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.     

A lock-and-key model for protein-protein interactions

MOTIVATION: Protein-protein interaction networks are one of the major post-genomic data sources available to molecular biologists. They provide a comprehensive view of the global interaction structure of an organism's proteome, as well as detailed information on specific interactions. Here we suggest a physical model of protein interactions that can be used to extract additional information at an intermediate level: It enables us to identify proteins which share biological interaction motifs, and also to identify potentially missing or spurious interactions. RESULTS: Our new graph model explains observed interactions between proteins by an underlying interaction of complementary binding domains (lock-and-key model). This leads to a novel graph-theoretical algorithm to identify bipartite subgraphs within protein-protein interaction networks where the underlying data are taken from yeast two-hybrid experimental results. By testing on synthetic data, we demonstrate that under certain modelling assumptions, the algorithm will return correct domain information about each protein in the network. Tests on data from various model organisms show that the local and global patterns predicted by the model are indeed found in experimental data. Using functional and protein structure annotations, we show that bipartite subnetworks can be identified that correspond to biologically relevant interaction motifs. Some of these are novel and we discuss an example involving SH3 domains from the Saccharomyces cerevisiae interactome. AVAILABILITY: The algorithm (in Matlab format) is available (see http://www.maths.strath.ac.uk/~aas96106/lock_key.html).     

Computational design of protein-protein interactions

Computational protein design strategies have been developed to reengineer protein-protein interfaces in an automated, generalizable fashion. In the past two years, these methods have been successfully applied to generate chimeric proteins and protein pairs with specificities different from naturally occurring protein-protein interactions. Although there are shortcomings in current approaches, both in the way conformational space is sampled and in the energy functions used to evaluate designed conformations, the successes suggest we are now entering an era in which computational methods can be used to modulate, reengineer and design protein-protein interaction networks in living cells.     

Quantitative model for binary measurements of protein-protein interactions.

We develop a stochastic model for quantifying the binary measurements of protein-protein interactions. A key concept in the model is the binary response function (BRF) which represents the conditional probability of successfully detecting a protein-protein interaction with a given number of the protein complexes. A popular form of the BRF is introduced and the effect of the sharpness (Hill's coefficient) of this function is studied. Our model is motivated by the recently developed yeast two-hybrid method for measuring protein-protein interaction networks. We suggest that the same phenomenological BRF can also be applied to the mass spectroscopic measurement of protein-protein interactions. Based on the model, we investigate the contributions to the network topology of protein-protein interactions from (i) the distribution of protein binary association free energy, and from (ii) the cellular protein abundance. It is concluded that the association constants among different protein pairs cannot be totally independent. It is also shown that not only the association constants but also the protein abundance could be a factor in producing the power-law degree distribution of protein-protein interaction networks.     

Strategies to search and design stabilizers of protein-protein interactions: a feasibility study

Since protein-protein interactions play a pivotal role in the communication on the molecular level in virtually every biological system and process, the search and design for modulators of such interactions is of utmost importance. In recent years many inhibitors for specific protein-protein interactions have been developed, however, in only a few cases, small and druglike molecules are able to interfere in the complex formation of proteins. On the other hand, there are several small molecules known to modulate protein-protein interactions by means of stabilizing an already assembled complex. To achieve this goal, a ligand is binding to a pocket, which is located rim-exposed at the interface of the interacting proteins, for example as the phytotoxin Fusicoccin, which stabilizes the interaction of plant H+-ATPase and 14-3-3 protein by nearly a factor of 100. To suggest alternative leads, we performed a virtual screening campaign to discover new molecules putatively stabilizing this complex. Furthermore, we screen a dataset of 198 transient recognition protein-protein complexes for cavities, which are located rim-exposed at their interfaces. We provide evidence for high similarity between such rim-exposed cavities and usual ligands accommodating active sites of enzymes. This analysis suggests that rim-exposed cavities at protein-protein interfaces are druggable binding sites. Therefore, the principle of stabilizing protein-protein interactions seems to be a promising alternative to the approach of the competitive inhibition of such interactions by small molecules.     

