Predicted protein-protein interactions in the moss Physcomitrella patens: a new bioinformatic resource

Background

Physcomitrella patens, a haploid dominant plant, is fast becoming a useful molecular genetics and bioinformatics tool due to its key phylogenetic position as a bryophyte in the post-genomic era. Genome sequences from select reference species were compared bioinformatically to Physcomitrella patens using reciprocal blasts with the InParanoid software package. A reference protein interaction database assembled using MySQL by compiling BioGrid, BIND, DIP, and Intact databases was queried for moss orthologs existing for both interacting partners. This method has been used to successfully predict interactions for a number of angiosperm plants.

Results

The first predicted protein-protein interactome for a bryophyte based on the interolog method contains 67,740 unique interactions from 5,695 different Physcomitrella patens proteins. Most conserved interactions among proteins were those associated with metabolic processes. Over-represented Gene Ontology categories are reported here.

Conclusion

Addition of moss, a plant representative 200 million years diverged from angiosperms to interactomic research greatly expands the possibility of conducting comparative analyses giving tremendous insight into network evolution of land plants. This work helps demonstrate the utility of “guilt-by-association” models for predicting protein interactions, providing provisional roadmaps that can be explored using experimental approaches. Included with this dataset is a method for characterizing subnetworks and investigating specific processes, such as the Calvin-Benson-Bassham cycle.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0524-1) contains supplementary material, which is available to authorized users.     

Implications for domain fusion protein-protein interactions based on structural information

Background  

Several in silico methods exist that were developed to predict protein interactions from the copious amount of genomic and proteomic data. One of these methods is Domain Fusion, which has proven to be effective in predicting functional links between proteins.     

Fuzzy complexes: polymorphism and structural disorder in protein-protein interactions

The notion that all protein functions are determined through macromolecular interactions is the driving force behind current efforts that aim to solve the structures of all cellular complexes. Recent findings, however, demonstrate a significant amount of structural disorder or polymorphism in protein complexes, a phenomenon that has been largely overlooked thus far. It is our view that such disorder can be classified into four mechanistic categories, covering a continuous spectrum of structural states from static to dynamic disorder and from segmental to full disorder. To emphasize its generality and importance, we suggest a generic term, 'fuzziness', for this phenomenon. Given the crucial role of protein disorder in protein-protein interactions and in regulatory processes, we envision that fuzziness will become integral to understanding the interactome.     

Transient protein-protein interactions: structural, functional, and network properties

Transient interactions, which involve protein interactions that are formed and broken easily, are important in many aspects of cellular function. Here we describe structural and functional properties of transient interactions between globular domains and between globular domains, short peptides, and disordered regions. The importance of posttranslational modifications in transient interactions is also considered. We review techniques used in the detection of the different types of transient protein-protein interactions. We also look at the role of transient interactions within protein-protein interaction networks and consider their contribution to different aspects of these networks.     

Inhibiting protein-protein interactions: a model for antagonist design

Protein-protein interactions (PPI) are a ubiquitous mode of transmitting signals in cells and tissues. We are testing a stepwise, generic, structure-driven approach for finding low molecular weight inhibitors of protein-protein interactions. The approach requires development of a high-affinity, single chain antibody directed specifically against the interaction surface of one of the proteins to obtain structural information on the interface. To this end, we developed a single chain antibody (sc1E3) against hIL-1beta that exhibited the equivalent affinity of the soluble IL-1 receptor type I (sIL-1R) for hIL-1beta and competitively blocked the sIL-1R from binding to the cytokine. The antibody proved to be more specific for hIL-1beta than the sIL-1R in that it failed to bind to either murine IL-1beta or human/murine IL-1alpha proteins. Additionally, failure of sc1E3 to bind to several hIL-1beta mutant proteins, altered at receptor site B, indicated that the antibody interacted preferentially with this site. This, coupled with other surface plasmon resonance and isothermal titration calorimetry measurements, shows that sc1E3 can achieve comparable affinity of binding hIL-1beta as the receptor through interactions at a smaller interface. This stable single chain antibody based heterodimer has simplified the complexity of the IL-1/IL-1R PPI system and will facilitate the design of the low molecular weight inhibitors of this interaction.     

Luxury accommodations: the expanding role of structural plasticity in protein-protein interactions

The recognition of multiple ligands at a single molecular surface is essential to many biological processes. Conformational flexibility has emerged as a compelling strategy for association at such convergent binding sites. Studies over the past few years have brought about a greater understanding of the role that protein plasticity might play in protein-protein interactions.     

