Le terme de sulfoprotéomique est utilisé pour désigner l’étude de la sulfatation des protéines. Bien que la sulfatation soit depuis peu considérée comme une MPT d’une importance majeure, il y a toujours peu de travaux scientifiques qui y sont consacrés en comparaison avec ce qui se fait sur la phosphorylation notamment. Ce retard s’explique notamment par la difficulté à analyser les espèces protéiques sulfatées dans les conditions classiques utilisées en protéomique, notamment par spectrométrie de masse. Ces travaux de thèse visent justement à développer des méthodes d’analyses par spectrométrie de masse dédiées à l’étude de la sulfatation des protéines, afin d’augmenter le champ des connaissances de cette MPT. Pour cela, nous avons largement utilisé le mode d’ionisation négatif, très peu, voire jamais utilisé en protéomique, avec deux techniques de fragmentation pour réaliser des spectres MS/MS, à savoir les fragmentations CID et HCD. Les résultats obtenus nous ont permis de mettre en évidence une méthode d’analyse permettant la formation d’ions spécifiques de la sulfatation et de la phosphorylation (qui sont isobariques), permettant ainsi une identification certaine de chacune des deux MPTs. Nous avons également entrepris d’étudier le rôle de la sulfatation d’un récepteur cellulaire, CXCR4, dans son interaction avec son ligand naturel, la chimiokine SDF-1/CXCL12. Cette étude a été menée par électrophorèse capillaire, et pourra constituer une base de travail solide pour des futures analyses mettant en œuvre le couplage entre l’électrophorèse capillaire et la spectrométrie de masse pour une meilleure caractérisation des complexes formés entre les partenaires protéiques. / Sulfoproteomics term designs protein sulfation studies. It appears during the 2000’s, when the interest for others Post-Translational Modifications (PTMs) than phosphorylation and glycosylation was growing up. Even though sulfation is thought to be an important PTM, a weak number of publications has emerged about it, notably if we compare with the huge quantity of phosphorylation papers. This difference is mainly due to the difficulty to correctly analyze sulfated proteins and peptides in the classical ways of proteomics, as in mass spectrometry for example. The goal of this thesis is to develop mass spectrometry methods dedicated to the characterization of sulfated species, in order to improve the knowledge of this PTM. To do that, we have mainly used negative ion mode, which is almost never used, with two fragmentations techniques for the MS/MS spectra, which are CID and HCD. Results obtained allow us to pinpoint an analytical method allowing the differentiation between sulfation and phosphorylation (they are isobaric), based on the presence of specific ion for each PTM in MS/MS. In another part of the project, we have investigated the role of sulfation in the interaction between a cellular receptor, CXCR4, and its in vivo ligand, the chemokine SDF-1/CXCL12. We used capillary electrophoresis for this work, and it could be a good basis for future analyses using capillary electrophoresis coupled with mass spectrometry, in order to have a better characterization of the observed complexes.

Alternative splicing of pre-mRNA is a critical mechanism for enabling genetic diversity, and is a carefully regulated process in neuronal differentiation. RNA binding proteins (RBPs) are developmentally expressed and physically interact with RNA to drive specific splicing changes. This work tests the hypothesis that RBP-RNA interactions are critical for regulating timed and coordinated alternative splicing changes during neurodevelopment and that these splicing changes are in turn part of major regulatory mechanisms that underlie morphological and functional maturation of neurons. I describe our efforts to identify functional RBP-RNA interactions, including the identification of previously unobserved splicing events, and explore the combinatorial roles of multiple brain-specific RBPs during development. Using integrative modeling that combines multiple sources of data, we find hundreds of regulated splicing events for each of RBFOX, NOVA, PTBP, and MBNL. In the neurodevelopmental context, we find that the proteins control different sets of exons, with RBFOX, NOVA, and PTBP regulating early splicing changes and MBNL largely regulating later splicing changes. These findings additionally led to the observation that CNS and sensory neurons express a variety of different RBP programs, with many sensory neurons expressing a less mature splicing pattern than CNS neurons. We also establish a foundation for further exploration of neurodevelopmental splicing, by investigating the regulation of previously unobserved splicing events.

