Principles of Protein−Protein Interactions: What are the Preferred Ways For Proteins To Interact?

Assessment of helical interfaces in protein-protein interactions

Herein we identify and analyze helical protein interfaces as potential targets for synthetic modulators of protein-protein interactions.

ModLink+: improving fold recognition by using protein-protein interactions

MOTIVATION

Several strategies have been developed to predict the fold of a target protein sequence, most of which are based on aligning the target sequence to other sequences of known structure. Previously, we demonstrated that the consideration of protein-protein interactions significantly increases the accuracy of fold assignment compared with PSI-BLAST sequence comparisons. A drawback of our method was the low number of proteins to which a fold could be assigned. Here, we present an improved version of the method that addresses this limitation. We also compare our method to other state-of-the-art fold assignment methodologies.

RESULTS

Our approach (ModLink+) has been tested on 3716 proteins with domain folds classified in the Structural Classification Of Proteins (SCOP) as well as known interacting partners in the Database of Interacting Proteins (DIP). For this test set, the ratio of success [positive predictive value (PPV)] on fold assignment increases from 75% for PSI-BLAST, 83% for HHSearch and 81% for PRC to >90% for ModLink+at the e-value cutoff of 10(-3). Under this e-value, ModLink+can assign a fold to 30-45% of the proteins in the test set, while our previous method could cover <25%. When applied to 6384 proteins with unknown fold in the yeast proteome, ModLink+combined with PSI-BLAST assigns a fold for domains in 3738 proteins, while PSI-BLAST alone covers only 2122 proteins, HHSearch 2969 and PRC 2826 proteins, using a threshold e-value that would represent a PPV >82% for each method in the test set.

AVAILABILITY

The ModLink+server is freely accessible in the World Wide Web at http://sbi.imim.es/modlink/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Targeting protein–protein interactions for therapeutic intervention: a challenge for the future

Background: Over the last two decades, an increasing research effort in academia and industry has focused on the modulation (both inhibition and stabilization) of protein–protein interactions (PPIs) in order to develop novel therapeutic approaches and target-selective agents in drug discovery. Discussion: The diversity and complexity of highly dynamic systems such as PPIs present many challenges for the identification of drug-like molecules with the ability to modulate the PPI with the necessary selectivity and potency. In this review, a number of these strategies will be presented along with a critical overview of the challenges and potential solutions relating to the exploitation of PPIs as molecular targets. Conclusions: Both traditional drug discovery approaches and some more recently developed innovative strategies have already provided valuable tools for the discovery of PPI modulators, and a number of successful examples have highlighted the potential of targeting PPIs for therapeutic intervention, especially in the oncology area.

Fast predictions of thermodynamics and kinetics of protein-protein recognition from structures: from molecular design to systems biology

The increasing call for an overall picture of the interactions between the components of a biological system that give rise to the observed function is often summarized by the expression systems biology. Both the interpretative and predictive capabilities of holistic models of biochemical systems, however, depend to a large extent on the level of physico-chemical knowledge of the individual molecular interactions making up the network. This review is focused on the structure-based quantitative characterization of protein-protein interactions, ubiquitous in any biochemical pathway. Recently developed, fast and effective computational methods are reviewed, which allow the assessment of kinetic and thermodynamic features of the association-dissociation processes of protein complexes, both in water soluble and membrane environments. The performance and the accuracy of fast and semi-empirical structure-based methods have reached comparable levels with respect to the classical and more elegant molecular simulations. Nevertheless, the broad accessibility and lower computational cost provide the former methods with the advantageous possibility to perform systems-level analyses including extensive in silico mutagenesis screenings and large-scale structural predictions of multiprotein complexes.

