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ABSTRACT: The advent of parallel computing technology and low-cost computing hardware has facilitated the adoption of high-performance
computing tools for the analysis of sedimentation data. Over the past 15years, we have developed the UltraScan software (Demeler
et al., http://ultrascan.uthscsa.edu
) to support sedimentation analysis, experimental design, and data management. We describe here recent extensions and advances
in methodology that have been adapted in UltraScan. High-performance computing methods implemented on parallel supercomputers
utilizing grid computing technology are used to analyze sedimentation experiments at much higher resolution than was previously
possible. We discuss the implementation of parallel computing in three novel algorithms used in UltraScan for modeling of
sedimentation velocity experiments and provide guidelines for effective data analysis.
Colloid and Polymer Science 04/2012; 286(2):139-148. · 2.33 Impact Factor
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ABSTRACT: High resolution analysis approaches for sedimentation experiments have recently been developed that promise to provide a detailed
description of heterogeneous samples by identifying both shape and molecular weight distributions. In this study, we describe
the effect experimental noise has on the accuracy and precision of such determinations and offer a stochastic Monte Carlo
approach, which reliably quantifies the effect of noise by determining the confidence intervals for the parameters that describe
each solute. As a result, we can now predict reliable confidence intervals for determined parameters. We also explore the
effect of various experimental parameters on the confidence intervals and provide suggestions for improving the statistics
by applying a few practical rules for the design of sedimentation experiments.
Colloid and Polymer Science 04/2012; 286(2):129-137. · 2.33 Impact Factor
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ABSTRACT: We compare here the utility of sedimentation velocity (SV) to sedimentation equilibrium (SE) analysis for the characterization of reversible systems. Genetic algorithm optimization in UltraScan is used to optimize the model and to obtain solution properties of all components present in the system. We apply our method to synthetic and experimental data, and suggest limits for the accessible kinetic range. We conclude that equilibrium constants obtained from SV and SE analysis are equivalent, but that SV experiments provide better confidence for the K(d), can better account for the presence of contaminants and provide additional information including rate constants and shape parameters.
Macromolecular Bioscience 07/2010; 10(7):775-82. · 3.89 Impact Factor
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ABSTRACT: The US-SOMO suite provides a flexible interface for accurately computing solution parameters from 3D structures of biomacromolecules through bead-modeling approaches. We present an extended analysis of the influence of accessible surface area screening, overlap reduction routines, and approximations for non-coded residues and missing atoms on the computed parameters for models built by the residue-to-bead direct correspondence and the cubic grid methods. Importantly, by taking the theoretical hydration into account at the atomic level, the performance of the grid-type models becomes comparable or exceeds that of the corresponding hydrated residue-to-bead models.
Macromolecular Bioscience 07/2010; 10(7):746-53. · 3.89 Impact Factor
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Helmut Cölfen,
Thomas M Laue,
Wendel Wohlleben,
Kristian Schilling,
Engin Karabudak,
Bradley W Langhorst, Emre Brookes,
Bruce Dubbs,
Dan Zollars,
Mattia Rocco,
Borries Demeler
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ABSTRACT: Progress in analytical ultracentrifugation (AUC) has been hindered by obstructions to hardware innovation and by software incompatibility. In this paper, we announce and outline the Open AUC Project. The goals of the Open AUC Project are to stimulate AUC innovation by improving instrumentation, detectors, acquisition and analysis software, and collaborative tools. These improvements are needed for the next generation of AUC-based research. The Open AUC Project combines on-going work from several different groups. A new base instrument is described, one that is designed from the ground up to be an analytical ultracentrifuge. This machine offers an open architecture, hardware standards, and application programming interfaces for detector developers. All software will use the GNU Public License to assure that intellectual property is available in open source format. The Open AUC strategy facilitates collaborations, encourages sharing, and eliminates the chronic impediments that have plagued AUC innovation for the last 20 years. This ultracentrifuge will be equipped with multiple and interchangeable optical tracks so that state-of-the-art electronics and improved detectors will be available for a variety of optical systems. The instrument will be complemented by a new rotor, enhanced data acquisition and analysis software, as well as collaboration software. Described here are the instrument, the modular software components, and a standardized database that will encourage and ease integration of data analysis and interpretation software.
