Dissecting protein structure and function using directed evolution

To characterize the contributions of individual amino acids to the structure or function of a protein, researchers have adopted directed evolution approaches, which use iterated cycles of mutagenesis and selection or screening to search vast areas of sequence space for sets of mutations that provide insights into the protein of interest.     

Inhibiting protein-protein interactions using designed molecules

Continuing investigations into protein-protein interactions have revealed their key role in regulating a wide range of cellular processes. Although efforts to modulate these interactions are more challenging and much less mature than work on conventional drug discovery pathways, significant progress has been made on several fronts. Highlights of recent advances involve peptide-based inhibitors, including sidechain and backbone cross-linked agents, and peptide scaffolds, as well as small-molecule inhibitors of protein-protein interactions, such as those containing terephthalate or bis-imidazole scaffolds.     

Highly specific protein-protein interactions, evolution and negative design

We consider highly specific protein-protein interactions in proteomes of simple model proteins. We are inspired by the work of Zarrinpar et al (2003 Nature 426 676). They took a binding domain in a signalling pathway in yeast and replaced it with domains of the same class but from different organisms. They found that the probability of a protein binding to a protein from the proteome of a different organism is rather high, around one half. We calculate the probability of a model protein from one proteome binding to the protein of a different proteome. These proteomes are obtained by sampling the space of functional proteomes uniformly. In agreement with Zarrinpar et al we find that the probability of a protein binding a protein from another proteome is rather high, of order one tenth. Our results, together with those of Zarrinpar et al, suggest that designing, say, a peptide to block or reconstitute a single signalling pathway, without affecting any other pathways, requires knowledge of all the partners of the class of binding domains the peptide is designed to mimic. This knowledge is required to use negative design to explicitly design out interactions of the peptide with proteins other than its target. We also found that patches that are required to bind with high specificity evolve more slowly than those that are required only to not bind to any other patch. This is consistent with some analysis of sequence data for proteins engaged in highly specific interactions.     

Dissecting the role of protein-protein and protein-nucleic acid interactions in MS2 bacteriophage stability

To investigate the role of protein-protein and protein-nucleic acid interactions in virus assembly, we compared the stabilities of native bacteriophage MS2, virus-like particles (VLPs) containing nonviral RNAs, and an assembly-defective coat protein mutant (dlFG) and its single-chain variant (sc-dlFG). Physical (high pressure) and chemical (urea and guanidine hydrochloride) agents were used to promote virus disassembly and protein denaturation, and the changes in virus and protein structure were monitored by measuring tryptophan intrinsic fluorescence, bis-ANS probe fluorescence, and light scattering. We found that VLPs dissociate into capsid proteins that remain folded and more stable than the proteins dissociated from authentic particles. The proposed model is that the capsid disassembles but the protein remains bound to the heterologous RNA encased by VLPs. The dlFG dimerizes correctly, but fails to assemble into capsids, because it lacks the 15-amino acid FG loop involved in inter-dimer interactions at the viral fivefold and quasi-sixfold axes. This protein was very unstable and, when compared with the dissociation/denaturation of the VLPs and the wild-type virus, it was much more susceptible to chemical and physical perturbation. Genetic fusion of the two subunits of the dimer in the single-chain dimer sc-dlFG stabilized the protein, as did the presence of 34-bp poly(GC) DNA. These studies reveal mechanisms by which interactions in the capsid lattice can be sufficiently stable and specific to ensure assembly, and they shed light on the processes that lead to the formation of infectious viral particles.     

Prediction of protein-protein interactions using protein signature profiling

Protein domains are conserved and functionally independent structures that play an important role in interactions among related proteins. Domain-domain interactions have been recently used to predict protein-protein interactions (PPI). In general, the interaction probability of a pair of domains is scored using a trained scoring function. Satisfying a threshold, the protein pairs carrying those domains are regarded as "interacting". In this study, the signature contents of proteins were utilized to predict PPI pairs in Saccharomyces cerevisiae, Caenorhabditis elegans, and Homo sapiens. Similarity between protein signature patterns was scored and PPI predictions were drawn based on the binary similarity scoring function. Results show that the true positive rate of prediction by the proposed approach is approximately 32% higher than that using the maximum likelihood estimation method when compared with a test set, resulting in 22% increase in the area under the receiver operating characteristic (ROC) curve. When proteins containing one or two signatures were removed, the sensitivity of the predicted PPI pairs increased significantly. The predicted PPI pairs are on average 11 times more likely to interact than the random selection at a confidence level of 0.95, and on average 4 times better than those predicted by either phylogenetic profiling or gene expression profiling.     

Quantification of protein-protein interactions using fluorescence polarization.

Quantitative determinations of the dissociation constants of biomolecular interactions, in particular protein-protein interactions, are essential for a detailed understanding of the molecular basis of their specificities. Fluorescence spectroscopy is particularly well suited for such studies. This article highlights the theoretical and practical aspects of fluorescence polarization and its application to the study of protein-protein interactions. Consideration is given to the nature of the different types of fluorescence probes available and the probe characteristics appropriate for the system under investigation. Several examples from the literature are discussed that illustrate different practical aspects of the technique applied to diverse systems.     

Prediction of protein-protein interactions using random decision forest framework

MOTIVATION: Protein interactions are of biological interest because they orchestrate a number of cellular processes such as metabolic pathways and immunological recognition. Domains are the building blocks of proteins; therefore, proteins are assumed to interact as a result of their interacting domains. Many domain-based models for protein interaction prediction have been developed, and preliminary results have demonstrated their feasibility. Most of the existing domain-based methods, however, consider only single-domain pairs (one domain from one protein) and assume independence between domain-domain interactions. RESULTS: In this paper, we introduce a domain-based random forest of decision trees to infer protein interactions. Our proposed method is capable of exploring all possible domain interactions and making predictions based on all the protein domains. Experimental results on Saccharomyces cerevisiae dataset demonstrate that our approach can predict protein-protein interactions with higher sensitivity (79.78%) and specificity (64.38%) compared with that of the maximum likelihood approach. Furthermore, our model can be used to infer interactions not only for single-domain pairs but also for multiple domain pairs.     

