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BACKGROUND:A hub protein is one that interacts with many functional partners. The annotation of hub proteins, or more generally the protein-protein interaction "degree" of each gene, requires quality genome-wide data. Data obtained using yeast two-hybrid methods contain many false positive interactions between proteins that rarely encounter each other in living cells, and such data have fallen out of favor.RESULTS:We find that protein "stickiness", measured as network degree in ostensibly low quality yeast two-hybrid data, is a more predictive genomic metric than the number of functional protein-protein interactions, as assessed by supposedly higher quality high throughput affinity capture mass spectrometry data. In the yeast Saccharomyces cerevisiae, a protein's high stickiness, but not its high number of functional interactions, predicts low stochastic noise in gene expression, low plasticity of gene expression across different environments, and high probability of forming a homo-oligomer. Our results are robust to a multiple regression analysis correcting for other known predictors including protein abundance, presence of a TATA box and whether a gene is essential. Once the higher stickiness of homo-oligomers is controlled for, we find that homo-oligomers have noisier and more plastic gene expression than other proteins, consistent with a role for homo-oligomerization in mediating robustness.CONCLUSIONS:Our work validates use of the number of yeast two-hybrid interactions as a metric for protein stickiness. Sticky proteins exhibit low stochastic noise in gene expression, and low plasticity in expression across different environments.

Inter-molecular interaction is at the heart of biological function. Proteins can interact with ligands, peptides, small molecules, and other proteins to serve their structural or functional purpose. With advances in combinatorial chemistry and the development of high throughput binding assays, the available inter-molecular interaction data is increasing exponentially. As the space of testable compounds increases, the complexity and cost of finding a suitable inhibitor for a protein interaction increases. Computational drug discovery plays an important role in minimizing the time and cost needed to study the space of testable compounds. This work focuses on the usage of various computational methods in identifying protein interaction inhibitors and demonstrates the ability of computational drug discovery to contribute to the ever growing field of molecular interaction. A program to predict the location of binding surfaces on proteins, STP (Mehio et al., Bioinformatics, 2010, in press), has been created based on calculating the propensity of triplet-patterns of surface protein atoms that occur in binding sites. The use of STP in predicting ligand binding sites, allosteric binding sites, enzyme classification numbers, and binding details in multi-unit complexes is demonstrated. STP has been integrated into the in-house high throughput drug discovery pipeline, allowing the identification of inhibitors for proteins whose binding sites are unknown. Another computational paradigm is introduced, creating a virtual library of -turn peptidomimetics, designed to mimic the interaction of the Baff-Receptor (Baff-R) with the B-Lymphocyte Stimulator (Blys). LIDAEUS (Taylor, et al., Br J Pharmacol, 2008; 153, p. S55-S67) is used to identify chemical groups with favorable binding to Blys. Natural and non-natural sidechains are then used to create a library of synthesizable cyclic hexapeptides that would mimic the Blys:Baff-R interaction. Finally, this work demonstrates the usage and synergy of various in-house computational resources in drug discovery. The ProPep database is a repository used to study trends, motifs, residue pairing frequencies, and aminoacid enrichment propensities in protein-peptide interaction. The LHRLL protein-peptide interaction motif is identified and used with UFSRAT (S. Shave, PhD Thesis, University of Edinburgh, 2010) to conduct ligand-based virtual screening and generate a list of possible antagonists from the EDULISS (K. Hsin, PhD Thesis, University of Edinburgh, 2010) compound repository. A high throughput version of AutoDock (Morris, et al., J Comput Chem, 1998; 19, p. 1639-62) was adapted and used for precision virtual screening of these molecules, resulting in a list of compounds that are likely to inhibit the binding of this motif to several Nuclear Receptors.