DOCKGROUND resource for studying protein-protein interfaces

MOTIVATION: Public resources for studying protein interfaces are necessary for better understanding of molecular recognition and developing intermolecular potentials, search procedures and scoring functions for the prediction of protein complexes. RESULTS: The first release of the DOCKGROUND resource implements a comprehensive database of co-crystallized (bound-bound) protein-protein complexes, providing foundation for the upcoming expansion to unbound (experimental and simulated) protein-protein complexes, modeled protein-protein complexes and systematic sets of docking decoys. The bound-bound part of DOCKGROUND is a relational database of annotated structures based on the Biological Unit file (Biounit) provided by the RCSB as a separated file containing probable biological molecule. DOCKGROUND is automatically updated to reflect the growth of PDB. It contains 67,220 pairwise complexes that rely on 14,913 Biounit entries from 34,778 PDB entries (January 30, 2006). The database includes a dynamic generation of non-redundant datasets of pairwise complexes based either on the structural similarity (SCOP classification) or on user-defined sequence identity. The growing DOCKGROUND resource is designed to become a comprehensive public environment for developing and validating new methodologies for modeling of protein interactions. AVAILABILITY: DOCKGROUND is available at http://dockground.bioinformatics.ku.edu. The current first release implements the bound-bound part.     

Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data

MOTIVATION: Biological processes in cells are properly performed by gene regulations, signal transductions and interactions between proteins. To understand such molecular networks, we propose a statistical method to estimate gene regulatory networks and protein-protein interaction networks simultaneously from DNA microarray data, protein-protein interaction data and other genome-wide data. RESULTS: We unify Bayesian networks and Markov networks for estimating gene regulatory networks and protein-protein interaction networks according to the reliability of each biological information source. Through the simultaneous construction of gene regulatory networks and protein-protein interaction networks of Saccharomyces cerevisiae cell cycle, we predict the role of several genes whose functions are currently unknown. By using our probabilistic model, we can detect false positives of high-throughput data, such as yeast two-hybrid data. In a genome-wide experiment, we find possible gene regulatory relationships and protein-protein interactions between large protein complexes that underlie complex regulatory mechanisms of biological processes.     

A human protein-protein interaction network: a resource for annotating the proteome

Protein-protein interaction maps provide a valuable framework for a better understanding of the functional organization of the proteome. To detect interacting pairs of human proteins systematically, a protein matrix of 4456 baits and 5632 preys was screened by automated yeast two-hybrid (Y2H) interaction mating. We identified 3186 mostly novel interactions among 1705 proteins, resulting in a large, highly connected network. Independent pull-down and co-immunoprecipitation assays validated the overall quality of the Y2H interactions. Using topological and GO criteria, a scoring system was developed to define 911 high-confidence interactions among 401 proteins. Furthermore, the network was searched for interactions linking uncharacterized gene products and human disease proteins to regulatory cellular pathways. Two novel Axin-1 interactions were validated experimentally, characterizing ANP32A and CRMP1 as modulators of Wnt signaling. Systematic human protein interaction screens can lead to a more comprehensive understanding of protein function and cellular processes.     

Specificity in protein-protein interactions: the structural basis for dual recognition in endonuclease colicin-immunity protein complexes

Bacteria producing endonuclease colicins are protected against their cytotoxic activity by virtue of a small immunity protein that binds with high affinity and specificity to inactivate the endonuclease. DNase binding by the immunity protein occurs through a "dual recognition" mechanism in which conserved residues from helix III act as the binding-site anchor, while variable residues from helix II define specificity. We now report the 1.7 A crystal structure of the 24.5 kDa complex formed between the endonuclease domain of colicin E9 and its cognate immunity protein Im9, which provides a molecular rationale for this mechanism. Conserved residues of Im9 form a binding-energy hotspot through a combination of backbone hydrogen bonds to the endonuclease, many via buried solvent molecules, and hydrophobic interactions at the core of the interface, while the specificity-determining residues interact with corresponding specificity side-chains on the enzyme. Comparison between the present structure and that reported recently for the colicin E7 endonuclease domain in complex with Im7 highlights how specificity is achieved by very different interactions in the two complexes, predominantly hydrophobic in nature in the E9-Im9 complex but charged in the E7-Im7 complex. A key feature of both complexes is the contact between a conserved tyrosine residue from the immunity proteins (Im9 Tyr54) with a specificity residue on the endonuclease directing it toward the specificity sites of the immunity protein. Remarkably, this tyrosine residue and its neighbour (Im9 Tyr55) are the pivots of a 19 degrees rigid-body rotation that relates the positions of Im7 and Im9 in the two complexes. This rotation does not affect conserved immunity protein interactions with the endonuclease but results in different regions of the specificity helix being presented to the enzyme.     

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.     

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.     

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).     

Targeting protein-protein interactions for parasite control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable.     

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.