Characterization of heterologous protein-protein interactions using analytical ultracentrifugation.

Methods for quantitative characterization of heterologous protein-protein interactions by means of analytical ultracentrifugation (AUC) include sedimentation equilibrium, tracer sedimentation equilibrium, sedimentation velocity, and analytical band sedimentation. Fundamental principles governing the behavior of macromolecules in a centrifugal field are summarized, and the application of these principles to the interpretation of data obtained from each type of experiment is reviewed. Instrumentation and software for the acquisition and analysis of data obtained from different types of AUC experiments are described.     

Imaging protein-protein interactions using fluorescence resonance energy transfer microscopy

Fluorescence resonance energy transfer (FRET) detects the proximity of fluorescently labeled molecules over distances >100 A. When performed in a fluorescence microscope, FRET can be used to map protein-protein interactions in vivo. We here describe a FRET microscopy method that can be used to determine whether proteins that are colocalized at the level of light microscopy interact with one another. This method can be implemented using digital microscopy systems such as a confocal microscope or a wide-field fluorescence microscope coupled to a charge-coupled device (CCD) camera. It is readily applied to samples prepared with standard immunofluorescence techniques using antibodies labeled with fluorescent dyes that act as a donor and acceptor pair for FRET. Energy transfer efficiencies are quantified based on the release of quenching of donor fluorescence due to FRET, measured by comparing the intensity of donor fluorescence before and after complete photobleaching of the acceptor. As described, this method uses Cy3 and Cy5 as the donor and acceptor fluorophores, but can be adapted for other FRET pairs including cyan fluorescent protein and yellow fluorescent protein.     

Prediction of protein-protein interactions: unifying evolution and structure at protein interfaces

The vast majority of the chores in the living cell involve protein-protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein-protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations.     

Non-additivity in protein-protein interactions

The energy of binding between proteins may be seen as the sum of the contributions of the individual amino acid residues. These contributions are additive when the binding energy, due to different amino acid residues, is independent of the interactions between amino acids in the same polypeptide chain. A measure of non-additivity is the coupling free energy. In this communication it is shown that: (1) the coupling free energy is the sum of intramolecular and intermolecular contributions; and (2), when additivity exists, experimentally determined values for the free energy of transfer of amino acids from water to the hydrophobic protein-protein interface are a very good approximation of their contribution to the energy of binding. Additivity cycles can be useful in determining the precise conditions where this approximation holds.     

Diversity of protein-protein interactions

In this review, we discuss the structural and functional diversity of protein-protein interactions (PPIs) based primarily on protein families for which three-dimensional structural data are available. PPIs play diverse roles in biology and differ based on the composition, affinity and whether the association is permanent or transient. In vivo, the protomer's localization, concentration and local environment can affect the interaction between protomers and are vital to control the composition and oligomeric state of protein complexes. Since a change in quaternary state is often coupled with biological function or activity, transient PPIs are important biological regulators. Structural characteristics of different types of PPIs are discussed and related to their physiological function, specificity and evolution.     

Ultra-weak reversible protein-protein interactions

Ultra-weak interactions (K(d)>100μM) between proteins have in the last decade become an increasing focus of attention in cell biology, especially in relation to cell-cell interactions and signalling processes. Methods for their quantitative definition are reviewed. NMR spectroscopy plays a major role in this area, as it not only can define interactions as weak or weaker than 3mM, but in favourable cases structural information concerning the complex can be yielded. Free solution technologies mostly fail when addressed to such systems. The AUC has the highest practical capability, but evaluation of the data to yield K(a) values is complicated by the presence of thermodynamic/hydrodynamic effects of a comparable order of magnitude. These effects can however be computationally removed by means of suitable algorithms, and K(d) values of up to 50mM can be characterised. The relative merits of velocity and equilibrium approaches are discussed, and both are shown to have particular advantages.     

MultiProtIdent: identifying proteins using database search and protein-protein interactions

Protein identification is important in proteomics. Proteomic analyses based on mass spectra (MS) constitute innovative ways to identify the components of protein complexes. Instruments can obtain the mass spectrum to an accuracy of 0.01 Da or better, but identification errors are inevitable. This study shows a novel tool, MultiProtIdent, which can identify proteins using additional information about protein-protein interactions and protein functional associations. Both single and multiple Peptide Mass Fingerprints (PMFs) are input to MultiProtIdent, which matches the PMFs to a theoretical peptide mass database. The relationships or interactions among proteins are considered to reduce false positives in PMF matching. Experiments to identify protein complexes reveal that MultiProtIdent is highly promising. The website associated with this study is http://dbms104.csie.ncu.edu.tw/.     

Principles of protein-protein interactions

In the postgenomic era, one of the most interesting and important challenges is to understand protein interactions on a large scale. The physical interactions between protein domains are fundamental to the workings of a cell: in multi-domain polypeptide chains, in multi-subunit proteins and in transient complexes between proteins that also exist independently. Thus experimental investigation of protein-protein interactions has been extensive, including recent large-scale screens using mass spectrometry. The role of computational research on protein-protein interactions encompasses not only prediction, but also understanding the nature of the interactions and their three-dimensional structures. I will discuss properties such as sequence conservation and co-regulation of genes and proteins involved in different types of physical interactions. Given that all proteins consist of their evolutionary units, the domains, all interactions occur between these domains. The interactions between domains belonging to different protein families will be the second topic of my talk.