Analytical ultracentrifugation as a tool for studying protein interactions

The last two decades have led to significant progress in the field of analytical ultracentrifugation driven by instrumental, theoretical, and computational methods. This review will highlight key developments in sedimentation equilibrium (SE) and sedimentation velocity (SV) analysis. For SE, this includes the analysis of tracer sedimentation equilibrium at high concentrations with strong thermodynamic non-ideality, and for ideally interacting systems, the development of strategies for the analysis of heterogeneous interactions towards global multi-signal and multi-speed SE analysis with implicit mass conservation. For SV, this includes the development and applications of numerical solutions of the Lamm equation, noise decomposition techniques enabling direct boundary fitting, diffusion deconvoluted sedimentation coefficient distributions, and multi-signal sedimentation coefficient distributions. Recently, effective particle theory has uncovered simple physical rules for the co-migration of rapidly exchanging systems of interacting components in SV. This has opened new possibilities for the robust interpretation of the boundary patterns of heterogeneous interacting systems. Together, these SE and SV techniques have led to new approaches to study macromolecular interactions across the entire spectrum of affinities, including both attractive and repulsive interactions, in both dilute and highly concentrated solutions, which can be applied to single-component solutions of self-associating proteins as well as the study of multi-protein complex formation in multi-component solutions.     

Protein interactions and disease: computational approaches to uncover the etiology of diseases

The genomic era has been characterised by vast amounts of data from diverse sources, creating a need for new tools to extract biologically meaningful information. Bioinformatics is, for the most part, responding to that need. The sparseness of the genomic data associated with diseases, however, creates a new challenge. Understanding the complex interplay between genes and proteins requires integration of data from a wide variety of sources, i.e. gene expression, genetic linkage, protein interaction, and protein structure among others. Thus, computational tools have become critical for the integration, representation and visualization of heterogeneous biomedical data. Furthermore, several bioinformatics methods have been developed to formulate predictions about the functional role of genes and proteins, including their role in diseases. After an introduction to the complex interplay between proteins and genetic diseases, this review explores recent approaches to the understanding of the mechanisms of disease at the molecular level. Finally, because most known mechanisms leading to disease involve some form of protein interaction, this review focuses on the recent methodologies for understanding diseases through their underlying protein interactions. Recent contributions from genetics, protein structure and protein interaction network analyses to the understanding of diseases are discussed here.     

Analytical Ultracentrifugation Sedimentation Velocity for the Characterization of Detergent-Solubilized Membrane Proteins Ca++-ATPase and ExbB

We have investigated the potential of new methods of analysis of sedimentation velocity (SV) analytical ultracentrifugation (AUC) for the characterization of detergent-solubilized membrane proteins. We analyze the membrane proteins Ca⁺⁺-ATPase and ExbB solubilized with DDM (dodecyl-β-d-maltoside). SV is extremely well suited for characterizing sample heterogeneity. DDM micelles (s _20w?=?3.1 S) and complexes (Ca⁺⁺-ATPase: s _20w?=?7.3 S; ExbB: s _20w?=?4 S) are easily distinguished. Using different detergent and protein concentrations, SV does not detect any evidence of self-association for the two proteins. An estimate of bound detergent of 0.9 g/g for Ca⁺⁺-ATPase and 1.5 g/g for ExbB is obtained from the combined analysis of SV profiles obtained using absorbance and interference optics. Combining s _20w with values of the hydrodynamic radius, R _s?=?5.5 nm for Ca⁺⁺-ATPase or R _s?=?3.4 nm for ExbB, allows the determination of buoyant molar masses, M _b. In view of their M _b and composition, Ca⁺⁺-ATPase and ExbB are monomers in our experimental conditions. We conclude that one of the main advantages of SV versus other techniques is the possibility to ascertain the homogeneity of the samples and to focus on a given complex even in the presence of other impurities or aggregates. The relative rapidity of SV measurements also allows experiments on unstable samples.     