轉錄因子(TF) 和轉錄因子結合位點(TFBS) 之間的結合(binding) 是重要的生物信息學課題。高清晰度(長度<10 )的結合核心(binding core) 是從昂貴和費時的三維結構實驗中發現的。因此，我們希望開發一種以序列為基礎的高效計算方法，提供高信心的結合核心作為實驗對象，以提高三維結構實驗的效率。雖然現有很多基於序列的motif辨認算法，但很少有直接針對關聯TF和TFBS的結合核心的。在不使用任何三維結構的結合核心下，最近我們應用了關聯規則挖掘方法於低分辨率的(TF長度>490) 結合序列準確地發掘出高清晰度結合核心，然而，這種方法有幾個缺點。在這篇論文中，我們正式地定義了使用關聯規則挖掘預測蛋白質-脫氧核糖核酸(DNA) 結合核心的問題和開發了一個以樹為基礎的算法以克服前一種方法的缺點。 / 目前的關聯規則挖掘方法在這個問題上只能解決確切的序列，而最近的近似方法並沒有採用任何正式的模型，並且受限於實驗已知的序列。由於生物的基因突變是常見的，因此我們進一步定義開採近似的蛋白質-DNA序列結合核心的問題，並延伸該算法至預測近似的蛋白質-DNA結合核心。真實數據的實驗結果中表明了在該算法在預測新的TF-TFBS結合核心中的性能和適用性。最後，我們提出、測試並討論了多種減少雜訊以提高結果質量的方案。其中，當最小支持度(minimumsupport) 的限制定得低時，統計檢驗能有效地從結果中删除雜訊。 / The studies of protein-DNA bindings between transcription fac-tors (TFs) and transcription factor binding sites (TFBSs) are important bioinformatics topics. Currently, high-resolution (length < 10) TF-TFBS binding cores are discovered by expensive and time-consuming 3D structure experiments. Thus, we are motivated to develop a cheap and efficient sequence-based computational method for providing testable novel binding cores with high condence to accelerate the experiments. Although there are abundant sequence-based motif discovery algorithms, few directly address associating both TF and TFBS core motifs, which are both veriable on 3D structures. Recent association rule mining approaches on low-resolution binding sequences (TF length > 490) are shown promising in identifying accurate binding cores without using any 3D structures, however, the approach has several drawbacks. In this thesis, the problem of predicting protein-DNA binding cores using association rule mining is formally dened and a novel tree-based algorithm is developed to overcome the disadvantages of the previous approach. / While the previous association rule mining method on this problem addresses exact sequences only, the most recent ad hoc method for approximation does not establish any formal model and is limited by experimentally known patterns. As biological mutations are common, it is desirable to formally extend the exact model into an approximate one. Thus, we further formalize the problem of mining approximate protein-DNA association rules from sequence data and extend the proposed algorithm to predict approximate protein-DNA binding cores. Experimental results on real data show the performance and applicability of the proposed algorithm in predicting novel TF-TFBS binding cores. Finally, several methods for reducing noise and thus improving the quality of the mined rules are proposed and discussed. Particularly, statistical tests give impressive result on removing noise when the minimum support threshold is small. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wong, Po Yuen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 126-136). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Predicting Protein-DNA Binding Cores --- p.1 / Chapter 1.2 --- Contributions --- p.3 / Chapter 1.3 --- Thesis Outline --- p.4 / Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Biological Background --- p.7 / Chapter 2.1.1 --- The Central Dogma of Molecular Biology --- p.7 / Chapter 2.1.2 --- Transcriptional Regulation --- p.10 / Chapter 2.1.3 --- Experiments on studying TF-TFBS bindings --- p.12 / Chapter 2.2 --- Computational Background --- p.13 / Chapter 2.2.1 --- Motif Discovery --- p.13 / Chapter 2.2.2 --- Association Rule Mining --- p.14 / Chapter 2.2.3 --- Frequent Pattern Mining --- p.16 / Chapter 2.3 --- TF-TFBS Binding Rule Mining in Bioinformatics --- p.17 / Chapter 3 --- Mining TF-TFBS Rules --- p.23 / Chapter 3.1 --- Introduction --- p.24 / Chapter 3.2 --- Problem Definition --- p.25 / Chapter 3.3 --- Frequent Sequence Tree (FS-Tree) --- p.31 / Chapter 3.3.1 --- Semantic of FS-Tree --- p.31 / Chapter 3.3.2 --- Construction of FS-Tree --- p.34 / Chapter 3.4 --- The algorithm --- p.40 / Chapter 3.4.1 --- Correctness --- p.42 / Chapter 3.5 --- Results --- p.44 / Chapter 3.5.1 --- Performance --- p.45 / Chapter 3.5.2 --- Verification using 3D-Structures --- p.53 / Chapter 3.6 --- Discussion and Conclusion --- p.58 / Chapter 3.6.1 --- Parameters Setting --- p.59 / Chapter 3.6.2 --- Deduplication --- p.60 / Chapter 4 --- Extension to Approximate TF-TFBS Rules --- p.63 / Chapter 4.1 --- Introduction --- p.65 / Chapter 4.2 --- Problem Definition --- p.66 / Chapter 4.3 --- Frequent Sequence Class Tree --- p.74 / Chapter 4.4 --- The extended algorithm --- p.82 / Chapter 4.4.1 --- Correctness --- p.87 / Chapter 4.5 --- Results --- p.89 / Chapter 4.5.1 --- Performance --- p.89 / Chapter 4.5.2 --- Verification using PDB --- p.94 / Chapter 4.6 --- Discussion and Conclusion --- p.100 / Chapter 5 --- Noise Reducing Methods --- p.102 / Chapter 5.1 --- Introduction --- p.103 / Chapter 5.2 --- Reducing Noise within a TFBS Group --- p.104 / Chapter 5.2.1 --- Using Exact Count Threshold --- p.106 / Chapter 5.2.2 --- Using Minimum Support --- p.108 / Chapter 5.2.3 --- Using Minimum Approximate Support --- p.110 / Chapter 5.3 --- Reducing Noise using Statistical Test --- p.112 / Chapter 5.3.1 --- A Simple Model --- p.114 / Chapter 5.3.2 --- Statistical Model with Transactions --- p.116 / Chapter 5.4 --- Discussion and Conclusion --- p.120 / Chapter 6 --- Conclusion --- p.121 / Chapter 6.1 --- Conclusion --- p.121 / Chapter 6.2 --- Future Work --- p.123 / Bibliography --- p.126 / Chapter A --- Publications --- p.137 / Chapter A.1 --- Publications --- p.137

氫化酶作為一種催化劑，能催化氫分子成為質子及電子的相互轉換。 [鎳鐵]- 氫化酶散播最廣的一種氫化酶，從古菌到細菌都能找到 [鎳鐵]- 氫化酶。完整成熟的 [鎳鐵]-氫化酶需要插入鐵、氰化物、一氧化碳以及鎳到它的催化核心。這複雜的過程需要其它由若干 hyp 基因編譯的輔助蛋白酶的幫助，其中蛋白HypA 與 HypB 負責將鎳運送到[鎳鐵] -氫化酶的催化核心。敲除了 hypA 或hypB 基因的細菌株缺失[鎳鐵] -氫化酶的活性，如在生長介質裡添補鎳可恢復部份[鎳鐵] -氫化酶的活性。當HypB 與鳥嘌呤核苷酸結合時會變成蛋白二聚體。對比HypB 脫輔基蛋白及與HypB 與鳥嘌呤三核苷酸類似物的蛋白複合物的晶體結構可發現，HypB 透過一個保守賴氨酸殘基( Archaeoglobus fulgidus HypB 的殘基 148 )組成分子間鹽橋以構成蛋白二聚體。Escherichia coli 的體內實驗顯示，此保守賴氨酸殘基對活性氫化酶的製造起必要的作用，反映由此殘基所構成的鹽橋對HypB 功能的重要性。此外，本研究展示了A. fulgidusHypA 及 HypB 蛋白之間的相互作用。通過在A. fulgidus HypB 上進行系統性的突變，發現HypB 利用其GTP 酶域上的一段氨基端區域與HypA 相互作用。跟據這個結果，我們進而在E. coli HypB 上發現了兩個保守的非極性殘基與HypA 相互作用。當以丙氨酸取代在HypB 上的這兩個非極性殘基時，HypB 無法激活E. coli 中的氫化酶，導置降低的氫化酶活性，這表明了HypA 和HypB 的相互作用對[鎳鐵] -氫化酶成熟過程的必要性。 / Hydrogenases catalyze the inter-conversion of molecular hydrogen into protons and electrons. [NiFe]-hydrogenase is the most widely distributed hydrogenases, which is found in organisms ranging from archaea to bacteria. Maturation of [NiFe]-hydrogenase requires the insertion of iron, cyanide and carbon monoxide, followed by nickel, to the catalytic core of the enzyme. The maturation process of hydrogenase is a complicated procedure, which requires many accessory proteins encoded by hyp genes. HypA and HypB participate in the nickel delivery step to the catalytic core of hydrogenase, which is supported by the fact that strain deficient in hypA or hypB gene lack hydrogenase activity which can be recovered partially by elevating nickel content in the