Probing 2-dimensional protein-protein interactions on model membranes

This protocol describes an in vitro approach for measuring the kinetics and affinities of interactions between membrane-anchored proteins. This method is particularly established for dissecting the interaction dynamics of cytokines with their receptor subunits. For this purpose, the receptor subunits are tethered in an orientated manner onto solid-supported lipid bilayers by using multivalent chelator lipids. Interaction between the ligand with the receptor subunits was probed by a combination of surface-sensitive spectroscopic detection techniques. Label-free detection by reflectance interferometry is used for following assembly of the membrane and tethering of the receptor subunits in quantitative terms. Total internal reflection spectroscopy is used for monitoring ligand binding to the membrane-anchored receptor, for monitoring ligand-receptor interactions by FRET and for monitoring ligand-exchange kinetics. These assays can be used for determining the affinities and stabilities of ligand-receptor complexes in plane of the membrane. The techniques described in this protocol can be established in 2-3 months.     

Probability-based model of protein-protein interactions on biological timescales

Background  

Simulation methods can assist in describing and understanding complex networks of interacting proteins, providing fresh insights into the function and regulation of biological systems. Recent studies have investigated such processes by explicitly modelling the diffusion and interactions of individual molecules. In these approaches, two entities are considered to have interacted if they come within a set cutoff distance of each other.     

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.     

Mining literature for protein-protein interactions

MOTIVATION: A central problem in bioinformatics is how to capture information from the vast current scientific literature in a form suitable for analysis by computer. We address the special case of information on protein-protein interactions, and show that the frequencies of words in Medline abstracts can be used to determine whether or not a given paper discusses protein-protein interactions. For those papers determined to discuss this topic, the relevant information can be captured for the Database of Interacting PROTEINS: Furthermore, suitable gene annotations can also be captured. RESULTS: Our Bayesian approach scores Medline abstracts for probability of discussing the topic of interest according to the frequencies of discriminating words found in the abstract. More than 80 discriminating words (e.g. complex, interaction, two-hybrid) were determined from a training set of 260 Medline abstracts corresponding to previously validated entries in the Database of Interacting Proteins. Using these words and a log likelihood scoring function, approximately 2000 Medline abstracts were identified as describing interactions between yeast proteins. This approach now forms the basis for the rapid expansion of the Database of Interacting Proteins.     

Biotin induces tetramerization of a recombinant monomeric avidin. A model for protein-protein interactions

Chicken avidin, a homotetramer that binds four molecules of biotin was converted to a monomeric form by successive mutations of interface residues to alanine. The major contribution to monomer formation was the mutation of two aspartic acid residues, which together account for ten hydrogen bonding interactions at the 1-4 interface. Mutation of these residues, together with the three hydrophobic residues at the 1-3 interface, led to stable monomer formation in the absence of biotin. Upon addition of biotin, the monomeric avidin reassociated to the tetramer, which exhibited properties similar to those of native avidin, with respect to biotin binding, thermostability, and protease resistance. To our knowledge, these unexpected results represent the first example of a small monovalent ligand that induces oligomerization of a monomeric protein. This study may suggest a biological role for low molecular weight ligands in inducing oligomerization and in maintaining the stability of multimeric protein assemblies.     

Electrochemical detection of protein-protein interactions using a yeast two hybrid: 17-beta-estradiol as a model

In this work we present a modified yeast two-hybrid bioassay for the highly sensitive detection of protein-protein interactions, based on the electrochemical monitoring of beta-D-galactosidase reporter gene activity, using p-aminophenyl-beta-D-galactopyranoside (PAPG) as a synthetic substrate. In a model system, the sensitive detection of 17-beta-estradiol was achieved at concentrations as low as 10(-11)M (approx 2 pg/ml) by monitoring 17-beta-estradiol receptor dimerization after exposure to 17-beta-estradiol. The sensitivity of this system was higher than that of standard optical methods by three orders of magnitude.     

