMCID: PMC9334640 DOI: 10.1038/s41467-022-32075-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
Ion mobility (IM) mass spectrometry provides structural information about protein shape and size in the form of an orientationally-averaged collision cross-section (CCSIM). While IM data have been used with various computational methods, they have not yet been utilized to predict monomeric protein structure from sequence. Here, we show that IM data can significantly improve protein structure determination using the modelling suite Rosetta. We develop the Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm that allows for fast and accurate prediction of CCSIM from structure. Following successful testing of the PARCS algorithm, we use an integrative modelling approach to utilize IM data for protein structure prediction. Additionally, we propose a confidence metric that identifies near native models in the absence of a known structure. The results of this study demonstrate the ability of IM data to consistently improve protein structure prediction.
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Affiliation(s)
- S M Bargeen Alam Turzo
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH, 43210, USA
| | - Justin T Seffernick
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH, 43210, USA
| | - Amber D Rolland
- Department of Chemistry and Biochemistry and Materials Science Institute, University of Oregon, Eugene, OR, 97403, USA
| | - Micah T Donor
- Department of Chemistry and Biochemistry and Materials Science Institute, University of Oregon, Eugene, OR, 97403, USA
| | - Sten Heinze
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH, 43210, USA
| | - James S Prell
- Department of Chemistry and Biochemistry and Materials Science Institute, University of Oregon, Eugene, OR, 97403, USA
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH, 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry and Resource for Native Mass Spectrometry Guided Structural Biology, Ohio State University, Columbus, OH, 43210, USA.
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7
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Biehn SE, Picarello DM, Pan X, Vachet RW, Lindert S. Accounting for Neighboring Residue Hydrophobicity in Diethylpyrocarbonate Labeling Mass Spectrometry Improves Rosetta Protein Structure Prediction. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2022; 33:584-591. [PMID: 35147431 PMCID: PMC8988852 DOI: 10.1021/jasms.1c00373] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Covalent labeling mass spectrometry allows for protein structure elucidation via covalent modification and identification of exposed residues. Diethylpyrocarbonate (DEPC) is a commonly used covalent labeling reagent that provides insight into structure through the labeling of lysine, histidine, serine, threonine, and tyrosine residues. We recently implemented a Rosetta algorithm that used binary DEPC labeling data to improve protein structure prediction efforts. In this work, we improved on our modeling efforts by accounting for the level of hydrophobicity of neighboring residues in the microenvironment of serine, threonine, and tyrosine residues to obtain a more accurate estimate of the hydrophobic neighbor count. This was incorporated into Rosetta functionality, along with considerations for solvent-exposed histidine and lysine residues. Overall, our new Rosetta score term successfully identified best scoring models with less than 2 Å root-mean-squared deviations (RMSDs) for five of the seven benchmark proteins tested. We additionally developed a confidence metric to measure prediction success for situations in which a native structure is unavailable.
