RNA-ligand binding often depends crucially on the local RNA secondary structure at the binding site. We develop here a model that quantitatively predicts the effect of RNA secondary structure on effective RNA-ligand binding activities based on equilibrium thermodynamics and the explicit computations of partition functions for the RNA structures. A statistical test for the impact of a particular structural feature on the binding affinities follows directly from this approach. The formalism is extended to describing the effects of hybridizing small \modifier RNAs' to a target RNA molecule outside its ligand binding site. We illustrate the applicability of our approach by quantitatively describing the interaction of the mRNA stabilizing protein HuR with AU-rich elements [Meisner et al. (2004), Chem. Biochem. in press]. We discuss our model and recent experimental findings demonstrating the ffectivity of modifier RNAs in vitro in the context of the current research activities in the field of non-coding RNAs. We speculate that modifier RNAs might also exist in nature; if so, they present an additional regulatory layer for fine-tuning gene expression that could evolve rapidly, leaving no obvious traces in the genomic DNA sequences.

In recent years it has become evident that functional RNAs in living organisms are not just curious remnants from a primoridal RNA world but an ubiquitous phenomenon complementing protein enzyme based activity. Functional RNAs, just like proteins, depend in many cases upon their well-defined and evolutionarily conserved three-dimensional structure. In contrast to protein folds, however, RNA molecules have a biophysically important coarse-grained representation: their secondary structure. At this level of resolution at least, RNA structures can be efficiently predicted given only the sequence information. As a consequence, computational studies of RNA routinely incorporate structural information explicitly. RNA secondary structure prediction has proven useful in diverse fields ranging from theoretical models of sequence evolution and biopolymer folding, to genome analysis and even the design biotechnologically or pharmaceutically useful molecules.

<div>Proteins are susceptible to physical and chemical degradation in solution, which can lead to the loss of therapeutic activity and increase the potential for immunogenic responses when administered. Many degradation reactions are mediated by water, and therefore the proteins are often formulated as solids in which degradation rates are slowed significantly. Lyophilization is the most common method for producing solid protein formulations, which removes the water by sublimation and desorption under vacuum from the frozen protein solutions. Lyophilization requires excipients to protect the protein from the inherent stresses involved in the process. Degradation can still occur during lyophilization and storage, and needs to be characterized in order to develop a successful formulation with desired storage stability. The analytical techniques to characterize solid-state proteins are limited, however, and many do not provide site-specific information and lack the ability to predict stability beforehand.</div><div>Recently, solid-state hydrogen-deuterium exchange mass spectrometry (ssHDX-MS) has been developed to characterize proteins in solid powders with peptide level resolution. The technique was found to be sensitive to formulation and process changes. The ssHDX-MS metrics are highly correlated to the long-term storage stability, suggesting that the method can serve as a formulation screening tool. This dissertation aims to evaluate the factors affecting ssHDX kinetics and to develop a mechanistic understanding of the exchange process in solid samples, which in turn will support the solid-state protein development and enable it to be conducted in a more a cost and time-effective way. First, the contribution of peptide-matrix interactions to deuterium incorporation kinetics in the absence of higher-order structure was assessed using lyophilized poly-D, L-alanine peptides. Deuterium incorporation depended on excipient type and D₂O_(g) activity in the solid samples. A reversible pseudo-first-order kinetic model was proposed and validated using the experimental data. Second, the reversibility of the hydrogen-deuterium exchange reaction in the solid-state was evaluated to support the ssHDX mechanistic model further. The reaction was found to be reversible irrespective of initial conditions and independent of the excipient type. Pre-hydration of the peptide samples prior to deuterium labeling did not affect deuterium incorporation in amorphous samples compared to the controls not subjected to pre-hydration. Third, the contribution of peptide secondary structure to deuterium uptake kinetics was quantified using structured PDLA analogs. The deuterium incorporation in structured peptides was less than that of the PDLA peptides suggesting that both peptide structure and peptide-matrix interactions contribute to ssHDX-MS. Finally, a quantitative data analysis method was presented that allows the interpretation of ssHDX-MS data of a protein relative to controls. Altogether, the findings present a comprehensive mechanistic understanding of the ssHDX-MS of proteins that is relevant to the industry.</div>

