Structure-Based Assembly of Protein Complexes in Yeast

Domain interactions within the Ski2/3/8 complex and between the Ski complex and Ski7p

The Ski complex (composed of Ski3p, Ski8p, and the DEVH ATPase Ski2p) is a central component of the 3'-5' cytoplasmic mRNA degradation pathway in yeast. Although the proteins of the complex interact with each other as well as with Ski7p to mediate degradation by exosome, a 3'-exonuclease complex, the nature of these interactions is not well understood. Here we explore interactions within the Ski complex and between the Ski complex and Ski7p using a directed two-hybrid approach combined with coimmunoprecipitation experiments. We also test the functional significance of these interactions in vivo. Our results suggest that within the Ski complex, Ski3p serves as a scaffold protein with its C terminus interacting with Ski8p, and the sub-C terminus interacting with Ski2p, while no direct interaction between Ski2p and Ski8p was found. Ski7p interacts with the Ski complex via its interaction with Ski8p and Ski3p. In addition, inactivating the Ski complex by mutating conserved residues in the DEVH helicase motif of Ski2 did not abrogate its interaction with Ski7p, indicating that Ski2p function is not necessary for this interaction.

Computational characterization of proteins

Computational characterization of proteins is a necessary first step in understanding the biologic role of a protein. The composite architecture of mammalian proteins makes the prediction of the biologic role rather difficult. Nevertheless, integration of many different prediction methods allows for a more accurate representation. Information on the 3D structure of a protein improves the reliability of predictions of many features. This article reviews existing methods used to characterize proteins and several tools that provide an integrated access to different types of information. The authors point out the increasing importance of structural constraints and an increasing need to integrate different approaches.

Global rigid body modeling of macromolecular complexes against small-angle scattering data

New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms.

Protein–protein interactions: organization, cooperativity and mapping in a bottom-up Systems Biology approach

Understanding and ultimately predicting protein associations is immensely important for functional genomics and drug design. Here, we propose that binding sites have preferred organizations. First, the hot spots cluster within densely packed 'hot regions'. Within these regions, they form networks of interactions. Thus, hot spots located within a hot region contribute cooperatively to the stability of the complex. However, the contributions of separate, independent hot regions are additive. Moreover, hot spots are often already pre-organized in the unbound (free) protein states. Describing a binding site through independent local hot regions has implications for binding site definition, design and parametrization for prediction. The compactness and cooperativity emphasize the similarity between binding and folding. This proposition is grounded in computation and experiment. It explains why summation of the interactions may over-estimate the stability of the complex. Furthermore, statistically, charge-charge coupling of the hot spots is disfavored. However, since within the highly packed regions the solvent is screened, the electrostatic contributions are strengthened. Thus, we propose a new description of protein binding sites: a site consists of (one or a few) self-contained cooperative regions. Since the residue hot spots are those conserved by evolution, proteins binding multiple partners at the same sites are expected to use all or some combination of these regions.

Inferring protein-protein interactions through high-throughput interaction data from diverse organisms

MOTIVATION

Identifying protein-protein interactions is critical for understanding cellular processes. Because protein domains represent binding modules and are responsible for the interactions between proteins, computational approaches have been proposed to predict protein interactions at the domain level. The fact that protein domains are likely evolutionarily conserved allows us to pool information from data across multiple organisms for the inference of domain-domain and protein-protein interaction probabilities.

RESULTS

We use a likelihood approach to estimating domain-domain interaction probabilities by integrating large-scale protein interaction data from three organisms, Saccharomyces cerevisiae, Caenorhabditis elegans and Drosophila melanogaster. The estimated domain-domain interaction probabilities are then used to predict protein-protein interactions in S.cerevisiae. Based on a thorough comparison of sensitivity and specificity, Gene Ontology term enrichment and gene expression profiles, we have demonstrated that it may be far more informative to predict protein-protein interactions from diverse organisms than from a single organism.

AVAILABILITY

The program for computing the protein-protein interaction probabilities and supplementary material are available at http://bioinformatics.med.yale.edu/interaction.