medium. HypB is capable to form dimer in solution upon guanine nucleotide binding. By comparing the crystal structures of HypB in dimer and monomer form, an important lysine residue (residue 148 in A. fulgidus HypB) which is required to form an intermolecular salt bridge during GTP-dependent dimerization, has been identified. Substitution of this lysine resiue with alanie would break HypB dimer in vitro. In vivo complementation study in E. coli showed that the corresponding lysine residue in E. coli HypB is required for active hydrogenase production indicating the importance of this intermolecular salt bridge to the biological function of HypB. Besides, interaction between A. fulgidus HypA and HypB are demonstrated in this work. By making systematic mutation to A. fulgidus HypB, the N‐terminal region of the GTPase‐domain has been identified to be important for its interaction with HypA. Further mutagenesis study has been done on E. coli HypB and two conserved non‐polar residues responsible for interaction with HypA have been identified. Alanine substitution of these conserved non‐polar residues result in HypB mutants which failed to rescue hydrogenase activity in vivo in E. coli showing that HypA/HypB interaction is required for hydrogenase maturation. / Detailed summary in vernacular field only. / Chan, Kwok Ho. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 88-95). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Chapter Chapter 1 --- Introduction: Hydrogenase biosynthesis requires insertion of nickel facilitated by protein HypA and HypB --- p.1 / Chapter 1.1 --- What is hydrogenase? --- p.1 / Chapter 1.2 --- [NiFe] hydrogenase contains a complex catalytic core composed of metal atoms and diatomic ligands --- p.2 / Chapter 1.3 --- The [NiFe] catalytic core --- p.4 / Chapter 1.4 --- Building the catalytic [NiFe] core --- p.4 / Chapter 1.5 --- Nickel insertion into the hydrogenase precursor involves the proteins HypB, HypA and SlyD --- p.7 / Chapter 1.5.1 --- Protein HypB --- p.7 / Chapter 1.5.2 --- Protein HypA --- p.11 / Chapter 1.5.3 --- Protein SlyD --- p.12 / Chapter 1.6 --- Objectives - How HypB dimerization and HypA/HypB interaction are involved in hydrogenase maturation process? --- p.13 / Chapter Chapter 2 --- A conserved Lys residue is required for GTP-dependent dimerization and hydrogenase maturation --- p.17 / Chapter 2.1 --- Introduction --- p.17 / Chapter 2.2 --- Materials and Methods --- p.22 / Chapter 2.2.1 --- Recombinant Plasmid Construction --- p.22 / Chapter 2.2.2 --- HypB mutant construction by site-directed Mutagenesis --- p.22 / Chapter 2.2.3 --- Protein Expression and purification --- p.23 / Chapter 2.2.4 --- HypB protein purification --- p.23 / Chapter 2.2.5 --- Analytical gel filtration chromatography coupled with Light Scattering (SEC/LS) --- p.24 / Chapter 2.2.6 --- Nucleotide binding affinity determination --- p.25 / Chapter 2.2.7 --- GTPase activity determination --- p.26 / Chapter 2.2.8 --- Sample preparation for hydrogenase activity assay --- p.26 / Chapter 2.2.9 --- Hydrogenase activity determination --- p.27 / Chapter 2.3 --- Results --- p.29 / Chapter 2.3.1 --- AfHypB undergoes GTP-dependent dimerization --- p.29 / Chapter 2.3.2 --- Analysis of Structural difference between the apo form and GTP S-bound form suggests a mechanism of GTP-dependent dimerization for HypB --- p.30 / Chapter 2.3.3 --- Lys-148 is essential for GTP-dependent dimerization --- p.31 / Chapter 2.3.4 --- Disruption of dimerization by K148 mutation did not affect nucleotide binding and GTP hydrolysis activity significantly --- p.32 / Chapter 2.3.5 --- The conserved lysine residue is required for hydrogenase maturation in E. coli --- p.33 / Chapter 2.4 --- Discussion --- p.45 / Chapter 2.4.1 --- A conserved intermolecular salt‐bridge is required for GTP-dependent dimerization of HypB and hydrogenase maturation --- p.45 / Chapter 2.4.2 --- The extra metal binding site at the dimeric interface of HypB may provide a mechanism of why GTP-dependent dimerization is essential to Ni insertion --- p.46 / Chapter Chapter 3 --- N-terminal region of GTPase‐domain of HypB is required for interaction with HypA --- p.51 / Chapter 3.1 --- Introduction --- p.51 / Chapter 3.2 --- Methods and materials --- p.53 / Chapter 3.2.1 --- Recombinant Plasmid Construction --- p.53 / Chapter 3.2.2 --- HypB variant construction by site‐directed Mutagenesis --- p.53 / Chapter 3.2.3 --- Protein Expression --- p.54 / Chapter 3.2.4 --- Tag‐free AfHypA and AfHypB purification --- p.54 / Chapter 3.2.5 --- Analytical size exclusion chromatography coupled with Light Scattering --- p.54 / Chapter 3.2.6 --- GST pull‐down of GST‐AfHypA and AfHypB --- p.55 / Chapter 3.2.7 --- Tandem affinity pull‐down of GST‐EcHypA and His‐SUMO‐EcHypB --- p.55 / Chapter 3.2.8 --- GST pull‐down of GST‐EcHypA and His‐SUMO‐EcHypB --- p.56 / Chapter 3.2.9 --- Hydrogenase activity determination --- p.57 / Chapter 3.3 --- Results --- p.58 / Chapter 3.3.1 --- HypA and HypB from A. fulgidus form 1:1 heterodimer in solution --- p.58 / Chapter 3.3.2 --- The N‐terminal regions upstream of the first helix of A. fulgidus HypB is required for HypA-HypB interaction --- p.59 / Chapter 3.3.3 --- Two conserved hydrophobic residues on HypB from E. coli are required to interact with HypA --- p.60 / Chapter 3.3.4 --- HypA-HypB interaction is required for hydrogenase maturation in E. coli --- p.62 / Chapter 3.4 --- Discussion --- p.73 / Chapter 3.4.1 --- The N‐terminal region of the GTPase domain is required for interaction with HypA and hydrogenase maturation in E. coli --- p.73 / Chapter 3.4.2 --- Location of interaction site on HypB reveals possible role for HypA/HypB interaction --- p.74 / Chapter 3.4.3 --- Mode of specific interaction with HypA: Interaction via a disordered region implies a coupled folding and binding process --- p.75 / Chapter Chapter 4 --- Conclusion and Future Perspectives --- p.80 / Chapter A1.1 --- Summary of findings in this work --- p.80 / Chapter A1.2 --- Implications in hydrogenase maturation --- p.81 / Chapter A1.3 --- Questions unresolved --- p.82 / Chapter 4.3.1 --- Factors that activate GTPase activity of HypB are still elusive --- p.82 / Chapter 4.3.2 --- How nickel delivery is regulated by HypA/HypB complex is still unclear --- p.83 / References --- p.88 / Chapter Appendix 1 --- Preliminary results of HypA/HypB protein complex structural study --- p.96 / Chapter A1.1 --- Structural study may provide invaluable insights to the role of HypA‐HypB interaction --- p.96 / Chapter A1.2 --- X‐ray crystallography as an approach to determine HypA/HypB complex structure --- p.96 / Chapter A1.3 --- Initial crystal hits were obtained with purified AfHypA/HypB complex --- p.97 / Chapter Appendix 2 --- Publications associated to the thesis --- p.100 / Chapter Appendix 3 --- Constructs and Primers used --- p.101