Οι πρωτεϊνικές αλληλεπιδράσεις (PPI) αναφέρονται στην σύνδεση δύο ή περισσοτέρων πρωτεϊνών ώστε να εκτελεστεί μια βιολογική λειτουργία. Την τελευταία δεκαετία, νέες τεχνολογίες υψηλής απόδοσης για τον εντοπισμό αυτών των αλληλεπιδράσεων έχουν παράγει μεγάλης κλίμακας σύνολα δεδομένων τόσο του ανθρώπου όσο και των περισσοτέρων ειδών. Με την αναπαράσταση αυτών των δεδομένων σε δίκτυα, με τους κόμβους να αναπαριστούν τις πρωτεΐνες και τις ακμές τις αλληλεπιδράσεις, μπορούν να εξαχθούν χρήσιμες πληροφορίες σχετικά με τον προσδιορισμό της λειτουργίας των πρωτεϊνών/πρόβλεψη ή σχετικά με το πώς να σχεδιαστούν κατάλληλα φάρμακα που προσδιορίζουν τα νέα γονίδια-στόχους για τον καρκίνο ή τους μηχανισμούς που ελέγχουν (ή ρυθμίζουν) τις βιολογικές αλληλεπιδράσεις που είναι υπεύθυνες για την καλή ή την κακή λειτουργία ενός κυττάρου. Στα πλαίσια της παρούσας διπλωματικής, κληθήκαμε να κάνουμε λειτουργική πρόβλεψη των πρωτεϊνών στο δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου εφαρμόζοντας μια μέθοδο δυναμικής επικάλυψης η οποία βασίζεται στον έλεγχο του πώς οι ταλαντωτές οργανώνονται σε ένα «αρθρωτό»(modular) δίκτυο σχηματίζοντας διεπαφές συγχρονισμού και κοινότητες επικάλυψης. Μελετήσαμε το δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου και τις κλάσεις λειτουργιών θεωρώντας ένα σύνολο ταλαντωτών φάσης (phase oscillators) με μία τοπολογία συνδέσεων που ορίζεται από το δίκτυο πρωτεϊνικών αλληλεπιδράσεων του ανθρώπου. Συγκεκριμένα, αρχίσαμε με μία απλή ομαδοποίηση για κάθε πρωτεΐνη και έπειτα χρησιμοποιήσαμε την μέθοδο δυναμικής επικάλυψης για τον προσδιορισμό των λειτουργιών των πρωτεϊνών του PPI δικτύου. Στην συνέχεια, εντοπίσαμε εκείνες τις πρωτεΐνες οι οποίες δεν είχαν ομαδοποιηθεί σωστά καθώς και τις πρωτεϊνες που ήταν πιθανόν να «συμμετείχαν» σε περισσότερες από μία λειτουργικές κλάσεις (πολυλειτουργικές πρωτεΐνες). Με κατάλληλο έλεγχο των αλληλεπιδράσεων μεσαίας κλίμακας του δικτύου των δυναμικών συστημάτων που δημιουργήθηκε παρήχθησαν χρήσιμες πληροφορίες για τις μικρής και μεγάλης κλίμακας διαδικασίες μέσω των οποίων οι βιολογικές διεργασίες οργανώνονται σε ένα κύτταρο γεγονός που αποκαλύπτει ότι η μέθοδος είναι ικανή όχι μόνο να εντοπίσει τις μη σωστά ομαδοποιημένες πρωτεΐνες αλλά και να αποκαλύψει αυτές που έχουν διπλή λειτουργικότητα (2 λειτουργίες). / Protein-protein interactions (PPI) refer to the binding of two or more proteins to perform a biological function. In the last decade, novel high-throughput technologies for detecting those interactions have produced large-scale data sets across human and most model species. By embedding these data in networks, with nodes representing proteins and edges the detected PPIs, useful information can be extracted regarding protein functional annotation/prediction or on how to design proper drugs, identifying new targets on cancer, or mechanisms to control (or regulate) the biological interactions responsible for the functioning,or malfunctioning, of a cell. Under the framework of my master thesis, I had to apply a method of dynamical overlap based on the inspection of how oscillators organize in a modular network by forming synchronization interfaces and overlapping communities to the human PPI network. I studied the human protein interaction network (PIN) and its functional modules by considering an ensemble of phase oscillators with a topology of connections defined by the human PIN. In particular, I started with a single classification for each protein and I used the dynamical overlap method for identifying/predicting of the proteins function(s) in the PPI network. Then, I identified all those proteins that were misclassified and those proteins that were likely to be involved in more than one of the functional categories in our data(multifunctional proteins). A proper inspection on the meso-scale interactions of the generated network of dynamical systems provided useful information on the micro- and macro- scale processes through which biological processes are organized in a cell, that is, the method is not only able to identify the misclassified proteins but also to unveil those proteins that have double functionality.