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Affiliation(s)
- Sarah E Biehn
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, United States
| | - Danielle M Picarello
- Department of Bioengineering, Lehigh University, Bethlehem, Pennsylvania 18015, United States
- Rosetta Commons Research Experience for Undergraduates, Rosetta Commons, https://www.rosettacommons.org/about/intern
| | - Xiao Pan
- Department of Chemistry, University of Massachusetts, Amherst, Amherst, Massachusetts 01003, United States
| | - Richard W Vachet
- Department of Chemistry, University of Massachusetts, Amherst, Amherst, Massachusetts 01003, United States
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, United States
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9
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Abstract
Knowledge of protein structure is crucial to our understanding of biological function and is routinely used in drug discovery. High-resolution techniques to determine the three-dimensional atomic coordinates of proteins are available. However, such methods are frequently limited by experimental challenges such as sample quantity, target size, and efficiency. Structural mass spectrometry (MS) is a technique in which structural features of proteins are elucidated quickly and relatively easily. Computational techniques that convert sparse MS data into protein models that demonstrate agreement with the data are needed. This review features cutting-edge computational methods that predict protein structure from MS data such as chemical cross-linking, hydrogen-deuterium exchange, hydroxyl radical protein footprinting, limited proteolysis, ion mobility, and surface-induced dissociation. Additionally, we address future directions for protein structure prediction with sparse MS data. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Sarah E Biehn
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA;
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA;
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10
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Biehn SE, Limpikirati P, Vachet RW, Lindert S. Utilization of Hydrophobic Microenvironment Sensitivity in Diethylpyrocarbonate Labeling for Protein Structure Prediction. Anal Chem 2021; 93:8188-8195. [PMID: 34061512 DOI: 10.1021/acs.analchem.1c00395] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Diethylpyrocarbonate (DEPC) labeling analyzed with mass spectrometry can provide important insights into higher order protein structures. It has been previously shown that neighboring hydrophobic residues promote a local increase in DEPC concentration such that serine, threonine, and tyrosine residues are more likely to be labeled despite low solvent exposure. In this work, we developed a Rosetta algorithm that used the knowledge of labeled and unlabeled serine, threonine, and tyrosine residues and assessed their local hydrophobic environment to improve protein structure prediction. Additionally, DEPC-labeled histidine and lysine residues with higher relative solvent accessible surface area values (i.e., more exposed) were scored favorably. Application of our score term led to reductions of the root-mean-square deviations (RMSDs) of the lowest scoring models. Additionally, models that scored well tended to have lower RMSDs. A detailed tutorial describing our protocol and required command lines is included. Our work demonstrated the considerable potential of DEPC covalent labeling data to be used for accurate higher order structure determination.
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Affiliation(s)
- Sarah E Biehn
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, United States
| | - Patanachai Limpikirati
- Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok 10330, Thailand
| | - Richard W Vachet
- Department of Chemistry, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, United States
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11
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Richardson K, Langridge D, Dixit SM, Ruotolo BT. An Improved Calibration Approach for Traveling Wave Ion Mobility Spectrometry: Robust, High-Precision Collision Cross Sections. Anal Chem 2021; 93:3542-3550. [PMID: 33555172 DOI: 10.1021/acs.analchem.0c04948] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The combination of ion-mobility (IM) separation with mass spectrometry (MS) has impacted global measurement efforts in areas ranging from food analysis to drug discovery. Reasons for the broad adoption of IM-MS include its significantly increased peak capacity, duty-cycle, and ability to reconstruct fragmentation data in parallel, all of which greatly enable the analyses of complex mixtures. More fundamentally, however, measurements of ion-gas molecule collision cross sections (CCSs) are used to support compound identification and quantitation efforts as well as study the structures of large biomolecules. As the first commercialized form of IM-MS, Traveling Wave Ion Mobility (TWIM) devices are operated at low pressures (∼3 mbar) and voltages, are relatively short (∼25 cm), and separate ions on a timescale of tens of milliseconds. These qualities make TWIM ideally suited for hybridization with MS. Owing to the complicated motion of ions in TWIM devices, however, IM transit times must be calibrated to enable CCS measurements. Applicability of these calibrations has hitherto been restricted to primarily singly charged small molecules and some classes of large, multiply charged ions under a significantly narrower range of instrument conditions. Here, we introduce and extensively characterize a dramatically improved TWIM calibration methodology. Using over 2500 experimental TWIM data sets, covering ions that span over 3.5 orders of magnitude of molecular mass, we demonstrate robust calibrations for a significantly expanded range of instrument conditions, thereby opening up new analytical application areas and enabling the expansion of high-precision CCS measurements for both existing and next-generation TWIM instrumentation.
