Sequence Reversal Prevents Chain Collapse and Yields Heat-Sensitive Intrinsic Disorder.

Sequence patterns of charge, hydrophobicity, hydrogen bonding, and other amino acid physicochemical properties contribute to mechanisms of protein folding, but how sequence composition and patterns influence the conformational dynamics of the denatured state ensemble is not fully understood. To investigate structure-sequence relationships in the denatured state, we reversed the sequence of staphylococcal nuclease and characterized its structure, thermodynamic character, and hydrodynamic radius using circular dichroism spectroscopy, dynamic light scattering, analytical ultracentrifugation, and size-exclusion chromatography as a function of temperature. The macromolecular size of "Retro-nuclease" is highly expanded in solution with characteristics similar to biological intrinsically disordered proteins. In contradistinction to a disordered state, Retro-nuclease exhibits a broad sigmoid transition of its hydrodynamic dimensions as temperature is increased, indicating a thermodynamically controlled compaction. Counterintuitively, the magnitude of these temperature-induced hydrodynamic changes exceed that observed from thermal denaturation of folded unaltered staphylococcal nuclease. Undetectable by calorimetry and intrinsic tryptophan fluorescence, the lack of heat capacity or fluorescence changes throughout the thermal transition indicate canonical hydrophobic collapse did not drive the Retro-nuclease structural transitions. Temperature-dependent circular dichroism spectroscopy performed on Retro-nuclease and computer simulations correlate to temperature sensitivity in the intrinsic sampling of backbone conformations for polyproline II and α-helix. The experimental results indicate a role for sequence direction in mediating the collapse of the polypeptide chain, whereas the simulation trends illustrate the generality of the observed heat effects on disordered protein structure.

Next-Generation AUC: Analysis of Multiwavelength Analytical Ultracentrifugation Data.

We describe important advances in methodologies for the analysis of multiwavelength data. In contrast to the Beckman-Coulter XL-A/I ultraviolet-visible light detector, multiwavelength detection is able to simultaneously collect sedimentation data for a large wavelength range in a single experiment. The additional dimension increases the data density by orders of magnitude, posing new challenges for data analysis and management. The additional data not only improve the statistics of the measurement but also provide new information for spectral characterization, which complements the hydrodynamic information. New data analysis and management approaches were integrated into the UltraScan software to address these challenges. In this chapter, we describe the enhancements and benefits realized by multiwavelength analysis and compare the results to those obtained from the traditional single-wavelength detector. We illustrate the advances offered by the new instruments by comparing results from mixtures that contain different ratios of protein and DNA samples, representing analytes with distinct spectral and hydrodynamic properties. For the first time, we demonstrate that the spectral dimension not only adds valuable detail, but when spectral properties are known, individual components with distinct spectral properties measured in a mixture by the multiwavelength system can be clearly separated and decomposed into traditional datasets for each of the spectrally distinct components, even when their sedimentation coefficients are virtually identical.

Characterization of size, anisotropy, and density heterogeneity of nanoparticles by sedimentation velocity.

A critical problem in materials science is the accurate characterization of the size dependent properties of colloidal inorganic nanocrystals. Due to the intrinsic polydispersity present during synthesis, dispersions of such materials exhibit simultaneous heterogeneity in density ρ, molar mass M, and particle diameter d. The density increments ∂ρ/∂d and ∂ρ/∂M of these nanoparticles, if known, can then provide important information about crystal growth and particle size distributions. For most classes of nanocrystals, a mixture of surfactants is added during synthesis to control their shape, size, and optical properties. However, it remains a challenge to accurately determine the amount of passivating ligand bound to the particle surface post synthesis. The presence of the ligand shell hampers an accurate determination of the nanocrystal diameter. Using CdSe and PbS semiconductor nanocrystals, and the ultrastable silver nanoparticle (M4Ag44(p-MBA)30), as model systems, we describe a Custom Grid method implemented in UltraScan-III for the characterization of nanoparticles and macromolecules using sedimentation velocity analytical ultracentrifugation. We show that multiple parametrizations are possible, and that the Custom Grid method can be generalized to provide high resolution composition information for mixtures of solutes that are heterogeneous in two out of three parameters. For such cases, our method can simultaneously resolve arbitrary two-dimensional distributions of hydrodynamic parameters when a third property can be held constant. For example, this method extracts partial specific volume and molar mass from sedimentation velocity data for cases where the anisotropy can be held constant, or provides anisotropy and partial specific volume if the molar mass is known.

A parametrically constrained optimization method for fitting sedimentation velocity experiments.

A method for fitting sedimentation velocity experiments using whole boundary Lamm equation solutions is presented. The method, termed parametrically constrained spectrum analysis (PCSA), provides an optimized approach for simultaneously modeling heterogeneity in size and anisotropy of macromolecular mixtures. The solutions produced by PCSA are particularly useful for modeling polymerizing systems, where a single-valued relationship exists between the molar mass of the growing polymer chain and its corresponding anisotropy. The PCSA uses functional constraints to identify this relationship, and unlike other multidimensional grid methods, assures that only a single molar mass can be associated with a given anisotropy measurement. A description of the PCSA algorithm is presented, as well as several experimental and simulated examples that illustrate its utility and capabilities. The performance advantages of the PCSA method in comparison to other methods are documented. The method has been added to the UltraScan-III software suite, which is available for free download from http://www.ultrascan.uthscsa.edu.