Termination of protein synthesis occurs in response to the translocation of a stop codon (UAA, UAG or UGA) into the A site of the ribosome. Unlike sense codons, stop signals in the mRNA are recognized by two classes of specialized proteins called release factors (RFs): the class I or decoding RF, which recognizes the stop codon and promotes peptidyl-tRNA hydrolysis and class II RF, a G-protein that promotes the dissociation of the decoding RF from the ribosome. The discovery that stop codons are decoded by a protein factor rather than a specific tRNA opened up the possibility that the signal for termination of protein synthesis might extend beyond the stop codon itself. Biochemical and genetic experiments in prokaryotes confirmed that bias in nucleotide usage around stop codons correlates with translation termination efficiency. The objective of the current investigation was to define the eukaryotic termination signal by determining the bias in the nucleotide sequence surrounding eukaryotic stop codons and to identify whether this was a determinant of translation termination efficiency. Bioinformatic analysis of five diverse eukaryotic genomes was undertaken to identify potential eukaryotic translation termination signal elements. Significant nucleotide bias was identified both 5� and 3� of the stop codon in all the genomes investigated. Correlations were identified between nucleotide bias and gene expression levels, and between nucleotide bias and natural recoding sites predicting that nucleotides 5� and 3� of the stop codon affect termination efficiency. These correlations were common to all organisms investigated and suggested the existence of a eukaryotic termination signal. Termination signals identified from the bioinformatic analysis were assayed to determine the efficiency of termination in an in vitro dual luciferase reporter assay. Results indicated that nucleotides both 5� and 3� of the stop codon could significantly alter termination signal efficiency, although readthrough did not vary by greater than 1%. The effect of nucleotides 3� to the stop codon on termination efficiency was investigated further in mammalian cultured cells using the dual luciferase reporter assay. Results showed a significant relationship between the identity of these nucleotides and observed termination efficiencies with nucleotides at positions +4 and +8 giving the strongest correlation. Termination sequence elements of the form UGA CUN NCN mediated up to 5% readthrough in cultured cells. Investigations into the underlying mechanisms that were responsible for the variation in termination efficiency were also undertaken. Co-transfection of specific suppressor tRNAs enhanced but did not change the pattern of observed termination efficiency, indicating that the mechanisms mediated by the termination signal element was not mediated through suppressor tRNA binding. Alignments of 18S rRNA sequences indicated potential extensive interactions between the rRNA and the mRNA termination signal element. Experiments that assessed the effect of eRF1 levels on termination at inefficient termination signals in vitro revealed that increased levels of eRF1 could improve termination efficiency. These results indicate that, as in prokaryotes, specific nucleotides beyond the stop codon modulate translation termination efficiency in eukaryotes, and that the translation termination signal should be considered a sequence element.