Sedimentation equilibrium analysis of protein interactions with global implicit mass conservation constraints and systematic noise decomposition

Sedimentation equilibrium is a powerful tool for the characterization of protein self-association and heterogeneous protein interactions. Frequently, it is applied in a configuration with relatively long solution columns and with equilibrium profiles being acquired sequentially at several rotor speeds. The present study proposes computational tools, implemented in the software SEDPHAT, for the global analysis of equilibrium data at multiple rotor speeds with multiple concentrations and multiple optical detection methods. The detailed global modeling of such equilibrium data can be a nontrivial computational problem. It was shown previously that mass conservation constraints can significantly improve and extend the analysis of heterogeneous protein interactions. Here, a method for using conservation of mass constraints for the macromolecular redistribution is proposed in which the effective loading concentrations are calculated from the sedimentation equilibrium profiles. The approach is similar to that described by Roark (Biophys. Chem. 5 (1976) 185-196), but its utility is extended by determining the bottom position of the solution columns from the macromolecular redistribution. For analyzing heterogeneous associations at multiple protein concentrations, additional constraints that relate the effective loading concentrations of the different components or their molar ratio in the global analysis are introduced. Equilibrium profiles at multiple rotor speeds also permit the algebraic determination of radial-dependent baseline profiles, which can govern interference optical ultracentrifugation data, but usually also occur, to a smaller extent, in absorbance optical data. Finally, the global analysis of equilibrium profiles at multiple rotor speeds with implicit mass conservation and computation of the bottom of the solution column provides an unbiased scale for determining molar mass distributions of noninteracting species. The properties of these tools are studied with theoretical and experimental data sets.     

Gel chromatography and analytical ultracentrifugation to determine the extent of detergent binding and aggregation, and Stokes radius of membrane proteins using sarcoplasmic reticulum Ca2+-ATPase as an example

For structural studies of integral membrane proteins, including their 3D crystallization, the judicious use of detergent for solubilization and purification is required. Detergent binding by the solubilized protein is an important parameter to determine the hydrodynamic properties in terms of size and aggregational (monomeric/oligo(proto)meric) state of the protein. Detergent binding can be measured by gel filtration chromatography under equilibrium conditions and after separation from mixed micelles of solubilized lipid and detergent. Using sarcoplasmic reticulum Ca(2+)-ATPase as an example, we demonstrate in this protocol complete procedures for measurement of detergent binding using (i) radiolabeled n-dodecyl-beta-D-maltoside (DM) or (ii) from measurements of the increase in refractive index due to the presence of bound detergent on the protein. The latter measurement can also be performed by sedimentation velocity (SV) analysis in the analytical ultracentrifuge which in addition allows determination of the sedimentation coefficient. In combination with estimation of Stokes radius by gel filtration calibration, the molecular mass and asymmetry of the solubilized protein can be calculated. In the proposed protocols, the gel chromatographic procedures require 1 d; SV experiments are performed just after size exclusion. The whole time for these experiments is 24 h. Data analysis of analytical ultracentrifugation requires a couple of days.     

The use of analytical sedimentation velocity to extract thermodynamic linkage

For 25 years, the Gibbs Conference on Biothermodynamics has focused on the use of thermodynamics to extract information about the mechanism and regulation of biological processes. This includes the determination of equilibrium constants for macromolecular interactions by high precision physical measurements. These approaches further reveal thermodynamic linkages to ligand binding events. Analytical ultracentrifugation has been a fundamental technique in the determination of macromolecular reaction stoichiometry and energetics for 85 years. This approach is highly amenable to the extraction of thermodynamic couplings to small molecule binding in the overall reaction pathway. In the 1980s this approach was extended to the use of sedimentation velocity techniques, primarily by the analysis of tubulin-drug interactions by Na and Timasheff. This transport method necessarily incorporates the complexity of both hydrodynamic and thermodynamic nonideality. The advent of modern computational methods in the last 20 years has subsequently made the analysis of sedimentation velocity data for interacting systems more robust and rigorous. Here we review three examples where sedimentation velocity has been useful at extracting thermodynamic information about reaction stoichiometry and energetics. Approaches to extract linkage to small molecule binding and the influence of hydrodynamic nonideality are emphasized. These methods are shown to also apply to the collection of fluorescence data with the new Aviv FDS.     

