Microtubules (MT) are regulated by multiple categories of proteins, including proteins responsible for severing MTs that are therefore called MT-severing proteins. Studies of katanin, spastin, and fidgetin in animal systems have clarified that these proteins are MT-severing. However, studies in plants have been limited to katanin p60, and little is known about spastin or fidgetin and their function in plants. I looked at plant genomes to identify MT-severing protein homologues to clarify which severing proteins exist in plants. I obtained data from a variety of eukaryotic species to look for MT-severing proteins using homology to human proteins and analyzed these protein sequences to obtain information on the evolution of MT-severing proteins in different species. I focused this analysis on MT-severing proteins in the maize and Arabidopsis thaliana genomes. I created evolutionary phylogenetic trees for katanin-p60, katanin-p80, spastin, and fidgetin using sequences from animal, plant, and fungal genomes. I focused on Arabidopsis spastin and worked to understand its functionality by identifying protein interaction partners. The yeast two-hybrid technique was used to screen an Arabidopsis cDNA library to identify putative spastin interactors. I sought to confirm the putative protein interactions by using molecular tools for protein localization such as the YFP system. Finally, a Biomolecular Fluorescence Complementation (BiFC) assay was initiated as a proof of concept for confirmation of in vivo protein-protein interaction.

5 Abstract Ca2+/calmodulin-dependent protein kinase kinase 2 (CaMKK2) belongs to the serine/ threonine protein kinase family, which is involved in the calcium signaling pathway. The increase of intracellular calcium concentration induces the activation of calmodulin (CaM), which then activates its binding partners including CaMKII, CaMKIII, CaMKK1 and CaMKK2. CaMKK2 activates CaMKI, CaMKIV and AMP-dependent kinase, AMPK, by phosphorylation. CaMKK2 is naturally present in cells in an autoinhibited state, which is caused by the steric hindrance of the active site by the autoinhibitory domain. When calmodulin binds to the calmodulin-binding domain, the autoinhibitory domain is removed and the active site becomes accessible. Upon activation, CaMKK2 undergoes autophosphorylation, which increases its enzyme activity. Negative regulation of CaMKK2 is mediated by cAMP-dependent protein kinase A (PKA)- and GSK3-dependent phosphorylation. Sites phosphorylated by PKA have been identified for both CaMKK1 and CaMKK2. Two of them are also motifs recognized by scaffolding 14-3-3 proteins. Previous studies have shown that the 14-3-3 protein binding maintains phosphorylated CaMKK2 in an inhibited state by blocking the dephosphorylation of S495, which prevents the binding to calmodulin. However, it is unclear if it is the...

ASF1 est un chaperon d’histones H3-H4 impliqué dans de nombreux cancers. Comme bon nombre de protéines, ce chaperon exerce ses fonctions dans la cellule à travers des interactions protéine-protéine qu’il établit avec d’autres partenaires protéiques. La présente thèse porte sur le développement d’une stratégie originale de design de peptides inhibiteurs de ce type d’interactions souvent associées à des maladies. Cette stratégie rationnelle et itérative repose sur le couplage d’épitopes de liaison provenant de différents partenaires de l’interaction, et leur stabilisation par l’introduction de résidus « ancre » permettant ainsi d’engager un grand nombre de contacts avec la cible. L’extension de cette approche vers des peptidomimes permet par la suite de surmonter les obstacles liés à l’utilisation des peptides en thérapeutique tels que la biodisponibilité et la demi-vie. Appliquée au ciblage d’ASF1, cette méthode a permis de concevoir un peptide, ip4, présentant une affinité de 3nM pour sa cible, soit 3000 fois supérieure au partenaire naturel H3. Ce même peptide a été mimé avec succès par un composé, if3, de nature oligourée. Efficacement internalisés à l’aide d’une Cell Penetrating Peptide clivable, ces inhibiteurs présentent un effet antiprolifératif provoquant la mort des cellules cancéreuse, vraisemblablement dû au ciblage spécifique d’ASF1. / ASF1 is a histone H3-H4 chaperone implicated in several cancers. Like many proteins, this chaperone mediates its cellular functions through protein-protein interactions involving various protein partners. The present thesis focuses on the development of an original strategy to design inhibitory peptides targeting such disease-associated type of biological interactions. This rational and iterative strategy relies on the tethering of binding epitopes isolated from different partners, and stabilized by “anchor” residues that engage large number of atomic contacts with the target. The further progression of this approach toward a peptidomimetic strategy overcomes obstacles commonly associated to the therapeutic use of peptides such as biodisponibility and half-life. Applied for targeting ASF1, such method allowed the conception of a peptide, ip4, presenting a 3nM affinity for its target, which is 3000 fold higher than that of the natural partner H3. This peptide could be successfully mimicked by an oligourea structure, giving rise to the peptidomimetic if3. When coupled to a cleavable Cell Penetrating Peptide, these inhibitors displayed an on-target effect where they impeded cancerous cells proliferation, ultimately resulting in cells death.

