A Parametrically Constrained Optimization Method for Fitting Sedimentation Velocity Experiments

Gorbet, Gary E.; Devlin, Taylor; Uribe, Blanca I. Hernandez; Demeler, Aysha K.; Lindsey, Zachary L.; Ganji, S.R Seyedalizadeh; Breton, Sabrah; Weise-Cross, Laura; Lafer, Eileen M.; Brookes, Emre; Demeler, Borries

doi:10.1016/j.bpj.2014.02.022

Cited by 60 publications

(59 citation statements)

References 21 publications

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“…This includes not only the model free approaches, such as the van Holde-Weischet or the dc/dt analysis, 19,35 but also high-performance analysis including correction for diffusion such as the c(s) analysis in Sedfit or the 2DSA and PCSA models implemented in Ultrascan3. [36][37][38][39] This will provide the opportunity to take into account the effect of diffusion where it is significant and will in turn allow for the simultaneous analysis of the size, density and shape of NPs using AC. Software performing Mie correction is currently under development.…”

Section: Discussionmentioning

confidence: 99%

New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

et al. 2015

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Analytical centrifugation (AC) is a powerful technique for the characterisation of nanoparticles in colloidal systems. As a direct and absolute technique it requires no calibration or measurements of standards. Moreover, it offers simple experimental design and handling, high sample throughput as well as moderate investment costs. However, the full potential of AC for nanoparticle size analysis requires the development of powerful data analysis techniques. In this study we show how the application of direct boundary models to AC data opens up new possibilities in particle characterisation. An accurate analysis method, successfully applied to sedimentation data obtained by analytical ultracentrifugation (AUC) in the past, was used for the first time in analysing AC data. Unlike traditional data evaluation routines for AC using a designated number of radial positions or scans, direct boundary models consider the complete sedimentation boundary, which results in significantly better statistics. We demonstrate that meniscus fitting, as well as the correction of radius and time invariant noise significantly improves the signal-to-noise ratio and prevents the occurrence of false positives due to optical artefacts. Moreover, hydrodynamic non-ideality can be assessed by the residuals obtained from the analysis. The sedimentation coefficient distributions obtained by AC are in excellent agreement with the results from AUC. Brownian dynamics simulations were used to generate numerical sedimentation data to study the influence of diffusion on the obtained distributions.Our approach is further validated using polystyrene and silica nanoparticles. In particular, we demonstrate the strength of AC for analysing multimodal distributions by means of gold nanoparticles.

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Section: Discussionmentioning

confidence: 99%

New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

et al. 2015

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“…Datasets were initially fitted to a single, ideal species model using Ultrascan. 43 The partial specific volume for each of the various peptides and the solvent density was calculated using Sednterp. 44 Circular Dichroism CD spectra were obtained using a JASCO J-810 spectropolarimeter fitted with a Peltier temperature controller.…”

Section: Sedimentation-equilibrium Experiments By Analytical Ultracenmentioning

confidence: 99%

N@a and N@d: Oligomer and Partner Specification by Asparagine in Coiled-Coil Interfaces

Fletcher¹,

Bartlett²,

Boyle³

et al. 2017

ACS Chem. Biol.

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The α-helical coiled coil is one of the best-studied protein–protein interaction motifs. As a result, sequence-to-structure relationships are available for the prediction of natural coiled-coil sequences and the de novo design of new ones. However, coiled coils adopt a wide range of oligomeric states and topologies, and our understanding of the specification of these and the discrimination between them remains incomplete. Gaps in our knowledge assume more importance as coiled coils are used increasingly to construct biomimetic systems of higher complexity; for this, coiled-coil components need to be robust, orthogonal, and transferable between contexts. Here, we explore how the polar side chain asparagine (Asn, N) is tolerated within otherwise hydrophobic helix–helix interfaces of coiled coils. The long-held view is that Asn placed at certain sites of the coiled-coil sequence repeat selects one oligomer state over others, which is rationalized by the ability of the side chain to make hydrogen bonds, or interactions with chelated ions within the coiled-coil interior of the favored state. We test this with experiments on de novo peptide sequences traditionally considered as directing parallel dimers and trimers, and more widely through bioinformatics analysis of natural coiled-coil sequences and structures. We find that when located centrally, rather than near the termini of such coiled-coil sequences, Asn does exert the anticipated oligomer-specifying influence. However, outside of these bounds, Asn is observed less frequently in the natural sequences, and the synthetic peptides are hyperthermostable and lose oligomer-state specificity. These findings highlight that not all regions of coiled-coil repeat sequences are equivalent, and that care is needed when designing coiled-coil interfaces.

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“…For the 2 nd order power law this results in K 3 combinations. For a detailed description of the PCSA algorithm the reader is referred to the work of Gorbet et al 11 Briefly, the PCSA discretizes s and D along the parametric curves and fits the amplitudes of individual terms in the linear combinations of the corresponding Lamm equation solutions to the experimental data. The parametric curve giving rise to the lowest root mean square deviation (RMSD) will then represent the best parameterization for the underlying distribution.…”

Section: Theorymentioning

confidence: 99%

“…High performance techniques such as the two-dimensional spectrum analysis (2DSA) and parametrically constrained spectrum analysis (PCSA) implemented in the UltraScan3 software or the c(s, D) analysis implemented in Sedfit offer the possibility to address polydispersity in more than one dimension. 9–11 This allows for the simultaneous analysis of size and shape anisotropy of macromolecules and NPs under the condition that the sedimentation and diffusion information is sufficiently represented in the data. Recent developments in data evaluation considerably widened the possibilities of NP analysis.…”

Section: Introductionmentioning

confidence: 99%

2D analysis of polydisperse core–shell nanoparticles using analytical ultracentrifugation

Walter

Gorbet

Akdas

et al. 2017

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Accurate knowledge of size, density and composition of nanoparticles (NPs) is of major importance for their applications. In this work the hydrodynamic characterization of polydisperse core-shell NPs by means of analytical ultracentrifugation (AUC) is addressed. AUC is one of the most accurate techniques for the characterization of NPs in the liquid phase because it can resolve particle size distributions (PSDs) with unrivaled resolution and detail. Small NPs have to be considered as core-shell systems when dispersed in a liquid since a solvation layer and stabilizer shell will significantly contribute to the particle’s hydrodynamic diameter and effective density. AUC measures the sedimentation and diffusion transport of the analytes, which are affected by the core-shell compositional properties. This work demonstrates that polydisperse and thus widely distributed NPs pose significant challenges for current state-of-the-art data evaluation methods. Existing methods either have insufficient resolution or do not correctly reproduce the core-shell properties. First, we investigate the performance of different data evaluation models by means of simulated data. Then, we propose a new methodology to address the core-shell properties of NPs. This method is based on the parametrically constrained spectrum analysis and offers complete access to the size and effective density of polydisperse NPs. Our study is complemented using experimental data derived for ZnO and CuInS2 NPs, which do not have a monodisperse PSD. For the first time, the size and effective density of such structures can be resolved with high resolution by means of a two-dimensional AUC analysis approach.

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A Parametrically Constrained Optimization Method for Fitting Sedimentation Velocity Experiments

Cited by 60 publications

References 21 publications

New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

New possibilities of accurate particle characterisation by applying direct boundary models to analytical centrifugation

N@a and N@d: Oligomer and Partner Specification by Asparagine in Coiled-Coil Interfaces

2D analysis of polydisperse core–shell nanoparticles using analytical ultracentrifugation

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