A novel projection approximation algorithm for the fast and accurate computation of molecular collision cross sections (II). Model parameterization and definition of empirical shape factors for proteins

Bleiholder, Christian; Contreras, Stephanie; Thanh, D.; Bowers, Michael T.

doi:10.1016/j.ijms.2012.08.027

Cited by 72 publications

(110 citation statements)

References 29 publications

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“…After that, the theoretical cross sections were computed using the projected superposition approximation (PSA) method available at (http://luschka. bic.ucsb.edu:8080/WebPSA/index.jsp) and the average values were reported [63,64].…”

Section: Molecular Dynamicsmentioning

confidence: 99%

Human Islet Amyloid Polypeptide N-Terminus Fragment Self-Assembly: Effect of Conserved Disulfide Bond on Aggregation Propensity

Ilitchev

Giammona

Thanh

et al. 2016

J. Am. Soc. Mass Spectrom.

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Abstract. Amyloid formation by human islet amyloid polypeptide (hIAPP) has long been implicated in the pathogeny of type 2 diabetes mellitus (T2DM) and failure of islet transplants, but the mechanism of IAPP self-assembly is still unclear. Numerous fragments of hIAPP are capable of self-association into oligomeric aggregates, both amyloid and non-amyloid in structure. The N-terminal region of IAPP contains a conserved disulfide bond between cysteines at position 2 and 7, which is important to hIAPP's in vivo function and may play a role in in vitro aggregation. The importance of the disulfide bond in this region was probed using a combination of ion mobilitybased mass spectrometry experiments, molecular dynamics simulations, and highresolution atomic force microscopy imaging on the wildtype 1-8 hIAPP fragment, a reduced fragment with no disulfide bond, and a fragment with both cysteines at positions 2 and 7 mutated to serine. The results indicate the wildtype fragment aggregates by a different pathway than either comparison peptide and that the intact disulfide bond may be protective against aggregation due to a reduction of interpeptide hydrogen bonding.

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Section: Molecular Dynamicsmentioning

confidence: 99%

Human Islet Amyloid Polypeptide N-Terminus Fragment Self-Assembly: Effect of Conserved Disulfide Bond on Aggregation Propensity

Ilitchev

Giammona

Thanh

et al. 2016

J. Am. Soc. Mass Spectrom.

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“…Besides, new computational methods are still being developed to provide Ω CALC in a faster and/or more accurate way and in different gases. Among these methods are the projection superposition approximation (PSA) described below, [95][96][97][98] the diffuse hard spheres scattering and diffuse trajectory models [99] and the scattering on electron density isosurfaces.…”

Section: Gas Phase Molecular Dynamics Simulationmentioning

confidence: 99%

“…Bower et al developed the PSA model. [95][96][97][98] PSA is based on the PA concept, improved by taking into account (1) the cooperative size effect by superposition of diffuse atomic contributions and (2) the presence of cavities using a shape factor ρ. This algorithm, whose atomic parameters were obtained for H, C, N, O, Na and K based on experimental cross section measurements, is made available to the community as a web service [104] to compute Ω CALC in both He and N 2 .…”

Section: Projection Superposition Approximationmentioning

confidence: 99%

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

D’Atri¹,

Porrini²,

Rosu³

et al. 2015

J. Mass Spectrom.

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Ion mobility spectrometry experiments allow the mass spectrometrist to determine an ion's rotationally averaged collision cross section Ω EXP . Molecular modelling is used to visualize what ion three-dimensional structure(s) is(are) compatible with the experiment. The collision cross sections of candidate molecular models have to be calculated, and the resulting Ω CALC are compared with the experimental data. Researchers who want to apply this strategy to a new type of molecule face many questions: (1) What experimental error is associated with Ω EXP determination, and how to estimate it (in particular when using a calibration for traveling wave ion guides)? (2) How to generate plausible 3D models in the gas phase? (3) Different collision cross section calculation models exist, which have been developed for other analytes than mine. Which one(s) can I apply to my systems? To apply ion mobility spectrometry to nucleic acid structural characterization, we explored each of these questions using a rigid structure which we know is preserved in the gas phase: the tetramolecular G-quadruplex [dTGGGGT] 4 , and we will present these detailed investigation in this tutorial. Additional supporting information may be found in the online version of this article at the publisher's web site.Keywords: ion mobility spectrometry; collision cross section; structure; nucleic acids; simulations; molecular modeling; gas-phase ion structure IntroductionElectrospray mass spectrometry (ESI-MS) in native conditions can preserve the structures of biomolecules and separate them according to their mass-to-charge ratios. [1,2] Ion mobility spectrometry (IMS) separates ions according to their size-to-charge ratios in the gas-phase. [3][4][5][6] Size is related to the mass (or number of atoms) and to the three-dimensional shape of a molecule. Therefore, by hyphenating IMS to mass spectrometry (IM-MS), one can sort ions according to both mass and shape. The challenge is to decipher structural information from ion mobility experiments. [7][8][9] The physical quantity characterizing the shape is the collision cross section (CCS), [10] which will be introduced in more detail in the Section on Ion mobility and collision cross sections. The present tutorial clarifies how to interpret CCS measurements in terms of three-dimensional structure for ions larger than 100 atoms extracted from the solution by electrospray ionization (ESI). The gold standard is to match CCSs experimentally obtained from IMS with CCSs calculated for modelling three-dimensional structures of the ion of interest. We will discuss the factors that can affect the precision (reproducibility) and accuracy in both the measurements and the calculations. Understanding each of these factors is crucial to interpret quantitative matches confidently and assess the meaningfulness of structural assignments.On the experimental side, we will describe the determination of CCS from traveling wave ion mobility spectrometers and from drift tube ion mobility spectrometers, with example data recorde...

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“…A priori assignment of IM CCSs is a daunting task, viz., currently there exist no guiding principles for correlating the measured CCS for an ion to specific 3-D shapes. In some cases it is possible to correlate CCS with 3-D shapes derived from other experimental measurements, specifically XRD or NMR [36][37][38][39] ; however, MD simulations provide a broader sampling of candidate conformations of the ions whose CCS values can be calculated by using MOBCAL 40 (or similar methods) 36,41 . The "theoretical" CCS obtained using MD simulations and MOBCAL can then be compared to the experimental CCS.…”

Section: Ms-based Approaches For Studies Of Peptide/protein Conformatmentioning

confidence: 99%

Effects of charge states, charge sites and side chain interactions on conformational preferences of a series of model peptide ions

Xiao

Pérez

Russell

2015

Analyst

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A novel projection approximation algorithm for the fast and accurate computation of molecular collision cross sections (II). Model parameterization and definition of empirical shape factors for proteins

Cited by 72 publications

References 29 publications

Human Islet Amyloid Polypeptide N-Terminus Fragment Self-Assembly: Effect of Conserved Disulfide Bond on Aggregation Propensity

Human Islet Amyloid Polypeptide N-Terminus Fragment Self-Assembly: Effect of Conserved Disulfide Bond on Aggregation Propensity

Linking molecular models with ion mobility experiments. Illustration with a rigid nucleic acid structure

Effects of charge states, charge sites and side chain interactions on conformational preferences of a series of model peptide ions

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