Microarray technologies enable scientists to identify co-expressed genes at large scale. However, the gene expression analysis does not show functional relationships between co-expressed genes. There is a demand for effective approaches to analyse gene expression data to enable biological discoveries that can lead to identification of markers or therapeutic targets of many diseases. In cancer research, a number of gene expression screens have been carried out to identify genes differentially expressed in cancerous tissue such as Pancreatic Ductal Adenocarcinoma (PDAC). PDAC carries very poor prognosis, it eludes early detection and is characterised by its aggressiveness and resistance to currently available therapies. To identify molecular markers and suitable targets, there exist a research effort that maps differentially expressed genes to protein interactions to gain an understanding at systems level. Such interaction networks have a complex interconnected structure, whose the understanding of which is not a trivial task. Several formal approaches use simulation to support the investigation of such networks. These approaches suffer from the missing knowledge concerning biological systems. Reasoning in the other hand has the advantage of dealing with incomplete and partial information of the network knowledge. The initial approach adopted was to provide an algorithm that utilises a network-centric approach to pancreatic cancer, by re-constructing networks from known interactions and predicting novel protein interactions from structural templates. This method was applied to a data set of co-expressed PDAC genes. To this end, structural domains for the gene products are identified by using threading which is a 3D structure prediction technique. Next, the Protein Structure Interaction Database (SCOPPI), a database that classifies and annotates domain interactions derived from all known protein structures, is used to find templates of structurally interacting domains. Moreover, a network of related biological pathways for the PDAC data was constructed. In order to reason over molecular networks that are affected by dysregulation of gene expression, BioRevise was implemented. It is a belief revision system where the inhibition behaviour of reactions is modelled using extended logic programming. The system computes a minimal set of enzymes whose malfunction explains the abnormal expression levels of observed metabolites or enzymes. As a result of this research, two complementary approaches for the analysis of pancreatic cancer gene expression data are presented. Using the first approach, the pathways found to be largely affected in pancreatic cancer are signal transduction, actin cytoskeleton regulation, cell growth and cell communication. The analysis indicates that the alteration of the calcium pathway plays an important role in pancreas specific tumorigenesis. Furthermore, the structural prediction method reveals ~ 700 potential protein-protein interactions from the PDAC microarray data, among them, 81 novel interactions such as: serine/threonine kinase CDC2L1 interacting with cyclin-dependent kinase inhibitor CDKN3 and the tissue factor pathway inhibitor 2 (TFPI2) interacting with the transmembrane protease serine 4 (TMPRSS4). These resulting genes were further investigated and some were found to be potential therapeutic markers for PDAC. Since TMPRSS4 is involved in metastasis formation, it is hypothesised that the upregulation of TMPRSS4 and the downregulation of its predicted inhibitor TFPI2 plays an important role in this process. The predicted protein-protein network inspired the analysis of the data from two other perspectives. The resulting protein-protein interaction network highlighted the importance of the co-expression of KLK6 and KLK10 as prognostic factors for survival in PDAC as well as the construction of a PDAC specific apoptosis pathway to study different effects of multiple gene silencing in order to reactivate apoptosis in PDAC. Using the second approach, the behaviour of biological interaction networks using computational logic formalism was modelled, reasoning over the networks is enabled and the abnormal behaviour of its components is explained. The usability of the BioRevise system is demonstrated through two examples, a metabolic disorder disease and a deficiency in a pancreatic cancer associated pathway. The system successfully identified the inhibition of the enzyme glucose-6-phosphatase as responsible for the Glycogen storage disease type I, which according to literature is known to be the main reason for this disease. Furthermore, BioRevise was used to model reaction inhibition in the Glycolysis pathway which is known to be affected by Pancreatic cancer.