Analysis of High Affinity Self-Association by Fluorescence Optical Sedimentation Velocity Analytical Ultracentrifugation of Labeled Proteins: Opportunities and Limitations

Sedimentation velocity analytical ultracentrifugation (SV) is a powerful first-principle technique for the study of protein interactions, and allows a rigorous characterization of binding stoichiometry and affinities. A recently introduced commercial fluorescence optical detection system (FDS) permits analysis of high-affinity interactions by SV. However, for most proteins the attachment of an extrinsic fluorophore is an essential prerequisite for analysis by FDS-SV. Using the glutamate receptor GluA2 amino terminal domain as a model system for high-affinity homo-dimerization, we demonstrate how the experimental design and choice of fluorescent label can impact both the observed binding constants as well as the derived hydrodynamic parameter estimates for the monomer and dimer species. Specifically, FAM (5,6-carboxyfluorescein) was found to create different populations of artificially high-affinity and low-affinity dimers, as indicated by both FDS-SV and the kinetics of dimer dissociation studied using a bench-top fluorescence spectrometer and Förster Resonance Energy Transfer. By contrast, Dylight488 labeled GluA2, as well as GluA2 expressed as an EGFP fusion protein, yielded results consistent with estimates for unlabeled GluA2. Our study suggests considerations for the choice of labeling strategies, and highlights experimental designs that exploit specific opportunities of FDS-SV for improving the reliability of the binding isotherm analysis of interacting systems.     

Sedimentation analysis of noninteracting and self-associating solutes using numerical solutions to the Lamm equation.

The potential of using the Lamm equation in the analysis of hydrodynamic shape and gross conformation of proteins and reversibly formed protein complexes from analytical ultracentrifugation data was investigated. An efficient numerical solution of the Lamm equation for noninteracting and rapidly self-associating proteins by using combined finite-element and moving grid techniques is described. It has been implemented for noninteracting solutes and monomer-dimer and monomer-trimer equilibria. To predict its utility, the error surface of a nonlinear regression of simulated sedimentation profiles was explored. Error contour maps were calculated for conventional independent and global analyses of experiments with noninteracting solutes and with monomer-dimer systems at different solution column heights, loading concentrations, and centrifugal fields. It was found that the rotor speed is the major determinant for the shape of the error surface, and that global analysis of different experiments can allow substantially improved characterization of the solutes. We suggest that the global analysis of the approach to equilibrium in a short-column sedimentation equilibrium experiment followed by a high-speed short-column sedimentation velocity experiment can result in sedimentation and diffusion coefficients of very high statistical accuracy. In addition, in the case of a protein in rapid monomer-dimer equilibrium, this configuration was found to reveal the most precise estimate of the association constant.     

Proteomics of membrane receptors and signaling

Receptors represent an abundant class of integral membrane proteins that transmit information on various types of signals within the cell. Assemblages of receptors and their interacting proteins (receptor complexes) have emerged as important units of signal transduction for various types of receptors including G protein coupled, ligand-gated ion channel, and receptor tyrosine kinase. This review aims to summarize the major approaches and findings of receptor proteomics. Isolation and characterization of receptor complexes from cells has become common using the methods of immunoaffinity-, ligand-, and tag-based chromatography followed by MS for the analysis of enriched receptor preparations. In addition, tools such as stable isotope labeling have contributed to understanding quantitative properties and PTMs to receptors and their interacting proteins. As data from studies on receptor-protein interactions considerably expands, complementary approaches such as bioinformatics and computational biology will undoubtedly play a significant role in defining cellular and network functions for various types of receptor complexes. Findings from receptor proteomics may also shed light on the mechanism of action for pharmacological drugs and can be of value in understanding molecular pathologies of disease states.     