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Affiliation(s)
- K Richardson
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - D Langridge
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - S M Dixit
- Department of Chemistry, University of Michigan, University Ave., Ann Arbor, Michigan 48109, United States
| | - B T Ruotolo
- Department of Chemistry, University of Michigan, University Ave., Ann Arbor, Michigan 48109, United States
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12
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Zhang S, Li J, Xie C, Wu Q, Yu J, Tang K. Resolution enhancement of overlapping peaks of ion mobility spectrometry based on improved particle swarm optimization algorithm. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2021; 35:e8935. [PMID: 32929827 DOI: 10.1002/rcm.8935] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 08/12/2020] [Accepted: 08/26/2020] [Indexed: 06/11/2023]
Abstract
RATIONALE Ion mobility spectrometry (IMS) is a powerful analytical tool that has been widely applied in many fields. However, the limited structural resolution of IMS results in peak overlapping in the analysis of samples with similar structures. We propose a novel method, improved particle swarm optimization (IPSO), for the separation of IMS overlapping peaks. METHODS This method, which prevents local optimization, is used to identify the peak model coefficients of IMS. Moreover, we use the half-peak width characteristics of IMS to determine the particle position range, which eliminates impossible combinations of single peaks and reduces the difficulty of identification of coefficients. RESULTS During a comparison in performance between IPSO and the genetic algorithm (GA), the results show that the maximum separation error of IPSO is only 1.45%, while the error of the GA is up to 17.43%. Moreover, the time consumed by IPSO is 95% less than that of the GA, and IPSO has a greater robustness under the same separation error conditions. CONCLUSIONS The method proposed provides accurate analytical results in separating overlapping IMS peaks even in cases of severe overlaps, which greatly enhances the structural resolution of IMS.
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Affiliation(s)
- Shulei Zhang
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
| | - Junhui Li
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
| | - Chengyi Xie
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
| | - Qidi Wu
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
| | - Jiancheng Yu
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, 315211, China
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
| | - Keqi Tang
- Institute of Mass Spectrometry, Ningbo University, Ningbo, 315211, China
- School of Material Science and Chemical Engineering, Ningbo University, Ningbo, 315211, China
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13
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Seffernick JT, Lindert S. Hybrid methods for combined experimental and computational determination of protein structure. J Chem Phys 2020; 153:240901. [PMID: 33380110 PMCID: PMC7773420 DOI: 10.1063/5.0026025] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 11/10/2020] [Indexed: 02/04/2023] Open
Abstract
Knowledge of protein structure is paramount to the understanding of biological function, developing new therapeutics, and making detailed mechanistic hypotheses. Therefore, methods to accurately elucidate three-dimensional structures of proteins are in high demand. While there are a few experimental techniques that can routinely provide high-resolution structures, such as x-ray crystallography, nuclear magnetic resonance (NMR), and cryo-EM, which have been developed to determine the structures of proteins, these techniques each have shortcomings and thus cannot be used in all cases. However, additionally, a large number of experimental techniques that provide some structural information, but not enough to assign atomic positions with high certainty have been developed. These methods offer sparse experimental data, which can also be noisy and inaccurate in some instances. In cases where it is not possible to determine the structure of a protein experimentally, computational structure prediction methods can be used as an alternative. Although computational methods can be performed without any experimental data in a large number of studies, inclusion of sparse experimental data into these prediction methods has yielded significant improvement. In this Perspective, we cover many of the successes of integrative modeling, computational modeling with experimental data, specifically for protein folding, protein-protein docking, and molecular dynamics simulations. We describe methods that incorporate sparse data from cryo-EM, NMR, mass spectrometry, electron paramagnetic resonance, small-angle x-ray scattering, Förster resonance energy transfer, and genetic sequence covariation. Finally, we highlight some of the major challenges in the field as well as possible future directions.
