Thesis (Ph. D.)--Michigan State University. Dept. of Chemistry, 2006. / Title from PDF t.p. (viewed on June 19, 2009) Includes bibliographical references (p. 202-210). Also issued in print.

Knowledge of the structure and dynamics of cellular protein complexes is essential for understanding their functionally relevant interactions. In Gram-negative bacteria, the complex machinery associated with the type II secretion system (T2SS) polymerises inner membrane pseudopilin proteins into thin filaments, to export substrates such as toxins, hydrolases and cytochromes. Here, computational simulations were used to study proteins from the Klebsiella oxytoca T2SS, focusing on the substrate pullulanase PulA, the major pseudopilin PulG, and the putative chaperone PulM. Chapter 3 contains an in silico study of both post-translationally acylated PulA (lipoPulA) and non-acylated PulA (PulANA) in association with a lipid bilayer, representing an approximation of the biological state prior to secretion; this study examined PulA dynamics and the possible role of the acyl tail in protein-membrane interactions before secretion. Novel insights into the interactions of a key residue necessary for Type 2 secretion were gained via simulations performed on a PulANA D2S variant, extending prior in vitro results. In Chapter 4, PulA was simulated in conditions closer to the physiological environment, using counter-ions to investigate the possible effect of the high periplasmic calcium concentration on protein conformation and lipid interactions prior to secretion. In Chapter 5, variants of the major pseudopilin PulG containing one transmembrane helix were simulated, demonstrating N-terminal interactions made possible by wild-type methylation of residue Phe1. Simulations of several monomeric PulG variants provided insight into the roles of the essential residue Glu5 and Phe1 methylation, previously identified by experimental work to be important. Simulations of the PulG dimer demonstrated the dynamic nature of the membrane-embedded dimer interface, and showed how computational analysis can predict in vivo contacts. Finally, Chapter 6 extended the T2SS studies to coarse-grained methods, sampling possible conformations and predicting the PulG-PulM interface within the membrane, prior to PulG presentation to the remaining secretion apparatus.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 106-123).

No description available.

Das Verständnis der Mechanismen, nach denen biologische Systeme ablaufen, ist ein wichtiger Fokus der aktuellen Strukturbiologie. Kernmagnetische Resonanzspektroskopie (NMR) ist eine geeignete Technik, um solche Ziele anzustreben sowie Struktur und Dynamik von Biomolekülen zu erforschen, um komplementäre Informationen zum Verständnis von Proteinfunktionalität zu erhalten. Rasante Fortschritte sind vor nicht langer Zeit auf dem Gebiet biologischer Festkörper-NMR (ssNMR) erzielt worden, was zu vollständiger Strukturaufklärung zahlreicher Peptide und kleiner Proteine, der Beschreibung von Protein-Komplexbildung sowie der der dynamischen Eigenschaften kleiner Proteine geführt hat. Festkörper-NMR ist die Methode der Wahl bei struktureller und dynamischer Charakterisierung von Membranproteinen und aggregierten amyloidogenen Systemen, die schwer löslich und kaum mit Lösungs-NMR oder Röntgenkristallographie zugänglich sind. Moderne Festkörper-NMR ist noch immer limitiert, was Auflösung und Empfindlichkeit betrifft, und macht weitere Entwicklungen auf den Gebieten der Probenpräparation und des Pulssequenz-Designs erforderlich. In meiner Arbeit untersuche ich die potenzielle Verwendung von Deuterierung in der Protein Festkörper-NMR zur Erhöhung von Empfindlichkeit und Auflösung in 15N-1H Korrelationsexperimenten. Der erzielte Fortschritt auf diesen Gebieten erlaubt die Verfolgung von Proteinrückgratbewegungen mit hoher Genauigkeit, die vorher nicht verfügbar war. Wir zeigen zum ersten Mal, dass TROSY Experimente für Festkörper-NMR gewinnbringend sind. Außerdem wurde eine Pulssequenz für 13C-13C J Kopplung zur Erhöhung der Auflösung in der Kohlenstoff-Dimension entwickelt. / Understanding the mechanisms how biological systems work is an important objective of current structural biology. Nuclear magnetic resonance (NMR) spectroscopy is a well suited technique to approach these goals and to study structure and dynamics of biomolecules in order to obtain complimentary information for understanding functionality of proteins. Recently, rapid progress has been made in the field of biological solid state NMR (ssNMR), which resulted in complete structure elucidation of several peptides and small proteins, the characterization of protein complex formation and the characterization of dynamic properties of small proteins. Solid state NMR is the method of choice for structural and dynamic characterization of membrane proteins and aggregated amyloidogenic systems, which are poorly soluble and can not be easily studied by solution state NMR and X-ray spectroscopy. Modern solid state NMR is still limited in resolution and sensitivity, and requires developments in sample preparation and pulse sequence design. In my thesis, I study the potential use of deuteration in protein solid state NMR for sensitivity, as well as for resolution enhancement in 15N-1H correlation experiments. Achieved progress in these fields allows to monitor backbone motion with high accuracy, which has not been available before. We show for the first time that TROSY type experiments can be beneficial for solid state NMR. In addition, a pulse sequence for 13C-13C J decoupling was developed to increase resolution in the carbon dimension.

Proteins are involved in numerous functions in the human body, including chemical transport, molecular recognition, and catalysis. To perform their function most proteins must adopt a specific structure (often referred to as the folded structure). A microscopic description of folding is an important prerequisite for elucidating the underlying basis of protein misfolding and rational drug design. However, protein folding occurs on heterogeneous length and time scales, presenting a grand challenge to both experiments and simulations. In computer simulations, challenges are generally mitigated by adopting coarse-grained descriptions of the physical environment, employing enhanced sampling strategies, and improving computing code and hardware. While significant advances have been made in these areas, for numerous systems a large spatiotemporal gap between experiment and simulations still exists, due to the limited time and length scales achieved by simulation, and the inability of many experimental techniques to probe fast motions and short distances. In this thesis, kinetic transition networks (KTNs) are constructed for various protein folding systems, via approaches based on the potential energy landscape (PEL) framework. By applying geometry optimisation techniques, the PEL is discretised into stationary points (i.e.~low-energy minima and the transition states that connect them). Essentially, minima characterise the low-lying regions of the PEL (thermodynamics) and transition states encode the motion between these regions (dynamics). Principles from statistical mechanics and unimolecular rate theory may then be employed to derive free energy surfaces and folding rates, respectively, from the KTN. Furthermore, the PEL framework can take advantage of parallel and distributed computing, since stationary points from separate simulations can be easily integrated into one KTN. Moreover, the use of geometry optimisation facilitates greater conformational sampling than conventional techniques based on molecular dynamics. Accordingly, this framework presents an appealing means of probing complex processes, such as protein folding. In this dissertation, we demonstrate the application of state-of-the-art theory, combining PEL analysis and KTNs to three diverse protein systems. First, to improve the efficiency of protein folding simulations, the intrinsic rigidity of proteins is exploited by implementing a local rigid body (LRB) approach. The LRB approach effectively integrates out irrelevant degrees of freedom from the geometry optimisation procedure and further accelerates conformational sampling. The effects of this approach on the underlying PEL are analysed in a systematic fashion for a model protein (tryptophan zipper\,1). We demonstrate that conservative local rigidification can reproduce the thermodynamic and dynamic properties for the model protein. Next, the PEL framework is employed to model large-scale conformational changes in proteins, which have conventionally been difficult to probe in silico. Methods based on geometry optimisation have proved useful in overcoming the broken ergodicity issue, which is associated with proteins that switch morphology. The latest PEL-based approaches are utilised to investigate the most extreme case of fold-switching found in the literature:~the α-helical hairpin to β-barrel transition of the C-terminal domain of RfaH, a bacterial transcription factor. PEL techniques are employed to construct the free energy landscape (FEL) for the refolding process and to discover mechanistic details of the transition at an atomistic level. The final part of the thesis focuses on modelling intrinsically disordered proteins (IDPs). Due to their inherent structural plasticity, IDPs are generally difficult to characterise, both experimentally and via simulations. An approach for studying IDPs within the PEL framework is implemented and tested with various contemporary potential energy functions. The cytoplasmic tail of the human cluster of differentiation 4 (CD4), implicated in HIV-1 infection, is characterised. Metastable states identified on the FEL help to unify, and are consistent with, several earlier predictions.