Phosducin-like protein acts as a molecular chaperone for G protein betagamma dimer assembly

Phosducin-like protein (PhLP) is a widely expressed binding partner of the G protein betagamma subunit dimer (Gbetagamma). However, its physiological role is poorly understood. To investigate PhLP function, its cellular expression was blocked using RNA interference, resulting in inhibition of Gbetagamma expression and G protein signaling. This inhibition was caused by an inability of nascent Gbetagamma to form dimers. Phosphorylation of PhLP at serines 18-20 by protein kinase CK2 was required for Gbetagamma formation, while a high-affinity interaction of PhLP with the cytosolic chaperonin complex appeared unnecessary. PhLP bound nascent Gbeta in the absence of Ggamma, and S18-20 phosphorylation was required for Ggamma to associate with the PhLP-Gbeta complex. Once Ggamma bound, PhLP was released. These results suggest a mechanism for Gbetagamma assembly in which PhLP stabilizes the nascent Gbeta polypeptide until Ggamma can associate, resulting in membrane binding of Gbetagamma and release of PhLP to catalyze another round of assembly.

The relationship between the flexibility of proteins and their conformational states on forming protein-protein complexes with an application to protein-protein docking

We investigate the extent to which the conformational fluctuations of proteins in solution reflect the conformational changes that they undergo when they form binary protein-protein complexes. To do this, we study a set of 41 proteins that form such complexes and whose three-dimensional structures are known, both bound in the complex and unbound. We carry out molecular dynamics simulations of each protein, starting from the unbound structure, and analyze the resulting conformational fluctuations in trajectories of 5 ns in length, comparing with the structure in the complex. It is found that fluctuations take some parts of the molecules into regions of conformational space close to the bound state (or give information about it), but at no point in the simulation does each protein as whole sample the complete bound state. Subsequent use of conformations from a clustered MD ensemble in rigid-body docking is nevertheless partially successful when compared to docking the unbound conformations, as long as the unbound conformations are themselves included with the MD conformations and the whole globally rescored. For one key example where sub-domain motion is present, a ribonuclease inhibitor, principal components analysis of the MD was applied and was also able to produce conformations for docking that gave enhanced results compared to the unbound. The most significant finding is that core interface residues show a tendency to be less mobile (by size of fluctuation or entropy) than the rest of the surface even when the other binding partner is absent, and conversely the peripheral interface residues are more mobile. This surprising result, consistent across up to 40 of the 41 proteins, suggests different roles for these regions in protein recognition and binding, and suggests ways that docking algorithms could be improved by treating these regions differently in the docking process.

From protein networks to biological systems

A system-level understanding of any biological process requires a map of the relationships among the various molecules involved. Technologies to detect and predict protein interactions have begun to produce very large maps of protein interactions, some including most of an organism's proteins. These maps can be used to study how proteins work together to form molecular machines and regulatory pathways. They also provide a framework for constructing predictive models of how information and energy flow through biological networks. In many respects, protein interaction maps are an entrée into systems biology.

Ribosome Builder: A software project to simulate the ribosome

The Ribosome Builder is a software project that provides tools and techniques to create dynamic models of macromolecular systems from the rapidly growing numbers of atomic structural models. It includes a computer program that allows the user to assemble the multiple molecular components within a 3D space and to define the hypothetical interactions of these components with the initial goal of understanding protein translation at an atomic level of detail. The program employs a simplified molecular dynamics forcefield that can simulate the long time-scale events, such as docking of translation factors and mRNA translocation. An embedded scripting language and Application Programming Interface (API) enable the creation of Steered Molecular Dynamics (SMD) simulations through the programmable application of external forces and torques on atoms and bonds. A graphical interface is provided for displaying and interacting with models, recording movies of molecular dynamics movements, and creating annotated 3D simulations of complex macromolecular events. Initial applications of the project include simulation of tetraloop folding, docking of an mRNA on the 30S subunit and a schematic simulation of the translation elongation cycle. The program is an open source project released under the GNU public license.

From proteomic inventory to architecture

Electron tomography can provide three-dimensional reconstructions of large pleomorphic structures at molecular resolution. While the principles of electron tomography have been known for decades, its use has gathered momentum only in recent years. Technological advances have made it possible to apply it to ice-embedded biological material (cryotomography), thereby ensuring a close-to-life preservation of the samples. In combination with advanced computational methods, such as molecular identification based on pattern recognition, it is a promising approach to comprehensively map macromolecular architecture inside organelles and cells and to visualize macromolecules at work in their natural environment.

Ten thousand interactions for the molecular biologist

Previous studies have suggested that nature is restricted to about 1,000 protein folds to perform a great diversity of functions. Here, we use protein interaction data from different sources and three-dimensional structures to suggest that the total number of interaction types is also limited, and estimate that most interactions in nature will conform to one of about 10,000 types. We currently know fewer than 2,000, and at the present rate of structure determination, it will be more than 20 years before we know a full representative set.