The D3 dopamine receptor (D3R) belongs to D2-class of dopamine receptors (DARs) and is involved in emotion, movement, and reward. D3R dysfunction has been reported in some neuropsychiatric disorders such as addiction, cognitive deficits, depression, schizophrenia, and Parkinson’s disease. Genetic studies have shown two polymorphic variants of the D3R gene resulting from substitution of serine to glycine at position nine of the amino terminus. Isoform 5 of adenylyl cyclase (AC5) is one of the nine transmembrane bound ACs in the brain and myocardium. Previous studies in rats have shown that AC5 is expressed in the striatum, nucleus accumbens and olfactory tubercle and at lower levels in islands of Calleja, where the D3R is also expressed. Previous studies showed that although D2R and D4R inhibit ACs activity in different cell types, inhibition of ACs by D3R is weak and often undetectable. It has been shown that D3R selectively inhibits AC5 activity in human embryonic kidney 293 (HEK293) cells co-transfected with D3R and AC5. Co-expression of D3R and AC5 in brain regions which are major coordinators of normal and pathological movement, and the selective inhibition of AC5 activity by D3R raise the possibility of a functional link between AC5 and D3R in the modulation of signal transduction and trafficking. I hypothesized that AC5 plays a unique role in modulation of D3R trafficking and signaling pathways through interaction between D3R and AC5. Herein, I demonstrated an interaction between D3R and AC5 in vivo and in vitro using reciprocal co-immunoprecipitation/immunoblotting (co-IP/IB) assays. Interestingly, DA may facilitate the formation of protein complex between D3R and AC5 in vitro. Radio ligand binding assays revealed that heterodimerization of D3R polymorphic variants with AC5 does not change ligand binding affinity and expression of the D3R. Furthermore, taking advantages of GloSensor assays, selective inhibition of AC5 activity by D3Ser9 and D3Gly9 has been shown following activation by DA and quinpirole. Using ELISA studies showed that AC5 promotes cell surface expression and total expression of D3Ser9 and D3Gly9. Moreover, ELISA results suggested that AC5 facilitates DA-induced D3Ser9 endocytosis in dynamin and β-arrestin 2 dependent process, while having no effect on D3Gly9 polymorphic variant. The results also revealed that AC5 attenuates heterologous (PKC-induced) internalization of D3Ser9, while it does not have any effect on D3Gly9 heterologous internalization. My results also displayed a complex formation between D3R, AC5 and, β-arrestin 2 under basal and DA stimulation conditions, which emphasize the role of β-arrestin 2 in D3R signal transduction. Overall, a new regulatory mechanism for D3R has been suggested. My results suggested that complex formation between both D3R polymorphic variants with AC5 can regulate signaling and trafficking properties of D3R without changing the binding affinity of the receptor. These data will be meaningful for understanding of diseases and developing treatment strategies.