Computational study of the heterodimerization between mu and delta receptors

A growing body of evidence indicated that the G protein coupled receptors exist as homo- or hetero-dimers in the living cell. The heterodimerization between mu and delta opioid receptors has attracted researchers' particular interests, it is reported to display novel pharmacological and signalling regulation properties. In this study, we construct the full-length 3D-model of mu and delta opioid receptors using the homology modelling method. Threading program was used to predict the possible templates for the N- and C-terminus domains. Then, a 30 ns molecular dynamics simulations was performed with each receptor embedded in an explicit membrane-water environment to refine and explore the conformational space. Based on the structures extracted from the molecular dynamics, the likely interface of mu-delta heterodimer was investigated through the analysis of protein-protein docking, cluster, shape complementary and interaction energy. The computational modelling works revealed that the most likely interface of heterodimer was formed between the transmembrane1,7 (TM1,7) domains of mu receptor and the TM(4,5) domains of delta receptor, with emphasis on mu-TM1 and delta-TM4, the next likely interface was mu(TM6,7)-delta(TM4,5), with emphasis on mu-TM6 and delta-TM4. Our results were consistent with previous reports.

Exploring the molecular design of protein interaction sites with molecular dynamics simulations and free energy calculations

The significant work that has been invested toward understanding protein-protein interaction has not translated into significant advances in structure-based predictions. In particular redesigning protein surfaces to bind to unrelated receptors remains a challenge, partly due to receptor flexibility, which is often neglected in these efforts. In this work, we computationally graft the binding epitope of various small proteins obtained from the RCSB database to bind to barnase, lysozyme, and trypsin using a previously derived and validated algorithm. In an effort to probe the protein complexes in a realistic environment, all native and designer complexes were subjected to a total of nearly 400 ns of explicit-solvent molecular dynamics (MD) simulation. The MD data led to an unexpected observation: some of the designer complexes were highly unstable and decomposed during the trajectories. In contrast, the native and a number of designer complexes remained consistently stable. The unstable conformers provided us with a unique opportunity to define the structural and energetic factors that lead to unproductive protein-protein complexes. To that end we used free energy calculations following the MM-PBSA approach to determine the role of nonpolar effects, electrostatics and entropy in binding. Remarkably, we found that a majority of unstable complexes exhibited more favorable electrostatics than native or stable designer complexes, suggesting that favorable electrostatic interactions are not prerequisite for complex formation between proteins. However, nonpolar effects remained consistently more favorable in native and stable designer complexes reinforcing the importance of hydrophobic effects in protein-protein binding. While entropy systematically opposed binding in all cases, there was no observed trend in the entropy difference between native and designer complexes. A series of alanine scanning mutations of hot-spot residues at the interface of native and designer complexes showed less than optimal contacts of hot-spot residues with their surroundings in the unstable conformers, resulting in more favorable entropy for these complexes. Finally, disorder predictions revealed that secondary structures at the interface of unstable complexes exhibited greater disorder than the stable complexes.

Topological properties of protein interaction networks from a structural perspective

Protein-protein interactions are usually shown as interaction networks (graphs), where the proteins are represented as nodes and the connections between the interacting proteins are shown as edges. The graph abstraction of protein interactions is crucial for understanding the global behaviour of the network. In this mini review, we summarize basic graph topological properties, such as node degree and betweenness, and their relation to essentiality and modularity of protein interactions. The classification of hub proteins into date and party hubs with distinct properties has significant implications for relating topological properties to the behaviour of the network. We emphasize that the integration of protein interface structure into interaction graph models provides a better explanation of hub proteins, and strengthens the relationship between the role of the hubs in the cell and their topological properties.

Circulating non-immune IgG complexes in health and disease

IgG molecules possess a well-defined ability to form complexes with various proteins at interaction sites composed of residues of the constant domains. Such non-immune complexes (non-ICs) were recently identified in the circulatory system of healthy people, as well as patients suffering from various pathologies. By forming non-ICs, attached proteins that are harmful to the organism (anaphylatoxins, for example) are removed from the circulation. Non-immune IgG complexes can react simultaneously with two cell receptors-one specific for IgG, and another specific for an associated protein. Such double reactions augment cellular responses. The attachment of a protein to an IgG site may induce structural changes in neighboring areas of IgG molecules. The formation of non-ICs helps proteins with low molecular mass to escape glomerular filtration, as well as enzymatic degradation and cell uptake. Non-immune IgG complexes have been found in commercial immune globulin preparations used for the treatment of various diseases. Among the IgG-attached proteins, there are specific disease biomarkers used for clinical diagnostics and understanding disease processes. Therefore, in order to identify potential biomarkers, not only proteins that are free in the liquid phase of serum but also proteins associated with abundant proteins such as IgG must be investigated.