In der vorliegenden Arbeit wird die Aufklärung der Konformation von Peptiden mit speziell modifizierten Aminosäuren beschrieben. Die Methoden der theoretischen Chemie (Quantenchemie, Molekülmechanik, Moleküldynamik) bilden dabei die Grundlage der Konformationsanalysen. Durch systematische Anwendung dieser Methoden werden im ersten Teil der Arbeit die konformativen Eigenschaften verschiedener [beta]-Aminosäuren und ihrer Oligomere ([beta]-Peptide) untersucht. Aus diesen Ergebnissen werden anschließend Regeln für das Sekundärstrukturdesign von ß-Peptiden abgeleitet. Der zweite Teil beschäftigt sich mit der theoretischen Konformationsanalyse von [alpha]- Hydrazinosäuren und ihrer Oligomere (Hydrazinopeptide). Aus den gewonnenen Erkenntnissen über die Ausbildung charakteristischer Sekundärstrukturelemente in diesen Verbindungen wird ebenfalls ein Regelwerk für das Design von Sekundärstrukturen aufgestellt. / The present work describes the conformational characteristics of pepttides with specifically modified amino acid constituents. For this purpose, the methods of theoretical chemistry (quantum chemistry, molecular mechanics, molecular dynamics) are utilisied for the conformational analyses. The conformation of various [beta]-amino acids and their oligomers ([beta]-peptides) are inverstigated in the first part of this work applying these methods. Rules for the design of definite secondary structures in [beta]-peptides are then derived from the obtained results. In the second part, systematic theoretical conformational analyses on [alpha]-hydrazino acids and their oligomers (hydrazino peptides) are described. The results are then used to compile a set of rules for the formation of characteriasitc secondary structures in this class of compounds.