How similar are protein folding and protein binding nuclei? Examination of vibrational motions of energy hot spots and conserved residues

The underlying physico-chemical principles of the interactions between domains in protein folding are similar to those between protein molecules in binding. Here we show that conserved residues and experimental hot spots at intermolecular binding interfaces overlap residues that vibrate with high frequencies. Similarly, conserved residues and hot spots are found in protein cores and are also observed to vibrate with high frequencies. In both cases, these residues contribute significantly to the stability. Hence, these observations validate the proposition that binding and folding are similar processes. In both packing plays a critical role, rationalizing the residue conservation and the experimental alanine scanning hot spots. We further show that high-frequency vibrating residues distinguish between protein binding sites and the remainder of the protein surface.

Structure-based systems biology: a zoom lens for the cell

Systems biology seeks to explain complex biological systems, such as the cell, through the integration of many different types of information. Here, we discuss how the incorporation of high-resolution structural data can provide key molecular details often necessary to understand the complex connection between individual molecules and cell behavior. We suggest a process of zooming on the cell, from global networks through pathways to the precise atomic contacts at the interfaces of interacting proteins.

Shared components of protein complexes--versatile building blocks or biochemical artefacts?

Protein complexes perform many important functions in the cell. Large-scale studies of protein-protein interactions have not only revealed new complexes but have also placed many proteins into multiple complexes. Whilst the advocates of hypothesis-free research touted the discovery of these shared components as new links between diverse cellular processes, critical commentators denounced many of the findings as artefacts, thus questioning the usefulness of large-scale approaches. Here, we survey proteins known to be shared between complexes, as established in the literature, and compare them to shared components found in high-throughput screens. We discuss the various challenges to the identification and functional interpretation of bona fide shared components, namely contaminants, variant and megacomplexes, and transient interactions, and suggest that many of the novel shared components found in high-throughput screens are neither the results of contamination nor central components, but appear to be primarily regulatory links in cellular processes.

Towards complete descriptions of the free-energy landscapes of proteins

In recent years increasingly detailed information about the structures and dynamics of protein molecules has been obtained by innovative applications of experimental techniques, in particular nuclear magnetic resonance spectroscopy and protein engineering, and theoretical methods, notably molecular dynamics simulations. In this article we discuss how such approaches can be combined by incorporating a wide range of different types of experimental data as restraints in computer simulations to provide unprecedented detail about the ensembles of structures that describe proteins in a wide variety of states from the native structure to highly unfolded species. Knowledge of these ensembles is beginning to enable the complete free-energy landscapes of individual proteins to be defined at atomic resolution. This strategy has provided new insights into the mechanism by which proteins are able to fold into their native states, or by which they fail to do so and give rise to harmful aggregates that are associated with a wide range of debilitating human diseases.

A structural perspective on protein-protein interactions

Structures of macromolecular complexes are necessary for a mechanistic description of biochemical and cellular processes. They can be solved by experimental methods, such as X-ray crystallography, NMR spectroscopy and electron microscopy, as well as by computational protein structure prediction, docking and bioinformatics. Recent advances and applications of these methods emphasize the need for hybrid approaches that combine a variety of data to achieve better efficiency, accuracy, resolution and completeness.

Protein interaction networks from yeast to human

Protein interaction networks summarize large amounts of protein-protein interaction data, both from individual, small-scale experiments and from automated high-throughput screens. The past year has seen a flood of new experimental data, especially on metazoans, as well as an increasing number of analyses designed to reveal aspects of network topology, modularity and evolution. As only minimal progress has been made in mapping the human proteome using high-throughput screens, the transfer of interaction information within and across species has become increasingly important. With more and more heterogeneous raw data becoming available, proper data integration and quality control have become essential for reliable protein network reconstruction, and will be especially important for reconstructing the human protein interaction network.

Data-driven docking for the study of biomolecular complexes

With the amount of genetic information available, a lot of attention has focused on systems biology, in particular biomolecular interactions. Considering the huge number of such interactions, and their often weak and transient nature, conventional experimental methods such as X-ray crystallography and NMR spectroscopy are not sufficient to gain structural insight into these. A wealth of biochemical and/or biophysical data can, however, readily be obtained for biomolecular complexes. Combining these data with docking (the process of modeling the 3D structure of a complex from its known constituents) should provide valuable structural information and complement the classical structural methods. In this review we discuss and illustrate the various sources of data that can be used to map interactions and their combination with docking methods to generate structural models of the complexes. Finally a perspective on the future of this kind of approach is given.