Indiana University-Purdue University Indianapolis (IUPUI) / Protein-protein interactions play a crucial role in a wide range of biological processes. Research on the design and synthesis of small molecules to modulate these proteinprotein interactions can lead to new targets and drugs to modulate their function. In Chapter one, we discuss the design and synthesis of small molecules to probe a proteinprotein interaction in a voltage-gated Ca2+ channel. Virtual screening identified a compound (BTT-3) that contained a 3,4-dihydro-3,4’-pyrazole core. This compound had modest biological activity when tested in a fluorescence polarization (FP) assay. The synthetic route to BTT-3 consisted of six steps. In addition, analogs of BTT-3 were made for a structure-activity study to establish the importance of a carboxylate moiety. We also synthesized a biotinylated benzophenone photo-affinity probe and linked it to BTT-3 to identify additional protein targets of the compound. In Chapter two, small-molecule antagonists targeting uPA-uPAR protein-protein interaction are presented. A total of 500 commercially-available compounds were previously identified by virtual screening and tested by a FP assay. Three classes of compounds were found with biological activity. The first class of compounds contains pyrrolidone core structures represented by IPR- 1110, the second class has a novel pyrrolo[3,4-c]pyrazole ring system, represented by xv IPR-1283 and the last series had compounds with a 1,2-disubstituted 1,2- dihydropyrrolo[3,4-b]indol-3(4H)-one core structure, represented by IPR-540. Each of these three compounds were synthesized and assessed by FP and ELISA assays. A binding mode of IPR-1110 with uPA was subsequently proposed. Based on this binding mode, another 61 IPR-1110 derivatives were synthesized by us to illustrate the SAR activity. Analogs of the other two series were also synthesized.

<p>  G Protein Coupled Receptor (GPCR) signaling plays a key role in intercellular communication and regulates many physiological processes relevant to disease. Approximately 30-40% of all FDA approved drugs target GPCR pathways, but limitations and off-target side effects remain obstacles. Regulator of G protein Signaling (RGS) proteins negatively modulate GPCR signaling by accelerating deactivation of the Gα subunit and thus represent a novel alternative to current approaches. While research on RGS proteins and how they are regulated has expanded rapidly, there are still gaps in knowledge for some members of the RGS family. One example is RGS2, which is selective for Gαq signaling. Lowered RGS2 levels are implicated in numerous diseases, and while the E3 ligase responsible for facilitating degradation of RGS2 has been identified more work needs to be done to viably drug it to enhance RGS2 protein levels. In this thesis, I explore how FBXO44, an E3 ligase substrate recognition component responsible for RGS2 degradation, interacts with RGS2 to explore approaches to inhibit degradation.</p> <p><br></p> <p>While the FBXO44-RGS2 interaction has been demonstrated previously, the degron sequence of RGS2 remained unknown. We hypothesized that FBXO44 binds RGS2 at its Nterminus and investigated this using N-terminally truncated RGS2 constructs. Our results indicated that FBXO44 binds between residues 5 and 16 of RGS2, as removal of these stabilized RGS2 against proteasomal degradation. Based on these results we designed a peptide microarray to identify important residues and properties for FBXO44 in vitro and found that Cys13 is essential for FBXO44 binding.</p> <p><br></p> <p>We also developed and optimized a high-throughput split luciferase screen to identify potential inhibitors of the FBXO44-RGS2 interaction. After forming a cell-line stably expressing tagged FBXO44 and RGS2 and optimizing assay condition, we achieved a robust assay for screening as determined by Z’-factor. <br>  </p>

No description available.