Biophysics of Structure and Mechanism 04/2009; 39(3):347-59. · 2.44 Impact Factor
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ABSTRACT: The interpretation of solution hydrodynamic data in terms of macromolecular structural parameters is not a straightforward task. Over the years, several approaches have been developed to cope with this problem, the most widely used being bead modeling in various flavors. We report here the implementation of the SOMO (SOlution MOdeller; Rai et al. in Structure 13:723-734, 2005) bead modeling suite within one of the most widely used analytical ultracentrifugation data analysis software packages, UltraScan (Demeler in Modern analytical ultracentrifugation: techniques and methods, Royal Society of Chemistry, UK, 2005). The US-SOMO version is now under complete graphical interface control, and has been freed from several constraints present in the original implementation. In the direct beads-per-atoms method, virtually any kind of residue as defined in the Protein Data Bank (e.g., proteins, nucleic acids, carbohydrates, prosthetic groups, detergents, etc.) can be now represented with beads whose number, size and position are all defined in user-editable tables. For large structures, a cubic grid method based on the original AtoB program (Byron in Biophys J 72:408-415, 1997) can be applied either directly on the atomic structure, or on a previously generated bead model. The hydrodynamic parameters are then computed in the rigid-body approximation. An extensive set of tests was conducted to further validate the method, and the results are presented here. Owing to its accuracy, speed, and versatility, US-SOMO should allow to fully take advantage of the potential of solution hydrodynamics as a complement to higher resolution techniques in biomacromolecular modeling.
Biophysics of Structure and Mechanism 03/2009; 39(3):423-35. · 2.44 Impact Factor
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ABSTRACT: We report a model-independent analysis approach for fitting sedimentation velocity data which permits simultaneous determination of shape and molecular weight distributions for mono- and polydisperse solutions of macromolecules. Our approach allows for heterogeneity in the frictional domain, providing a more faithful description of the experimental data for cases where frictional ratios are not identical for all components. Because of increased accuracy in the frictional properties of each component, our method also provides more reliable molecular weight distributions in the general case. The method is based on a fine grained two-dimensional grid search over s and f/f (0), where the grid is a linear combination of whole boundary models represented by finite element solutions of the Lamm equation with sedimentation and diffusion parameters corresponding to the grid points. A Monte Carlo approach is used to characterize confidence limits for the determined solutes. Computational algorithms addressing the very large memory needs for a fine grained search are discussed. The method is suitable for globally fitting multi-speed experiments, and constraints based on prior knowledge about the experimental system can be imposed. Time- and radially invariant noise can be eliminated. Serial and parallel implementations of the method are presented. We demonstrate with simulated and experimental data of known composition that our method provides superior accuracy and lower variance fits to experimental data compared to other methods in use today, and show that it can be used to identify modes of aggregation and slow polymerization.
Biophysics of Structure and Mechanism 03/2009; 39(3):405-14. · 2.44 Impact Factor
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ABSTRACT: A computational approach for fitting sedimentation velocity experiments from an analytical ultracentrifuge in a model-independent fashion is presented. This chapter offers a recipe for obtaining high-resolution information for both the shape and the molecular weight distributions of complex mixtures that are heterogeneous in shape and molecular weight and provides suggestions for experimental design to optimize information content. A combination of three methods is used to find the solution most parsimonious in parameters and to verify the statistical confidence intervals of the determined parameters. A supercomputer implementation with a MySQL database back end is integrated into the UltraScan analysis software. The UltraScan LIMS Web portal is used to perform the calculations through a Web interface. The performance and limitations of the method when employed for the analysis of complex mixtures are demonstrated using both simulated data and experimental data characterizing amyloid aggregation.
Methods in enzymology 02/2009; 454:87-113. · 1.90 Impact Factor
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ABSTRACT: Sedimentation experiments can provide alarge amount of information about the composition
of asample, and the properties of each component contained in the sample. To extract the details
of the composition and the component properties, experimental data can be described by amathematical
model, which can then be fitted to the data. If the model is nonlinear in the parameters, the parameter
adjustments are typically performed by anonlinear least squares optimization algorithm. For
models with many parameters, the error surface of this optimization often becomes very complex, the
parameter solution tends to become trapped in alocal minimum and the method may fail to converge.
We introduce here astochastic optimization approach for sedimentation velocity experiments utilizing
genetic algorithms which is immune to such convergence traps and allows high-resolution fitting of
nonlinear multi-component sedimentation models to yield distributions for sedimentation and diffusion
coefficients, molecular weights, and partial concentrations.
02/2006: pages 33-40;
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ABSTRACT: A computational approach for fitting sedimentation velocity experiments from an analytical ultracentrifuge in a model-independent fashion is presented. This chapter offers a recipe for obtaining high-resolution information for both the shape and the molecular weight distributions of complex mixtures that are heterogeneous in shape and molecular weight and provides suggestions for experimental design to optimize information content. A combination of three methods is used to find the solution most parsimonious in parameters and to verify the statistical confidence intervals of the determined parameters. A supercomputer implementation with a MySQL database back end is integrated into the UltraScan analysis software. The UltraScan LIMS Web portal is used to perform the calculations through a Web interface. The performance and limitations of the method when employed for the analysis of complex mixtures are demonstrated using both simulated data and experimental data characterizing amyloid aggregation.
Methods in Enzymology.