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Affiliation(s)
- Justin T. Seffernick
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
| | - Steffen Lindert
- Department of Chemistry and Biochemistry, Ohio State University, Columbus, Ohio 43210, USA
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14
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Allison TM, Barran P, Benesch JLP, Cianferani S, Degiacomi MT, Gabelica V, Grandori R, Marklund EG, Menneteau T, Migas LG, Politis A, Sharon M, Sobott F, Thalassinos K. Software Requirements for the Analysis and Interpretation of Native Ion Mobility Mass Spectrometry Data. Anal Chem 2020; 92:10881-10890. [PMID: 32649184 DOI: 10.1021/acs.analchem.9b05792] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
The past few years have seen a dramatic increase in applications of native mass and ion mobility spectrometry, especially for the study of proteins and protein complexes. This increase has been catalyzed by the availability of commercial instrumentation capable of carrying out such analyses. As in most fields, however, the software to process the data generated from new instrumentation lags behind. Recently, a number of research groups have started addressing this by developing software, but further improvements are still required in order to realize the full potential of the data sets generated. In this perspective, we describe practical aspects as well as challenges in processing native mass spectrometry (MS) and ion mobility-MS data sets and provide a brief overview of currently available tools. We then set out our vision of future developments that would bring the community together and lead to the development of a common platform to expedite future computational developments, provide standardized processing approaches, and serve as a location for the deposition of data for this emerging field. This perspective has been written by members of the European Cooperation in Science and Technology Action on Native MS and Related Methods for Structural Biology (EU COST Action BM1403) as an introduction to the software tools available in this area. It is intended to serve as an overview for newcomers and to stimulate discussions in the community on further developments in this field, rather than being an in-depth review. Our complementary perspective (http://dx.doi.org/10.1021/acs.analchem.9b05791) focuses on computational approaches used in this field.
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Affiliation(s)
- Timothy M Allison
- School of Physical and Chemical Sciences, Biomolecular Interaction Centre, University of Canterbury, Christchurch 8140, New Zealand
| | - Perdita Barran
- Michael Barber Centre for Collaborative Mass Spectrometry, Manchester Institute of Biotechnology, School of Chemistry, University of Manchester, Manchester M1 7DN, United Kingdom
| | - Justin L P Benesch
- Department of Chemistry, Chemistry Research Laboratory, University of Oxford, South Parks Road, Oxford OX1 3TA, United Kingdom
| | - Sarah Cianferani
- Laboratoire de Spectrométrie de Masse BioOrganique (LSMBO), Université de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, France
| | - Matteo T Degiacomi
- Department of Chemistry, Chemistry Research Laboratory, University of Oxford, South Parks Road, Oxford OX1 3TA, United Kingdom.,Department of Physics, Durham University, South Road, Durham DH1 3LE, United Kingdom
| | - Valerie Gabelica
- University of Bordeaux, INSERM and CNRS, ARNA Laboratory, IECB site, 2 Rue Robert Escarpit, 33600 Pessac, France
| | - Rita Grandori
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, 20126 Milan, Italy
| | - Erik G Marklund
- Department of Chemistry - BMC, Uppsala University, Box 576, 75123 Uppsala, Sweden
| | - Thomas Menneteau
- Division of Biosciences, Institute of Structural and Molecular Biology, University College of London, Gower Street, London WC1E 6BT, United Kingdom
| | - Lukasz G Migas
- Michael Barber Centre for Collaborative Mass Spectrometry, Manchester Institute of Biotechnology, School of Chemistry, University of Manchester, Manchester M1 7DN, United Kingdom
| | - Argyris Politis
- Department of Chemistry, King's College London, 7 Trinity Street, London SE1 1DB, United Kingdom
| | - Michal Sharon
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Frank Sobott
- Biomolecular & Analytical Mass Spectrometry, Department of Chemistry, University of Antwerp, 2020 Antwerp, Belgium.,School of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, United Kingdom.,Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Konstantinos Thalassinos
- Division of Biosciences, Institute of Structural and Molecular Biology, University College of London, Gower Street, London WC1E 6BT, United Kingdom.,Department of Biological Sciences, Institute of Structural and Molecular Biology, Birkbeck, Malet Street, London WC1E 7HX, United Kingdom
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15
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Exploring the structure and dynamics of macromolecular complexes by native mass spectrometry. J Proteomics 2020; 222:103799. [DOI: 10.1016/j.jprot.2020.103799] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 03/23/2020] [Accepted: 04/25/2020] [Indexed: 12/15/2022]