Protein:protein interactions are central to the regulation of the intrinsic programmed cell death (apoptosis) pathway. Opposing members of the Bcl-2 family of proteins, which have distinct sequence features, interact with each other on the outer mitochondrial membrane to regulate apoptosis. Pro-survival proteins such as Bcl-2, Bcl-x[L], Bcl-w, Mcl-1 and A1 protect cells from apoptosis and contain up to four regions of homology to Bcl-2 (Bcl-2 homology domains 1 - 4, BH1-4). Pro-apoptotic BH3-only proteins such as Bim, Puma, Noxa, Bad, Bmf, and Bid promote apoptosis by interacting with and inactivating pro-survival proteins, and contain just the BH3-domain. The pro-apoptotic proteins Bax and Bak are essential for apoptosis and contain three regions of homology to Bcl-2 (the BH1-, BH2- and BH3-domains). In this study, two different sets of interactions involving pro-survival proteins were investigated. Initially, the pro-apoptotic protein Bnip3 was examined to determine if it was a mitochondrial anchor for the pro-survival protein Bcl-w. Secondly, to characterise the interactions between a pro-survival protein and different BH3-domains, structures were solved of the pro-survival protein A1 in complex with four different BH3-domains. In the structure of Bcl-w, the hydrophobic C-terminus is bound to its own BH3-domain binding groove. This location of the C-terminus is consistent with the observation that Bcl-w is only loosely associated with the outer mitochondrial membrane in healthy cells. Upon interaction of Bcl-w with a BH3-domain, Bcl-w becomes tightly associated with the mitochondrial membrane, presumably due to displacement of the C-terminal residues by the BH3-only protein. In healthy cells it has been suggested that Bcl-w is associated with the membrane due to an interaction with an unidentified membrane protein, which preliminary experiments suggested may be Bnip3. Protein interaction experiments performed in vitro and in vivo did not reveal an interaction between Bnip3 and Bcl-w. It was originally thought that each pro-apoptotic BH3-only protein could interact with all pro-survival proteins. However, it has recently become clear that there is selectivity within the pathway suggesting functional groupings. Bim and Puma behave as originally predicted and can interact with all pro-survival proteins and are potent killers. In contrast, Noxa and Bad interact with distinct subsets of pro-survival proteins. Noxa only binds Mcl-1 and A1, while Bad binds Bcl-2, Bcl-x[L] and Bcl-w. As a result, either Noxa or Bad acting alone is a weak killer, but together they are potent. Other BH3-only proteins bind tightly to some pro-survival proteins and weakly to others. The diversity that exists between BH3-domain sequences precludes sequence-based identification of the determinants of specificity. In this study, crystal structures of A1:Puma BH3-domain, A1:Bmf BH3-domain, A1:Bak BH3-domain and A1:Bid BH3-domain complexes have been solved. Differences identified between these structures explain some of the variation in affinities observed in pro-survival protein:BH3-domain complexes. These observations, in combination with published data, suggest that BH3-domains bind weakly when the optimal interactions with conserved residues cannot be formed. Additionally, differences were observed in the A1:Bak BH3-domain structure that may be functionally important for the regulation of Bak.

Thesis (Ph. D.)--Washington State University, December 2007. / Includes bibliographical references (p. 98-107).

Graduation date: 1999

Graduation date: 2000

Graduation date: 1996