Computational analysis of membrane proteins: genomic occurrence, structure prediction and helix interactions

We review recent computational advances in the study of membrane proteins, focusing on those that have at least one transmembrane helix. Transmembrane protein regions are, in many respects, easier to investigate computationally than experimentally, due to the uniformity of their structure and interactions (e.g. consisting predominately of nearly parallel helices packed together) on one hand and presenting the challenges of solubility on the other. We present the progress made on identifying and classifying membrane proteins into families, predicting their structure from amino-acid sequence patterns (using many different methods), and analyzing their interactions and packing The total result of this work allows us for the first time to begin to think about the membrane protein interactome, the set of all interactions between distinct transmembrane helices in the lipid bilayer.     

Mapping of a region of the paramyxovirus L protein required for the formation of a stable complex with the viral phosphoprotein P.

The paramyxovirus large protein (L) and phosphoprotein (P) are both required for viral RNA-dependent RNA polymerase activity. Previous biochemical experiments have shown that L and P can form a complex when expressed from cDNA plasmids in vivo. In this report, L and P proteins of the paramyxovirus simian virus 5 (SV5) were coexpressed in HeLa T4 cells from cDNA plasmids, and L-P complexes were examined. To identify regions of the SV5 L protein that are required for L-P complex formation, 16 deletion mutants were constructed by mutagenesis of an SV5 L cDNA. Following coexpression of these L mutants with cDNA-derived P and radiolabeling with 35S-amino acids, cell lysates were analyzed for stable L-P complexes by a coimmunoprecipitation assay and by sedimentation on 5 to 20% glycerol gradients. Mutant forms of L containing deletions that removed as much as 1,008 residues from the C-terminal half of the full-length 2,255-residue L protein were detected in complexes with P by these two assays. In contrast, large deletions in the N-terminal half of L resulted in proteins that were defective in the formation of stable L-P complexes. Likewise, L mutants containing smaller deletions that individually removed N-terminal regions which are conserved among paramyxovirus and rhabdovirus L proteins (domain I, II, or III) were also defective in stable interactions with P. These results suggest that the N-terminal half of the L protein contains sequences important for stable L-P complex formation and that the C-terminal half of L is not directly involved in these interactions. SV5-infected HeLa T4 cells were pulse-labeled with 35S-amino acids, and cell extracts were examined by gradient sedimentation. Solubilized L protein was detected as an approximately 8 to 10S species, while the P protein was found as both a approximately 4S form (approximately 85%) and a species that cosedimented with L (approximately 15%). These data provide the first biochemical evidence in support of a simple domain structure for an L protein of the nonsegmented negative-sense RNA viruses. The results are discussed in terms of a structural model for the L protein and the interactions of L with the second viral polymerase subunit P.     

Designing specific protein-protein interactions using computation, experimental library screening, or integrated methods

Given the importance of protein-protein interactions for nearly all biological processes, the design of protein affinity reagents for use in research, diagnosis or therapy is an important endeavor. Engineered proteins would ideally have high specificities for their intended targets, but achieving interaction specificity by design can be challenging. There are two major approaches to protein design or redesign. Most commonly, proteins and peptides are engineered using experimental library screening and/or in vitro evolution. An alternative approach involves using protein structure and computational modeling to rationally choose sequences predicted to have desirable properties. Computational design has successfully produced novel proteins with enhanced stability, desired interactions and enzymatic function. Here we review the strengths and limitations of experimental library screening and computational structure-based design, giving examples where these methods have been applied to designing protein interaction specificity. We highlight recent studies that demonstrate strategies for combining computational modeling with library screening. The computational methods provide focused libraries predicted to be enriched in sequences with the properties of interest. Such integrated approaches represent a promising way to increase the efficiency of protein design and to engineer complex functionality such as interaction specificity.     