Characterization of a highly conserved binding site of Mlh1 required for exonuclease I-dependent mismatch repair

Mlh1 is an essential factor of mismatch repair (MMR) and meiotic recombination. It interacts through its C-terminal region with MutL homologs and proteins involved in DNA repair and replication. In this study, we identified the site of yeast Mlh1 critical for the interaction with Exo1, Ntg2, and Sgs1 proteins, designated as site S2 by reference to the Mlh1/Pms1 heterodimerization site S1. We show that site S2 is also involved in the interaction between human MLH1 and EXO1 or BLM. Binding at this site involves a common motif on Mlh1 partners that we called the MIP-box for the Mlh1 interacting protein box. Direct and specific interactions between yeast Mlh1 and peptides derived from Exo1, Ntg2, and Sgs1 and between human MLH1 and peptide derived from EXO1 and BLM were measured with K(d) values ranging from 8.1 to 17.4 microM. In Saccharomyces cerevisiae, a mutant of Mlh1 targeted at site S2 (Mlh1-E682A) behaves as a hypomorphic form of Exo1. The site S2 in Mlh1 mediates Exo1 recruitment in order to optimize MMR-dependent mutation avoidance. Given the conservation of Mlh1 and Exo1 interaction, it may readily impact Mlh1-dependent functions such as cancer prevention in higher eukaryotes.

On the electrostatic component of protein-protein binding free energy

Calculations of electrostatic properties of protein-protein complexes are usually done within framework of a model with a certain set of parameters. In this paper we present a comprehensive statistical analysis of the sensitivity of the electrostatic component of binding free energy (DeltaDeltaGel) with respect with different force fields (Charmm, Amber, and OPLS), different values of the internal dielectric constant, and different presentations of molecular surface (different values of the probe radius). The study was done using the largest so far set of entries comprising 260 hetero and 2148 homo protein-protein complexes extracted from a previously developed database of protein complexes (ProtCom). To test the sensitivity of the energy calculations with respect to the structural details, all structures were energy minimized with corresponding force field, and the energies were recalculated. The results indicate that the absolute value of the electrostatic component of the binding free energy (DeltaDeltaGel) is very sensitive to the force field parameters, the minimization procedure, the values of the internal dielectric constant, and the probe radius. Nevertheless our results indicate that certain trends in DeltaDeltaGel behavior are much less sensitive to the calculation parameters. For instance, the fraction of the homo-complexes, for which the electrostatics was found to oppose binding, is 80% regardless of the force fields and parameters used. For the hetero-complexes, however, the percentage of the cases for which electrostatics opposed binding varied from 43% to 85%, depending on the protocol and parameters employed. A significant correlation was found between the effects caused by raising the internal dielectric constant and decreasing the probe radius. Correlations were also found among the results obtained with different force fields. However, despite of the correlations found, the absolute DeltaDeltaGel calculated with different force field parameters could differ more than tens of kcal/mol in some cases. Set of rules of obtaining confident predictions of absolute DeltaDeltaGel and DeltaDeltaGel sign are provided in the conclusion section.PACS codes: 87.15.A-, 87.15. km.

PiSite: a database of protein interaction sites using multiple binding states in the PDB

The vast accumulation of protein structural data has now facilitated the observation of many different complexes in the PDB for the same protein. Therefore, a single protein complex is not sufficient to identify their interaction sites, especially for proteins with multiple binding states or different partners, such as hub proteins. PiSite is a database that provides protein–protein interaction sites at the residue level with consideration of multiple complexes at the same time, by mapping the binding sites of all complexes containing the same protein in the PDB. PiSite provides easy web interfaces with an interactive viewer working with typical web browsers, and the different binding modes can be checked visually. All of the information can also be downloaded for further analyses. In addition, PiSite provides a list of proteins with multiple binding partners and multiple binding states, as well as up-to-date statistics of protein–protein interfaces. PiSite is available at http://pisite.hgc.jp

Architectures and functional coverage of protein-protein interfaces

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing a unique interface architecture. This data set of protein-protein interfaces is analyzed and compared with older data sets. We observe that the number of both biological and crystal interfaces increases significantly compared to the number of Protein Data Bank entries. Furthermore, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, are the ones that are also preferred in single chains.