Two thirds of plant viruses are positive-strand RNA viruses including the family Tombusviridae. One of the best-studied members of this family is Tomato bushy stunt virus (TBSV). Like many other viruses, TBSV has much fewer genes when compared to its hosts’ genome. Nevertheless, TBSV utilizes its genome very judiciously. To compensate for a lack of many proteins of its own, it codes for multi-functional replication protein p33 and also co-opts host factors to facilitate its replication. By using recombinant replication proteins p33 and p92 containing single amino acid changes in protein-protein interaction domains (S1 and S2), I demonstrated that the replication proteins are required in sequential steps during virus replication. The in vitro cell-free extract(CFE) based TBSV replication assays revealed that mutations in S1 and S2 domains affected RNA template selection, recruitment and assembly of replicase complex. TBSV replicates on the cytosolic surface of peroxisomal membranes. To identify the host factor involved in this process of transporting viral replication proteins to peroxisome, I tested the peroxisomal transporter proteins for their ability to bind to p33 in vitro, which led to the discovery of Pex19p. Pull-down and co-purification experiments revealed transient nature of p33-Pex19p binding as expected from a transporter. When pex19p was retargeted to mitochondria, a large fraction of p33 was also re-distributed to the mitochondria validating the importance of Pex19p in p33 localization. TBSV also utilizes its genomic RNA for non-template activities during its replication. Accordingly, TBSV RNA serves as a platform for the assembly of replicase complex. To further characterize the regulatory cis-elements involved in this process, I utilized CFE and different TBSV RNA mutants together with recombinant p33 and p92 in vitro replication assays. These experiments revealed the role of RNA recruitment element [RIISL(+)] and 3’ non-coding regions as minimal cis-elements required to assemble functional replicase complex. The experiments also indicated that the RIISL(+) and 3’ non coding regions could be physically separated on two different RNA molecules to assemble TBSV replicase, suggesting insights into viral evolution.

Enterohaemorrhagic Escherichia coli (EHEC) are a recently emerged group of pathogens that can cause fatal infections in the young and elderly. EHEC utilize a virulence factor delivery organelle called a ’Type 3 secretion system’ that results in the formation of characteristic ‘pedestal structures’ on epithelial cells allowing colonization in the human or ruminant gastrointestinal tract. To achieve this, effector proteins have to be injected into host cells. The SepL-SepD complex has been shown to be key for controlling T3-related protein secretion in EHEC. Lack of either protein results in effector hypersecretion and strongly impaired secretion of EspADB translocon proteins. Therefore, the expression and function of SepL was the focus of my PhD research. The expression of SepL was shown to be heterogeneous and co-expressed with EspA filaments in EHEC O157 strains. My work revealed two transcriptional regulators (Ler and SepD) and two putative posttranscriptional regulators (Hfq and CsrA) of SepL expression. Further experiments mapped a key mRNA region required for heterogeneous expression of SepL. This sequence forms a predicted hairpin structure around the Shine-Dalgarno (SD) site of sepL. A model has been formed based on my data in which Hfq and CsrABCD bind to the mRNA potentially competing to control translation. Functionally, the C-terminus of SepL was found to be expendable for 1) SepD binding; 2) SepL membrane localization and 3) translocon export, however it was required for 1) limiting effector secretion via (2) a Tir interaction which might be disassociated by (3) an EscD interaction once host cell signals are sensed. Previously, the concept of two different types of T3 secretion signal were demonstrated in Yersinia spp, I tested this hypothesis in EHEC using both wild type and SepL/SepD deficient EHEC strains. SepL/SepD is required for the N-terminal signal pathway but not a chaperone binding domain signal pathway. A 12aa NleA which only contained an N-terminal signal was shown to bind to SepD and so did the multi-functional T3 chaperone ― CesT. Finally, Far-Western assays demonstrated that SepL only interacted with Tir while SepD could bind other effector proteins indicating that SepL/SepD may act as a targeting hub for effector protein secretion.