Computational detection of protein complexes in AP-MS experiments

Protein complex identification is an important goal of protein-protein interaction analysis. To date, development of computational methods for detecting protein complexes has been largely motivated by genome-scale interaction data sets from high-throughput assays such as yeast two-hybrid or tandem affinity purification coupled with mass spectrometry (TAP-MS). However, due to the popularity of small to intermediate-scale affinity purification-mass spectrometry (AP-MS) experiments, protein complex detection is increasingly discussed in local network analysis. In such data sets, protein complexes cannot be detected using binary interaction data alone because the data contain interactions with tagged proteins only and, as a result, interactions between all other proteins remain unobserved, limiting the scope of existing algorithms. In this article, we provide a pragmatic review of network graph-based computational algorithms for protein complex analysis in global interactome data, without requiring any computational background. We discuss the practical gap in applying these algorithms to recently surging small to intermediate-scale AP-MS data sets, and review alternative clustering algorithms using quantitative proteomics data and their limitations.     

Analysis of Antibody Aggregate Content at Extremely High Concentrations Using Sedimentation Velocity with a Novel Interference Optics

Monoclonal antibodies represent the most important group of protein-based biopharmaceuticals. During formulation, manufacturing, or storage, antibodies may suffer post-translational modifications altering their physical and chemical properties. Such induced conformational changes may lead to the formation of aggregates, which can not only reduce their efficiency but also be immunogenic. Therefore, it is essential to monitor the amount of size variants to ensure consistency and quality of pharmaceutical antibodies. In many cases, antibodies are formulated at very high concentrations > 50 g/L, mostly along with high amounts of sugar-based excipients. As a consequence, all routine aggregation analysis methods, such as size-exclusion chromatography, cannot monitor the size distribution at those original conditions, but only after dilution and usually under completely different solvent conditions. In contrast, sedimentation velocity (SV) allows to analyze samples directly in the product formulation, both with limited sample-matrix interactions and minimal dilution. One prerequisite for the analysis of highly concentrated samples is the detection of steep concentration gradients with sufficient resolution: Commercially available ultracentrifuges are not able to resolve such steep interference profiles. With the development of our Advanced Interference Detection Array (AIDA), it has become possible to register interferograms of solutions as highly concentrated as 150 g/L. The other major difficulty encountered at high protein concentrations is the pronounced non-ideal sedimentation behavior resulting from repulsive intermolecular interactions, for which a comprehensive theoretical modelling has not yet been achieved. Here, we report the first SV analysis of highly concentrated antibodies up to 147 g/L employing the unique AIDA ultracentrifuge. By developing a consistent experimental design and data fit approach, we were able to provide a reliable estimation of the minimum content of soluble aggregates in the original formulations of two antibodies. Limitations of the procedure are discussed.     

Structural glycobiology: a game of snakes and ladders

Oligo- and polysaccharides are infamous for being extremely flexible molecules, populating a series of well-defined rotational isomeric states under physiological conditions. Characterization of this heterogeneous conformational ensemble has been a major obstacle impeding high-resolution structure determination of carbohydrates and acting as a bottleneck in the effort to understand the relationship between the carbohydrate structure and function. This challenge has compelled the field to develop and apply theoretical and experimental methods that can explore conformational ensembles by both capturing and deconvoluting the structural and dynamic properties of carbohydrates. This review focuses on computational approaches that have been successfully used in combination with experiment to detail the three-dimensional structure of carbohydrates in a solution and in a complex with proteins. In addition, emerging experimental techniques for three-dimensional structural characterization of carbohydrate-protein complexes and future challenges in the field of structural glycobiology are discussed. The review is divided into five sections: (1) The complexity and plasticity of carbohydrates, (2) Predicting carbohydrate-protein interactions, (3) Calculating relative and absolute binding free energies for carbohydrate-protein complexes, (4) Emerging and evolving techniques for experimental characterization of carbohydrate-protein structures, and (5) Current challenges in structural glycoscience.