<p dir="ltr">Ebola virus is an enveloped filamentous shaped RNA virus which causes severe hemorrhagic fever in humans. Multiple outbreaks of different strains of ebolavirus have been reported in the past years with limited therapeutics available for treatment. Despite some advances in treatment, there remains a lack of knowledge about the mechanisms of ebolavirus replication in host cells.</p><p dir="ltr">Ebolavirus encodes for seven structural proteins with matrix protein (VP40) being the most abundantly expressed viral protein. VP40 is essential for viral assembly and budding as expression of VP40 alone is sufficient for formation of virus-like particles (VLPs). VP40 also disassembles during viral entry to help in viral and host cell membrane fusion. Oligomerization of VP40 has been reported to decrease viral replication and transcription. VP40 can perform these diverse functions by virtue of changes in conformation and oligomerization state. VP40 predominantly exists as a dimer through hydrophobic interactions between the alpha helices of the two protomers. Furthermore, VP40 oligomerizes into a hexamer which serves as the structural unit for cylindrical matrix layer formation. VP40 also forms a ring-shaped octamer for regulation of viral transcription. The different oligomeric forms of VP40 exist in an equilibrium for successful viral infection. However, the exact mechanism of formation, stability, and energetics of conversion between these oligomeric forms is unknown.</p><p dir="ltr">In this study, we performed biophysical analysis on the dimerization interface and identified keystone interactions which when abrogated lead to complete disruption of dimer interface. In addition, peptidomimetics approach was used to design and synthesize a library of compounds to probe the dimerization interface. The compounds were screened using thermal shift assay and then compared using MST and ITC studies. We identified that a peptide mimicking the alpha helical region stabilized by a p-xylene di-cysteine staple was able to bind to VP40 dimer. We also determined that this peptide binds near the dimer interface and was able to slightly shift equilibrium of VP40 dimer towards monomer formation.</p><p dir="ltr">Overall, this report sheds light on critical interactions required for VP40 dimer formation and stability and introduces use of peptidomimetics to probe for VP40 dimerization interface to understand energetics of oligomerization equilibrium, thereby increasing our knowledge about disease mechanism and paving way for development of therapeutics.</p>

Proteins are indispensable players in virtually all biological events. The functions of proteins are determined by their three dimensional (3D) structure and coordinated through intricate networks of protein-protein interactions (PPIs). Hence, a deep comprehension of such networks turns out to be crucial for understanding the cellular biology. Computational approaches have become critical tools for analysing PPI networks. In silico methods take advantage of the existing PPI knowledge to both predict new interactions and predict the function of proteins. Regarding the task of predicting PPIs, several methods have been already developed. However, recent findings demonstrate that such methods could take advantage of the knowledge on non-interacting protein pairs (NIPs). On the task of predicting the function of proteins,the Guilt-by-Association (GBA) principle can be exploited to extend the functional annotation of proteins over PPI networks. In this thesis, a new algorithm for PPI prediction and a protocol to complete cell signalling networks are presented. iLoops is a method that uses NIP data and structural information of proteins to predict the binding fate of protein pairs. A novel protocol for completing signalling networks –a task related to predicting the function of a protein, has also been developed. The protocol is based on the application of GBA principle in PPI networks. / Les proteïnes tenen un paper indispensable en virtualment qualsevol procés biològic. Les funcions de les proteïnes estan determinades per la seva estructura tridimensional (3D) i són coordinades per mitjà d’una complexa xarxa d’interaccions protiques (en anglès, protein-protein interactions, PPIs). Axí doncs, una comprensió en profunditat d’aquestes xarxes és fonamental per entendre la biologia cel•lular. Per a l’anàlisi de les xarxes d’interacció de proteïnes, l’ús de tècniques computacionals ha esdevingut fonamental als darrers temps. Els mètodes in silico aprofiten el coneixement actual sobre les interaccions proteiques per fer prediccions de noves interaccions o de les funcions de les proteïnes. Actualment existeixen diferents mètodes per a la predicció de noves interaccions de proteines. De tota manera, resultats recents demostren que aquests mètodes poden beneficiar-se del coneixement sobre parelles de proteïnes no interaccionants (en anglès, non-interacting pairs, NIPs). Per a la tasca de predir la funció de les proteïnes, el principi de “culpable per associació” (en anglès, guilt by association, GBA) és usat per extendre l’anotació de proteïnes de funció coneguda a través de xarxes d’interacció de proteïnes. En aquesta tesi es presenta un nou mètode pre a la predicció d’interaccions proteiques i un nou protocol basat per a completar xarxes de senyalització cel•lular. iLoops és un mètode que utilitza dades de parells no interaccionants i coneixement de l’estructura 3D de les proteïnes per a predir interaccions de proteïnes. També s’ha desenvolupat un nou protocol per a completar xarxes de senyalització cel•lular, una tasca relacionada amb la predicció de les funcions de les proteïnes. Aquest protocol es basa en aplicar el principi GBA a xarxes d’interaccions proteiques.