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16
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Dixit SM, Richardson K, Langridge D, Giles K, Ruotolo BT. A Novel Ion Pseudo-trapping Phenomenon within Traveling Wave Ion Guides. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2020; 31:880-887. [PMID: 32134265 DOI: 10.1021/jasms.9b00095] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The widespread use of traveling wave ion mobility (TWIM) technology in fields such as omics and structural biology motivates efforts to deepen our understanding of ion transport within such devices. Here, we describe a new advancement in TWIM theory, where pseudo-trapping within TW ion guides is characterized in detail. During pseudo-trapping, ions with different mobilities can travel with the same mean velocity, leaving others within the same TWIM experiment to separate as normal. Furthermore, pseudo-trapping limits typical band broadening experienced by ions during TWIM, manifesting as peaks with apparently improved IM resolving power, but all ions that undergo pseudo trapping are unable to separate by IM. SIMION simulations show that ions become locked into a repeated pattern of motion with respect to the TW reference frame during pseudo-trapping. We developed a simplified model capable of reproducing TW pseudo-trapping and reproducing trends observed in experimental data. Our model and simulations suggest that pseudo-trapping occurs only during experiments performed under static TWIM conditions, to an extent that depends on the detailed shape of the traveling wave. We show that pseudo-trapping alters the ion transit times and can adversely affect calibrated CCS measurements. Finally, we provide recommendations for avoiding unintentional pseudo-trapping in TWIM in order to obtain optimal separations and CCS determinations.
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Affiliation(s)
- Sugyan M Dixit
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
| | - Keith Richardson
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - David Langridge
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - Kevin Giles
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, U.K
| | - Brandon T Ruotolo
- Department of Chemistry, University of Michigan, 930 North University Avenue, Ann Arbor, Michigan 48109, United States
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17
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Rout MP, Sali A. Principles for Integrative Structural Biology Studies. Cell 2020; 177:1384-1403. [PMID: 31150619 DOI: 10.1016/j.cell.2019.05.016] [Citation(s) in RCA: 177] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 04/24/2019] [Accepted: 05/06/2019] [Indexed: 12/22/2022]
Abstract
Integrative structure determination is a powerful approach to modeling the structures of biological systems based on data produced by multiple experimental and theoretical methods, with implications for our understanding of cellular biology and drug discovery. This Primer introduces the theory and methods of integrative approaches, emphasizing the kinds of data that can be effectively included in developing models and using the nuclear pore complex as an example to illustrate the practice and challenges involved. These guidelines are intended to aid the researcher in understanding and applying integrative structural methods to systems of their interest and thus take advantage of this rapidly evolving field.
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Affiliation(s)
- Michael P Rout
- Laboratory of Cellular and Structural Biology, The Rockefeller University, New York, NY 10065, USA.
| | - Andrej Sali
- Department of Bioengineering and Therapeutic Sciences, Department of Pharmaceutical Chemistry, California Institute for Quantitative Biosciences, Byers Hall, 1700 4th Street, Suite 503B, University of California, San Francisco, San Francisco, CA 94158, USA.
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18
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Abstract
Maturation of urease involves post-translational insertion of nickel ions to form an active site with a carbamylated lysine ligand and is assisted by urease accessory proteins UreD, UreE, UreF and UreG. Here, we review our current understandings on how these urease accessory proteins facilitate the urease maturation. The urease maturation pathway involves the transfer of Ni2+ from UreE → UreG → UreF/UreD → urease. To avoid the release of the toxic metal to the cytoplasm, Ni2+ is transferred from one urease accessory protein to another through specific protein–protein interactions. One central theme depicts the role of guanosine triphosphate (GTP) binding/hydrolysis in regulating the binding/release of nickel ions and the formation of the protein complexes. The urease and [NiFe]-hydrogenase maturation pathways cross-talk with each other as UreE receives Ni2+ from hydrogenase maturation factor HypA. Finally, the druggability of the urease maturation pathway is reviewed.