Secondary structure dynamics of biopolymers play a vital role in many of the complex processes within a cell. However, due to the substantial number of atoms in the involved biopolymers along with the multitude of interactions that occur between the molecules, understanding these processes in detail is challenging and often involves computationally demanding simulations. In this thesis, the secondary structure dynamics of three different biopolymer systems were modeled using a single approach, which is based on intuitive principles that facilitate the interpretation. To this end, the kinetic behavior of each system was experimentally determined, and described by simplified reaction schemes, which were then connected to Markov chain models encompassing all principal secondary structural conformations. Firstly, we investigated the toehold-mediated strand displacement reaction, which is widely applied in nanotechnology to create DNA-based nano-devices and biochemical reaction networks. Our model correctly described the impact of base pair mismatches on the kinetics of these reactions, as measured by bulk fluorescence experiments. Additionally, it revealed that incumbent dissociation, base pair fraying, and internal loop formation are important processes during strand displacement. Furthermore, we established two dissipative elements to enhance temporal control over toehold-mediated strand displacement reactions. The first element allowed a reversible and repeatable incumbent strand release, whereas the second element provided the possibility to start the displacement reaction after a programmable temporal delay. Secondly, we studied the target recognition by the CRISPR-Cas effector complex Cascade, a highly promising protein for applications in genome engineering. Our model successfully reproduced all aspects of the torque- and mismatch-dependent R-loop formation time by Cascade obtained by single-molecule torque and bulk fluorescence measurements. Furthermore, we demonstrated that the seed effect observed for Cascade results from DNA supercoiling, rather than a structural property of the protein complex. Lastly, we explored the folding/unfolding of α-helices, which plays a critical role in the folding and function of proteins. Our model accurately described α-helix unfolding kinetics obtained by fast triplet-triplet energy transfer. Moreover, we showed that the complex α-helix unfolding does not follow a simple Einstein-type diffusion but is a combination of the sub-diffusive boundary diffusion and the rather peptide-length-independent coil nucleation. The presented models enabled access to the diverse timescales of the characterized processes, which are generally difficult to access experimentally, despite utilizing just a single approach. In particular, we obtained: tens of microseconds for the branch migration step time of the toehold-mediated strand displacement, hundreds of microseconds for the R-loop formation steps by Cascade, and tens of nanoseconds for folding or unfolding of an α-helix by a single residue. Given the simplicity and accessibility of the established models, we are confident that they will become useful tools for researchers to analyze the dynamics of biomolecules, and anticipate that similar modeling approaches can be applied to other biopolymer systems, being well-described by probabilistic models. / Die Sekundärstrukturdynamik von Biopolymeren spielt eine entscheidende Rolle bei vielen komplexen Prozessen innerhalb einer Zelle. Aufgrund der beträchtlichen Anzahl von Atomen in den beteiligten Biopolymeren und der Vielzahl an Wechselwirkungen zwischen den Molekülen ist es jedoch eine Herausforderung diese Prozesse im Detail zu verstehen, und erfordert oft rechenintensive Simulationen. In dieser Arbeit wurde die Sekundärstrukturdynamik von drei verschiedenen Biopolymersystemen mit einem einzigen Ansatz modelliert, welcher auf intuitiven Prinzipien beruht und somit eine erleichterte Interpretation der Ergebnisse ermöglicht. Hierzu wurde das kinetische Verhalten jedes Systems experimentell bestimmt und durch vereinfachte Reaktionsschemata beschrieben. Diese wurden anschließend mit Markov-Kettenmodellen verknüpft, welche alle wichtigen Konformationen der Sekundärstruktur abbilden. Als erstes System untersuchten wir die DNA Strangaustauschreaktion, welche in der Nanotechnologie häufig zur Herstellung von DNA-basierten Nanomaschinen und biochemischen Reaktionsnetzwerken eingesetzt wird. Unser Modell beschrieb die durch Ensemble-Fluoreszenz-Experimente gemessenen Auswirkungen von Basenfehlpaarungen auf die Kinetik dieser Reaktionen korrekt. Des Weiteren zeigte sich, dass die vorzeitige Strangablösung, das Ausfransen von Basenpaaren und die Bildung interner Schleifen wichtige Prozesse während des Strangaustausches sind. Darüber hinaus konnten wir zwei dissipative Elemente etablieren, um die zeitliche Kontrolle über die Strangaustauschreaktionen zu verbessern. Das erste Element ermöglicht eine reversible und wiederholbare Strangablösung, während das zweite Element die Möglichkeit bietet die Strangaustauschreaktionen nach einer programmierbaren zeitlichen Verzögerung zu starten. Zweitens untersuchten wir den Zielerkennungsprozess durch den CRISPR-Cas Komplex Cascade, ein vielversprechendes Protein für Anwendungen in der Genomtechnologie. Unser Modell reproduzierte erfolgreich alle Aspekte der torsions- und fehlpaarungs-abhängigen R-Schleifenbildung durch Cascade, welche durch Einzelmolekül-Torsions- und Ensemble-Fluoreszenz-Messungen ermittelt wurden. Zusätzlich konnten wir nachweisen, dass der für Cascade beobachtete „seed“-Effekt auf DNA-Verdrehung und nicht auf eine strukturelle Eigenschaft des Proteinkomplexes zurückzuführen ist. Schließlich untersuchten wir die Faltung/Entfaltung von α-Helices, welche eine entscheidende Rolle bei der Faltung und Funktion von Proteinen spielen. Unser Modell beschrieb die durch schnelle Triplett-Triplett-Energietransfer Experimente ermittelte α-Helix-Entfaltungskinetik exakt. Darüber hinaus konnten wir zeigen, dass die komplexe α-Helix-Entfaltung nicht einer einfachen Diffusion vom Einstein-Typ folgt, sondern eine Kombination aus subdiffusiver Grenzdiffusion und der eher peptidlängenunabhängigen Coil-Nukleation ist. Obwohl nur ein einziger Ansatz verwendet wurde, ermöglichten die vorgestellten Modelle den Zugang zu den vielschichtigen Zeitskalen der charakterisierten Prozesse, welche im Allgemeinen experimentell schwer zugänglich sind. Insbesondere konnten die folgenden zeitlichen Bereiche bestimmt werden: Dutzende von Mikrosekunden für die Schrittzeit der Strangaustauschreaktion, Hunderte von Mikrosekunden für die Schritte der R-Schleifenbildung durch Cascade, und Dutzende von Nanosekunden für die Faltung oder Entfaltung einer α-Helix um ein einzelnes Segment. Angesichts der Simplizität und Zugänglichkeit der etablierten Modelle sind wir zuversichtlich, dass sie zu nützlichen Werkzeugen für Forscher werden, um die Dynamik von Biomolekülen zu analysieren. Zusätzlich gehen wir davon aus, dass ähnliche Modellierungsansätze auf andere Biopolymersysteme angewendet werden können, sofern sie gut durch probabilistische Modelle beschrieben werden.

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付記する学位プログラム名: デザイン学大学院連携プログラム / 京都大学 / 新制・課程博士 / 博士(情報学) / 甲第24031号 / 情博第787号 / 新制||情||134(附属図書館) / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 阿久津 達也, 教授 山本 章博, 教授 鹿島 久嗣 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM