A key prerequisite for a deeper understanding of biological processes at molecular level is a detailed description of the three-dimensional structure of interaction partners and their complexes. We adopted the IFN-γ complex as our model system. Even though IFN-γ is one of the key modulators of the immunity response, which has been studied intensively for more than 60 years, the structure of the accessory receptor chain and the understanding of the IFN-γ complex is still lacking. In this work we firstly discussed the binary system between IFN-γ and its high affinity receptor R1 which is structurally known. Using a new innovative methodology we focused on the modulation of the affinity between IFN-γ and its receptor R1. Our approach was based on the modulation of protein - protein stability by mutating cavities in the proteins' structure and increasing the affinity about seven-fold. Secondly, we crystallized and solved the structure of the IFN-γ receptor 2, the accessory receptor molecule. Our analysis of variable residues on the surface of the structures of type II family receptors, to which receptor 2 belongs, revealed the putative binding site for IFN-γ. In the third part of our work, we crystallized IFN-γ from olive flounder Paralichthys olivaceus and solved its structure at 2.3 Å resolution (PDB...

Protein folding studies have provided important insights about the key role of non-covalent interactions in protein structure and conformational stability. Some of these interactions include salt bridges, cation-π, and anion-Ï€ interactions. Understanding these interactions is crucial to developing methods for predicting protein secondary, tertiary, quaternary structure from primary sequence and understanding protein-protein interactions and protein-ligand interactions. Several studies have described how the interaction between two amino acid side chains have a substantial effect on protein structure and conformational stability. This is under the assumption that the interaction between the two amino acids is independent of surrounding interactions. We are interested in understanding how salt bridges, cation-π, and anion-π interactions affect each other when they are in close proximity. Chapter 1 is a brief introduction on noncovalent interactions and noncovalent interaction cooperativity. Chapter 2 describes the progress we have made measuring the cooperativity between noncovalent interactions involving cations, anions and aromatic amino acids in a coiled-coil alpha helix model protein. Chapter 3 describes cooperativity between cation, anion, and nonaromatic hydrophobic amino acids in the context of a coiled-coil alpha helix. In chapter 4 we describe a strong anion-π interaction in a reverse turn that stabilizes a beta sheet model protein. In chapter 5 we measure the interaction between a cysteine linked maleimide and two lysines in a helix and show that it is a general strategy to stabilize helical structure.

Protein solution structures were analyzed by horizontal attenuated total reflectance (ATR) FTIR spectroscopy. Secondary structure compositions determined from analyses of amide-I and II region and amide-III region difference spectra were compared. Data for proteins of known solution structure, cytochrome c, concanavalin A and lysozyme, were compared with those reported in the iiterature. Melittin, a peptide from bee venom whose secondary structural configuration varies depending upon solution conditions was also examined. Acyl-carrier protein (ACP) is a small protein of recognized dynamic structure that in its diverse physiologic roles interacts specifically with numerous different proteins. Horizontal ATR FTIR analysis of ACP's secondary structure indicated a predominately helical structure best defined as a combination of ordered and disordered helices. The FTIR-derived structural composition agreed with those determined for ACP by other techniques. Comparison of independent analyses of the amide-I and III regions to determine protein configuration compositions was a useful method of verifying the internal consistency of the calculated structural compositions of dynamically-structured proteins.

Flavonoid glycosides are required for a number of crucial roles in planta and have the potential for development in a variety of agricultural, medicinal, and biotechnological applications. A number of recent advancements have been made in characterizing glycosyltransferases, the enzymes that are responsible for the synthesis of these important molecules. In this review, glycosyltransferases are considered with regard to biochemical properties, expression patterns, levels of enzyme activity during development, and structure/function relationships. This is presented with historical context to highlight critical findings, particularly with regard to the innovative work that has come from research on citrus species. The plant glycosyltransferase crystal structures that have been solved over the past decade, either alone or in complex with sugar donor and/or acceptor molecules, are discussed. The application of results from these structures to inform current structure/function work as well as implications and goals for future crystallography and tertiary modeling studies are considered. A thorough understanding of the properties of glycosyltransferases will be a critical step in any future biotechnological application of these enzymes in areas such as crop improvement and custom design of enzymes to produce desired compounds for nutritional and/or medicinal usage.

The KdpFABC complex is a P-type ATPase. Several features make the inducible Kplus-transporting ATPase a unique member of this enzyme family. Aspects of structure and function of KdpB, the catalytic subunit of the complex, were examined here. Site-directed mutagenesis of the charged residues aspartate 583 and lysine 586 in the putative transmembrane helix 5 of KdpB revealed that these charges are involved in the coupling of ATP hydrolysis to ion translocation. The binding of FITC was shown to be specific and the binding site is within the nucleotide-binding domain of KdpB, most probably at lysine 395. Modification of KdpB with FITC was affected by adenosine nucleotides. A Mg2plus-dependent hydrolysis of p-nitrophenolphosphate was observed, which was inhibited by micromolar concentrations of ortho-vanadate and FITC. Low concentrations of ATP stimulated pNPP hydrolysis, while higher concentrations of ATP were inhibitory. ADP, AMP and Pi inhibited the pNPP hydrolysis. The catalytic modules of KdpB were separately synthesized, purified and biochemically characterized. It was found that KdpBN was highly soluble and could be concentrated up to 1 mM and higher. Therefore, the KdpBN domain was used for further structural analysis using nuclear magnetic resonance spectroscopy. The KdpBN domain could be purified from cells grown in minimal medium with 15N-ammonium sulfate and 13C1-6 glucose as sole nitrogen and carbon sources, respectively. The purified, labeled KdpBN protein was applied to NMR analysis. High quality multidimensional NMR spectra were obtained (M. Haupt and H. Kessler, TU Munich, personal communication) and structure calculations leading to backbone assignments were carried out. An ortholog of the H4H5 domain of KdpB from the thermopilic archaeon Methanococcus jannaschii, Mj0968, was cloned, expressed, purified, and characterized.

Nous avons présenté COMMA, une méthode pour décrire et comparer les architectures dynamiques de différentes protéines. Il extrait propriétés dynamiques de ensembles conformationnels pour identifier les voies de communication, des chaînes de résidus liés par des interactions stables qui se déplacent ensemble, et cliques indépendants, des groupes de résidus qui fluctuent de manière concertée. Il fournit une description de l'infostery d'un complexe de protéines qui va au-delà des mesures au-delà de classiques de la façon dont une protéine se déplace ou change de forme. Nous avons montré l'efficacité de notre approche pour fournir des idées mécanistiques sur les effets des mutations délétères en identifiant les résidus qui jouent un rôle clé dans la propagation de ces effets. En outre COMMA révèle un lien entre les clusters de coévoluant résidus et les réseaux de corrélations dynamiques. Il permet de comparer les différents types de communication se produisant entre les résidus et de hiérarchiser les différentes régions d'une protéine en fonction de l'efficacité de leur communication. En outre, nous avons présenté une approche pour exploiter les séquences et les dynamiques structurelles pour prédire un paysage mutationnel. La discussion des exemples, a révélé l'interprétation physique sur la façon dont l'étude de la conservation apporte des idées importantes sur la sensibilité des positions conservées à des mutations. Notre méthode proposée, peut détecter des régions de protéines qui sont sujettes à des troubles ou des réarrangements conformationnels substantiels. De plus, il nous a permis de proposer des mutations qui régulent la stabilité des bobines enroulées désordonnées. / We presented COMMA, a method to describe and compare the dynamical architectures of different proteins or different variants of the same protein. COMMA extracts dynamical properties from conformational ensembles to identify communication pathways, chains of residues linked by stable interactions that move together, and independent cliques, clusters of residues that fluctuate in a concerted way. It provides a description of the infostery of a protein or protein complex that goes beyond the notions of chain, domain and secondary structure element/motif, and beyond classical measures of how a protein moves and/or changes its shape. We showed the efficiency of our approach in providing mechanistic insights on the effects of deleterious mutations by pinpointing residues playing key roles in the propagation of these effects. In addition COMMA reveals a link between clusters of coevolving residues and networks of dynamical correlations. It enables to contrast the different types of communication occurring between residues and to hierarchise the different regions of a protein depending on their communication efficiency. Furthermore, we presented an approach to exploit both the sequences and structural dynamics to predict a mutational landscape. The discussion of examples, revealed physical interpretation on how the study of conservation brings significant insights on the sensitivity of conserved positions to mutations. Our proposed method, can detect protein regions that are prone to disorder or substantial conformational rearrangements. Moreover, it enabled us to suggest mutations that regulate the stability of the disordered coiled-coils.