Surface fractality as a guide for studying protein-protein interactions

The concept of fractal dimension is applied to protein surfaces. Satellite tobacco necrosis virus, prealhumin, retinol binding protein and lysozyme have been studied. A residue fractal index has been defined, which provides a suitable colour code when using computer graphics for visualizing surfaces. Some provisions are made that render the MS algorithm useful to calculate protein surface fractal dimensions. It has been found that a correlation exists between regions of high fractal dimension and those involved in protein-protein interactions. The usefulness of surface fractality in this context is demonstrated by a molecular docking experiment.     

Dynamic property is a key determinant for protein-protein interactions

Dynamic property is highly correlated with the biological functions of macromolecules, such as the activity and specificity of enzymes and the allosteric regulation in the signal transduction process. Applications of the dynamic property to protein function researches have been discussed and encouraging progresses have been achieved, for example, in enzyme activity and protein-protein docking studies. However, how the global dynamic property contributes to protein-protein interaction was still unclear. We have studied the dynamic property in protein-protein interactions based on Gaussian Network Model and applied it to classify biological and nonbiological protein-protein complexes in crystal structures. The global motion correlation between residues from the two protomers was found to be remarkably different for biological and nonbiological complexes. This correlation has been used to discriminate biological and nonbiological complexes in crystal and gave a classification rate of 86.9% in the cross-validation test. The innovation of this feature is that it is a global dynamic property which does not rely directly on the interfacial properties of the complex. In addition, the correlation of the global motions was found to be weakly correlated with the dissociation rate constant of protein complexes. We suggest that the dynamic property is a key determinant for protein-protein interaction, which can be used to discriminate native and crystal complexes and potentially be applied in protein-protein dynamic rate constants estimations.     

Ankyrin repeat: a unique motif mediating protein-protein interactions

Ankyrin repeat, one of the most widely existing protein motifs in nature, consists of 30-34 amino acid residues and exclusively functions to mediate protein-protein interactions, some of which are directly involved in the development of human cancer and other diseases. Each ankyrin repeat exhibits a helix-turn-helix conformation, and strings of such tandem repeats are packed in a nearly linear array to form helix-turn-helix bundles with relatively flexible loops. The global structure of an ankyrin repeat protein is mainly stabilized by intra- and inter-repeat hydrophobic and hydrogen bonding interactions. The repetitive and elongated nature of ankyrin repeat proteins provides the molecular bases of the unique characteristics of ankyrin repeat proteins in protein stability, folding and unfolding, and binding specificity. Recent studies have demonstrated that ankyrin repeat proteins do not recognize specific sequences, and interacting residues are discontinuously dispersed into the whole molecules of both the ankyrin repeat protein and its partner. In addition, the availability of thousands of ankyrin repeat sequences has made it feasible to use rational design to modify the specificity and stability of physiologically important ankyrin repeat proteins and even to generate ankyrin repeat proteins with novel functions through combinatorial chemistry approaches.     

Biochemical approaches for discovering protein-protein interactions

Protein–protein interactions or protein complexes are integral in nearly all cellular processes, ranging from metabolism to structure. Elucidating both individual protein associations and complex protein interaction networks, while challenging, is an essential goal of functional genomics. For example, discovering interacting partners for a 'protein of unknown function' can provide insight into actual function far beyond what is possible with sequence-based predictions, and provide a platform for future research. Synthetic genetic approaches such as two-hybrid screening often reveal a perplexing array of potential interacting partners for any given target protein. It is now known, however, that this type of anonymous screening approach can yield high levels of false-positive results, and therefore putative interactors must be confirmed by independent methods. In vitro biochemical strategies for identifying interacting proteins are varied and time-honored, some being as old as the field of protein chemistry itself. Herein we discuss five biochemical approaches for isolating and characterizing protein–protein interactions in vitro : co-immunoprecipitation, blue native gel electrophoresis, in vitro binding assays, protein cross-linking, and rate-zonal centrifugation. A perspective is provided for each method, and where appropriate specific, trial-tested methods are included.