Structure of the complex between the cytosolic chaperonin CCT and phosducin-like protein

The three-dimensional structure of the complex formed between the cytosolic chaperonin CCT (chaperonin containing TCP-1) and phosducin (Pdc)-like protein (PhLP), a regulator of CCT activity, has been solved by cryoelectron microscopy. Binding of PhLP to CCT occurs through only one of the chaperonin rings, and the protein does not occupy the central folding cavity but rather sits above it through interactions with two regions on opposite sides of the ring. This causes the apical domains of the CCT subunits to close in, thus excluding access to the folding cavity. The atomic model of PhLP generated from several atomic structures of the homologous Pdc fits very well with the mass of the complex attributable to PhLP and predicts the involvement of several sequences of PhLP in CCT binding. Binding experiments performed with PhLP/Pdc chimeric proteins, taking advantage of the fact that Pdc does not interact with CCT, confirm that both the N- and C-terminal domains of PhLP are involved in CCT binding and that several regions suggested by the docking experiment are indeed critical in the interaction with the cytosolic chaperonin.

A systems view of mRNP biology

Gene expression occurs through a complex mRNA-protein (mRNP) system that stretches from transcription to translation. Gene expression processes are increasingly studied from global perspectives in order to understand their pathways, properties, and behaviors as a system. Here we review these beginnings of mRNP systems biology, as they have emerged from recent large-scale investigation of mRNP components, interactions, and dynamics. Such work has begun to lay the foundation for a broader, integrated view of mRNP organization in gene expression.

Statistical analysis of domains in interacting protein pairs

MOTIVATION

Several methods have recently been developed to analyse large-scale sets of physical interactions between proteins in terms of physical contacts between the constituent domains, often with a view to predicting new pairwise interactions. Our aim is to combine genomic interaction data, in which domain-domain contacts are not explicitly reported, with the domain-level structure of individual proteins, in order to learn about the structure of interacting protein pairs. Our approach is driven by the need to assess the evidence for physical contacts between domains in a statistically rigorous way.

RESULTS

We develop a statistical approach that assigns p-values to pairs of domain superfamilies, measuring the strength of evidence within a set of protein interactions that domains from these superfamilies form contacts. A set of p-values is calculated for SCOP superfamily pairs, based on a pooled data set of interactions from yeast. These p-values can be used to predict which domains come into contact in an interacting protein pair. This predictive scheme is tested against protein complexes in the Protein Quaternary Structure (PQS) database, and is used to predict domain-domain contacts within 705 interacting protein pairs taken from our pooled data set.

Bacterial subcellular architecture: recent advances and future prospects

Traditional textbook representations of the prokaryotic cytoplasm show an amorphous, unstructured amalgamation of proteins and small molecules in which a randomly arranged chromosome resides. The development and application of a swathe of microscopic techniques over the last 10 years in particular, has shown this image of the microbial cell to be incorrect: the cytoplasm is highly structured with many proteins carrying out their assigned functions at specific subcellular locations; bacteria contain cytoskeletal elements including microtubule, actin and intermediate filament homologues; the chromosome is not randomly folded and is organized in such a way as to facilitate efficient segregation upon cell division. This review will concentrate on recent advances in our understanding of subcellular architecture and the techniques that have led to these discoveries.

Crystal structure of Ski8p, a WD-repeat protein with dual roles in mRNA metabolism and meiotic recombination

Ski8p is a WD-repeat protein with an essential role for the Ski complex assembly in an exosome-dependent 3'-to-5' mRNA decay. In addition, Ski8p is involved in meiotic recombination by interacting with Spo11p protein. We have determined the crystal structure of Ski8p from Saccharomyces cerevisiae at 2.2 A resolution. The structure reveals that Ski8p folds into a seven-bladed beta propeller. Mapping sequence conservation and hydrophobicities of amino acids on the molecular surface of Ski8p reveals a prominent site on the top surface of the beta propeller, which is most likely involved in mediating interactions of Ski8p with Ski3p and Spo11p. Mutagenesis combined with yeast two-hybrid and GST pull-down assays identified the top surface of the beta propeller as being required for Ski8p binding to Ski3p and Spo11p. The functional implications for Ski8p function in both mRNA decay and meiotic recombination are discussed.

Computational exploration of structural information from cryo-electron tomograms

Cryo-electron tomography aims to act as an interface between in vivo cell imaging and techniques achieving atomic resolution. This attempt to bridge the resolution gap is facilitated by recent software and hardware advances. Information provided by atomically resolved macromolecules and molecular interaction data need to be put into a common framework in order to create a hybrid multidimensional cellular image. A major partner in this enterprise is the development of regularization and pattern recognition techniques, which try to identify macromolecular complexes as a function of their structural signature in cryo-electron tomograms of living cells.