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19
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Wang H, Eschweiler J, Cui W, Zhang H, Frieden C, Ruotolo BT, Gross ML. Native Mass Spectrometry, Ion Mobility, Electron-Capture Dissociation, and Modeling Provide Structural Information for Gas-Phase Apolipoprotein E Oligomers. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2019; 30:876-885. [PMID: 30887458 PMCID: PMC6504607 DOI: 10.1007/s13361-019-02148-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 02/04/2019] [Accepted: 02/04/2019] [Indexed: 05/09/2023]
Abstract
Apolipoprotein E (apoE) is an essential protein in lipid and cholesterol metabolism. Although the three common isoforms in humans differ only at two sites, their consequences in Alzheimer's disease (AD) are dramatically different: only the ε4 allele is a major genetic risk factor for late-onset Alzheimer's disease. The isoforms exist as a mixture of oligomers, primarily tetramer, at low μM concentrations in a lipid-free environment. This self-association is involved in equilibrium with the lipid-free state, and the oligomerization interface overlaps with the lipid-binding region. Elucidation of apoE wild-type (WT) structures at an oligomeric state, however, has not yet been achieved. To address this need, we used native electrospray ionization and mass spectrometry (native MS) coupled with ion mobility (IM) to examine the monomer and tetramer of the three WT isoforms. Although collision-induced unfolding (CIU) cannot distinguish the WT isoforms, the monomeric mutant (MM) of apoE3 shows higher stability when submitted to CIU than the WT monomer. From ion-mobility measurements, we obtained the collision cross section and built a coarse-grained model for the tetramer. Application of electron-capture dissociation (ECD) to the tetramer causes unfolding starting from the C-terminal domain, in good agreement with solution denaturation data, and provides additional support for the C4 symmetry structure of the tetramer.
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Affiliation(s)
- Hanliu Wang
- Department of Chemistry, Washington University, St. Louis, MO, 63130, USA
- Analytical Research and Development, Pfizer Inc., Chesterfield, MO, 63017, USA
| | - Joseph Eschweiler
- Drug Product Development, Abbvie Inc., North Chicago, IL, 60064, USA
- Department of Chemistry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Weidong Cui
- Department of Chemistry, Washington University, St. Louis, MO, 63130, USA
- Pivotal Attribute Sciences, Amgen Inc., Cambridge, MA, 02142, USA
| | - Hao Zhang
- Department of Chemistry, Washington University, St. Louis, MO, 63130, USA
- Pivotal Attribute Sciences, Amgen Inc., Cambridge, MA, 02142, USA
| | - Carl Frieden
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Brandon T Ruotolo
- Department of Chemistry, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Michael L Gross
- Department of Chemistry, Washington University, St. Louis, MO, 63130, USA.
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20
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Marklund EG, Benesch JL. Weighing-up protein dynamics: the combination of native mass spectrometry and molecular dynamics simulations. Curr Opin Struct Biol 2019; 54:50-58. [PMID: 30743182 DOI: 10.1016/j.sbi.2018.12.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 12/22/2018] [Accepted: 12/27/2018] [Indexed: 12/21/2022]
Abstract
Structural dynamics underpin biological function at the molecular level, yet many biophysical and structural biology approaches give only a static or averaged view of proteins. Native mass spectrometry yields spectra of the many states and interactions in the structural ensemble, but its spatial resolution is limited. Conversely, molecular dynamics simulations are innately high-resolution, but have a limited capacity for exploring all structural possibilities. The two techniques hence differ fundamentally in the information they provide, returning data that reflect different length scales and time scales, making them natural bedfellows. Here we discuss how the combination of native mass spectrometry with molecular dynamics simulations is enabling unprecedented insights into a range of biological questions by interrogating the motions of proteins, their assemblies, and interactions.
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Affiliation(s)
- Erik G Marklund
- Department of Chemistry - BMC, Uppsala University, Box 576, 75 123, Uppsala, Sweden.
| | - Justin Lp Benesch
- Department of Chemistry, Chemistry Research Laboratory, University of Oxford, Mansfield Road, Oxford, OX1 3TA, United Kingdom.