<p>Eukaryotic Topoisomerase 2 is an essential enzyme that solves DNA topological problems such as DNA knotting, catenation, and supercoiling. It alters the DNA topology by introducing transient double strand break in one DNA duplex as a gate for the passage of another DNA duplex. Two different aspects of studies about eukaryotic Topoisomerase 2 will be covered in this thesis. In the first half of the thesis, we investigated conformational changes of human Topoisomerase 2&#61537; (hsTop2&#61537;) in the presence of cofactors and inhibitors. In the second half, we focused on an unknown regulatory function in the C-terminal domain (CTD) of Drosophila Topoisomerase 2 (Top2).</p><p>In the project of studying enzyme conformational changes, we adapted a previously developed methodology, Pulse-Alkylation Mass Spectrometry, with monobromobimane to study the protein dynamics of hsTop2&#61537;. Using this method, we captured the evidence of conformational changes in the presence of ATP and Mg2+ or the Top2 inhibitor, ICRF-193 which were not previously observed. Last, by using CTD truncated hsTop2&#61537;, the increasing reactivity of Cys427 suggested the CTD domain might be tethered adjacent to the core enzyme.</p><p>Following the study of enzyme conformational changes, we switched gear to examine an interaction between Drosophila Top2 and Mus101, homolog of human TopBP1. We first found that Mus101 interacts with CTD of Top2 in a phosphorylation-dependent manner. Next, in the co-immunoprecipitation and pull-down experiments using truncated or mutant Top2 with various Ser to Ala substitutions, we mapped the binding motif to the last amino acids of Top2 and identified that phosphorylation of Ser1428 and Ser1443 is important for Top2 to interact with the N-terminus of Mus101, which contains BRCT1/2 domains (BRCT, BRCA1 C-terminus). The binding affinity of the N-terminal Mus101 with a synthetic phosphorylated peptide covering the last 25 amino acids of Top2 (with pS1428 and pS1443) was determined by surface plasmon resonance with a Kd of 0.57 &#956;M. In an in vitro decatenation assay, Mus101 can specifically reduce the decatenation activity of Top2, and dephosphorylation of Top2 attenuates this response to Mus101. Next, we endeavored to establish a cellular system for testing the biological function of Top2-Mus101 interaction. Top2-silenced S2 cells rescued by Top2&#61508;20, truncation of 20 amino acids from the C-terminus of Top2, developed abnormally high chromosome numbers, which implies an infidelity in chromosome segregation during mitosis. Lastly, Top2-null flies rescued by Top2 with S1428A and S1443A were found to be viable but sterile. After investigating spermatogenesis, telophase of meiosis I was delayed, indicating Top2-Mus101 interaction is also important in segregating DNA in meiosis.</p> / Dissertation

Legionella pneumophila, an intracellular pathogen of protozoa, is well known for its dimorphic life cycle that alternates between the vegetative replicative form (RF) and highly infectious cyst-like form (CLF). To this date several virulence factors including LpRpoS, LpIHF, and the Dot/Icm secretion system have been found to be required for the survival of L. pneumophila in macrophage and protozoa. Here we have identified and characterised Lpg1967, an orthologue of Pseudomonas PsrA in L. pneumophila. PsrA (Lpg1967) was found to regulate the expression of previously known virulence factors such non-coding RNAs, RsmY/Z, RpoS, LpIHF, flagella and Dot/Icm Type IV secretion system. In addition, the ΔpsrA mutant strain was unable to establish Legionella-containing vacuole and thus displayed a severe growth defect in the U937 derived macrophage cell line. Thus, PsrA was found to play an important role in controlling the regulatory cascade governing virulence in L. pneumophila. / October 2014

Protein – Protein interactions (PPIs) are thought to be conserved between species, although this has not been systematically investigated. This problem was explored in Escherichia coli from experimental data in Treponema pallidum by predicting PPIs, focusing on protein domains of little or unknown function. The comparison of T. pallidum to a model organism such as E. coli can not only reveal additional data about T. pallidum but also reveals how E. coli is similar to this distantly related, obligate parasite. A set of novel T. pallidum interactions, enriched for proteins of unknown function, were the basis of over 23,000 predicted homologous E. coli protein-protein and domain-domain interactions. Utilizing computational methods of protein analysis to define identity cross-species comparisons, this work shows that T. pallidum is nearly 61% similar to E. coli by orthologous groups (OG), demonstrating that what we knew of T. pallidum can be applied to E. coli. Observed binary interactions of that same pool of OGs result in only 4.3% shared T. pallidum interactions. Assigning function to proteins of unknown function leads to a greater understanding of how individual proteins relate to the larger interactome, the whole of interactions within a cell.

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