Les mitochondries sont en charge de la bioénergétique cellulaire, tout particulièrement dans le cerveau humain, au sein duquel les neurones sont extrêmement demandeurs en énergie et hautement dépendant de la phosphorylation oxydative. En effet, celles-ci génèrent un potentiel énergétique grâce à une chaîne de transport d’électrons, ou chaîne respiratoire, composée de quatre complexes protéiques ancrés dans la membrane interne mitochondriale. La chaine respiratoire permet la production d’énergie via la phosphorylation oxydative d’ADP en ATP par l’ATP synthéase dans la matrice mitochondriale. Le premier complexe (CI) de la chaîne est composé de 45 sous-unités protéiques (dont 44 différentes). En tant que premier enzyme de la phosphorylation oxydative, il joue un rôle d’initiateur et est essentiel pour la production d'énergie cellulaire. Un défaut d’assemblage du CI se traduit par d’importantes conséquences sur la bioénergétique cellulaire et augmente la production d’espèces réactives de l’oxygène (ROS), pouvant être à l'origine de divers troubles mitochondriaux, parmi lesquels certains processus neurodégénératifs. La bonne intégration des sous-unités et cofacteurs composant le CI est par conséquent primordiales et requièrent la participation de facteurs d’assemblage jouant le rôle de chaperonnes afin de stabiliser les sous-unités et faciliter leur intégration au sein de l'enzyme complète. De plus, certaines fonctions additionnelles à leur rôle d’assemblage peuvent intervenir dans d’autres processus cellulaire régulant l’activité métabolique.Le fonctionnement des facteurs d'assemblage du CI au niveau moléculaire demeure encore obscur. Néanmoins, il est admis que la plupart des facteurs d'assemblages identifiés sont actifs dès le début de l'assemblage, particulièrement pour l'incorporation des sous-unités membranaires. Récemment un groupe de facteurs d’assemblage composés des protéines NDUFAF1 (NADH dehydrogenase [ubiquinone] 1 alpha subcomplex assembly factor 1), ACAD9 (Acyl-CoA dehydrogenase 9), ECSIT (Evolutionarily conserved signaling intermediate in Toll pathway), et potentiellement TMEM126B (Transmembrane protein 126B) and TIMMDC1 (Translocase of inner mitochondrial membrane domain-containing 1) est désigné sous l'appellation complexe d’assemblage du complexe mitochondrial I (MCIA). Cependant, la composition et la stœchiométrie de ce dernier restent inconnus, excluant ainsi toute compréhension satisfaisante de sa structure et de son importance dans les mécanismes à l'oeuvre dans l’assemblage du CI.Cette thèse a pour but les caractérisations des facteurs d’assemblage ACAD9, ECSIT and NDUFAF1 grâce à un ensemble d’approches biochimiques et biophysiques dans le but de déterminer les mécanismes moléculaires et la cartographie des interactions impliqués dans l’assemblage du complexe MCIA. / Mitochondria are responsible for bioenergetics, particularly critical in the human brain, where neurons are extremely energy demanding and highly dependent on the oxidative phosphorylation (OXPHOS) system. They generate energetic potential through the electron transport chain (ETC), also named the respiratory chain, which is composed of four protein complexes embedded into the mitochondrial inner membrane (MIM) to enable the phosphorylation of ADP into ATP by the ATP synthase in the mitochondrial matrix. Together these complexes form the OXPHOS system. Complex I (CI), the first enzyme of the respiratory chain, is composed of 45 protein subunits (of which 44 are different) and initiates the OXPHOS system, being essential in cellular energy production. Defects in CI assembly severally impair ATP production, increase the production of reactive oxygen species (ROS) and are implicated in several mitochondrial disorders, including neurodegenerative diseases. The integration of the 45 subunits and the insertion of cofactors into the nascent complex requires the help of assembly factors. Assembly factors may act as chaperones that stabilize the intermediate complexes or subunits and help to attach them to other intermediate assemblies to build the complete enzyme. However, they may also have additional functions besides their requirement for CI assembly, in line with the emerging evidence that mitochondria are involved with various (sub)cellular processes that regulate cell metabolic activity.How CI assembly factors function at the molecular level is currently unclear, with very little structural information available. Nevertheless, it is thought that most identified assembly factors are involved in early assembly, more specifically in the incorporation of hydrophobic membrane subunits. Recently, the CI assembly factors NDUFAF1 (NADH dehydrogenase [ubiquinone] 1 alpha subcomplex assembly factor 1), ACAD9 (Acyl-CoA dehydrogenase 9), ECSIT (Evolutionarily conserved signaling intermediate in Toll pathway), and potentially TMEM126B (Transmembrane protein 126B) and TIMMDC1 (Translocase of inner mitochondrial membrane domain-containing 1) were proposed to form the so-called mitochondrial complex I assembly (MCIA) complex. However, the composition and stoichiometry of the MCIA complex are unknown, which precludes a proper understanding of the structural and mechanistic bases for building-up assembly intermediates and how the MCIA complex achieves specificity.This thesis pursues the characterisation of the MCIA core components ACAD9, ECSIT and NDUFAF1, mapping their interactions and characterising their structures using a combination of biophysical and biochemical approaches in order to elucidate the molecular mechanisms underlying the MCIA complex formation.

Spiders are capable of producing a variety of silk types, each with their own unique protein composition and function. Dragline silk in particular, has been of great interest due to its high tensile strength and extensibility. In the past, synthetically produced dragline fibers have not been able to match the superior properties of natural silk. A recent discovery in the western black widow spider, Latrodectus hesperus, might be the missing link between the current state of synthetic silks and naturally produced fibers. Our research is centered around the discovery a new family of five low-molecular-weight cysteine-rich proteins (CRPs) and their potential function within dragline silk. This study focuses on the characterization of recombinantly expressed CRP1, CRP2, and CRP4. Through structural analysis using circular dichroism, it has been determined that the CRP family members have mostly alpha-helical secondary structure and exhibit small differences in their ability to maintain their structure in the presence of changing environmental conditions. The study also covers the effects of temperature and pH on the folding and unfolding of the CRPs. It appears that pH is the dominant influence on protein unfolding within the major ampullate gland.

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Experimentally determining protein structure is a hard problem, with applications in both medicine and industry. Predicting protein structure is also difficult. Predicted contacts between residues within a protein is helpful during protein structure prediction. Recent state-of-the-art models have used deep learning to improve protein contact prediction. This thesis presents a new deep learning model for protein contact prediction, TiramiProt. It is based on the Tiramisu deep learning architecture, and trained and evaluated on the same data as the PconsC4 protein contact prediction model. 228 models using different combinations of hyperparameters were trained until convergence. The final TiramiProt model performs on par with two current state-of-the-art protein contact prediction models, PconsC4 and RaptorX-Contact, across a range of different metrics. A Python package and a Singularity container for running TiramiProt are available at https://gitlab.com/nikos.t.renhuldt/TiramiProt. / Att kunna bestämma proteiners struktur har tillämpningar inom både medicin och industri. Såväl experimentell bestämning av proteinstruktur som prediktion av densamma är svårt. Predicerad kontakt mellan olika delar av ett protein underlättar prediktion av proteinstruktur. Under senare tid har djupinlärning använts för att bygga bättre modeller för kontaktprediktion. Den här uppsatsen beskriver en ny djupinlärningsmodell för prediktion av proteinkontakter, TiramiProt. Modellen bygger på djupinlärningsarkitekturen Tiramisu. TiramiProt tränas och utvärderas på samma data som kontaktprediktionsmodellen PconsC4. Totalt tränades modeller med 228 olika hyperparameterkombinationer till konvergens. Mätt över ett flertal olika parametrar presterar den färdiga TiramiProt-modellen resultat i klass med state-of-the-art-modellerna PconsC4 och RaptorX-Contact. TiramiProt finns tillgängligt som ett Python-paket samt en Singularity-container via https://gitlab.com/nikos.t.renhuldt/TiramiProt.