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21
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Structural mass spectrometry comes of age: new insight into protein structure, function and interactions. Biochem Soc Trans 2019; 47:317-327. [DOI: 10.1042/bst20180356] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 11/27/2018] [Accepted: 12/04/2018] [Indexed: 12/15/2022]
Abstract
Abstract
Mass spectrometry (MS) provides an impressive array of information about the structure, function and interactions of proteins. In recent years, many new developments have been in the field of native MS and these exemplify a new coming of age of this field. In this mini review, we connect the latest methodological and instrumental developments in native MS to the new insights these have enabled. We highlight the prominence of an increasingly common strategy of using hybrid approaches, where multiple MS-based techniques are used in combination, and integrative approaches, where MS is used alongside other techniques such as ion-mobility spectrometry. We also review how the emergence of a native top-down approach, which combines native MS with top-down proteomics into a single experiment, is the pièce de résistance of structural mass spectrometry's coming of age. Finally, we outline key developments that have enabled membrane protein native MS to shift from being extremely challenging to routine, and how this technique is uncovering inaccessible details of membrane protein–lipid interactions.
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22
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Hansen K, Lau AM, Giles K, McDonnell JM, Struwe WB, Sutton BJ, Politis A. A Mass-Spectrometry-Based Modelling Workflow for Accurate Prediction of IgG Antibody Conformations in the Gas Phase. Angew Chem Int Ed Engl 2018; 57:17194-17199. [PMID: 30408305 PMCID: PMC6392142 DOI: 10.1002/anie.201812018] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Indexed: 11/09/2022]
Abstract
Immunoglobulins are biomolecules involved in defence against foreign substances. Flexibility is key to their functional properties in relation to antigen binding and receptor interactions. We have developed an integrative strategy combining ion mobility mass spectrometry (IM-MS) with molecular modelling to study the conformational dynamics of human IgG antibodies. Predictive models of all four human IgG subclasses were assembled and their dynamics sampled in the transition from extended to collapsed state during IM-MS. Our data imply that this collapse of IgG antibodies is related to their intrinsic structural features, including Fab arm flexibility, collapse towards the Fc region, and the length of their hinge regions. The workflow presented here provides an accurate structural representation in good agreement with the observed collision cross section for these flexible IgG molecules. These results have implications for studying other nonglobular flexible proteins.
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Affiliation(s)
- Kjetil Hansen
- Department of ChemistryKing's College London7 Trinity StreetLondonSE1 1DBUK
| | - Andy M. Lau
- Department of ChemistryKing's College London7 Trinity StreetLondonSE1 1DBUK
| | | | | | | | - Brian J. Sutton
- Randall Centre for Cell and Molecular BiophysicsKing's College LondonUK
| | - Argyris Politis
- Department of ChemistryKing's College London7 Trinity StreetLondonSE1 1DBUK
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23
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Hansen K, Lau AM, Giles K, McDonnell JM, Struwe WB, Sutton BJ, Politis A. A Mass‐Spectrometry‐Based Modelling Workflow for Accurate Prediction of IgG Antibody Conformations in the Gas Phase. Angew Chem Int Ed Engl 2018. [DOI: 10.1002/ange.201812018] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Kjetil Hansen
- Department of Chemistry King's College London 7 Trinity Street London SE1 1DB UK
| | - Andy M. Lau
- Department of Chemistry King's College London 7 Trinity Street London SE1 1DB UK
| | - Kevin Giles
- Waters Corp. Stamford Road Wilmslow SK9 4AX UK
| | - James M. McDonnell
- Randall Centre for Cell and Molecular Biophysics King's College London UK
| | | | - Brian J. Sutton
- Randall Centre for Cell and Molecular Biophysics King's College London UK
| | - Argyris Politis
- Department of Chemistry King's College London 7 Trinity Street London SE1 1DB UK
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