No / Cocrystallization of modafinil, (1), and 1,4-diiodotetrafluorobenzene, (2), in toluene leads to the formation of a metastable modafinil channel hydrate containing an unusual hydrogen bonded dimer motif involving the modafinil molecules that is not seen in anhydrous forms of modafinil. Computational methodologies utilizing bias drift-free differential evolution optimization have been developed and applied to a series of molecular clusters and multicomponent crystals in the modafinil/water and modafinil/water/additive systems for the additive molecules (2) or toluene. These calculations show the channel hydrate is less energetically stable than the anhydrous modafinil but more stable than a cocrystal involving (1) and (2). This provides theoretical evidence for the observed instability of the channel hydrate. The mechanism for formation of the channel hydrate is found to proceed via templating of the modafinil molecules with the planar additive molecules, allowing the formation of the unusual hydrogen-bonded modafinil dimer. It is envisaged that the additive is then replaced by water molecules to form the channel hydrate. The formation of the channel hydrate is more likely in the presence of (2) compared to toluene due to the destabilizing effect of the larger iodine molecules protruding into neighboring modafinil clusters. / Science Foundation Ireland, IRCSET, UCC 2012 Strategic Research Fund

Drug discovery has witnessed an increase in the application of in silico methods to complement existing in vitro and in vivo experiments, in an attempt to 'fail fast' and reduce the high attrition rates of clinical phases. Computer algorithms have been successfully employed for many tasks including biological target selection, hit identification, lead optimization, binding affinity determination, ADME and toxicity prediction, side-effect prediction, drug repurposing, and, in general, to direct experimental work. This thesis describes a multifaceted approach to virtual screening, to computationally identify small-molecule inhibitors against a biological target of interest. Conformer generation is a critical step in all virtual screening methods that make use of atomic 3D data. We therefore analysed the ability of computational tools to reproduce high quality, experimentally resolved conformations of organic small-molecules. We selected the best performing method (RDKit), and developed a protocol that generates a non-redundant conformer ensemble which tends to contain low-energy structures close to those experimentally observed. We then outline the steps we took to build a multi-million, small-molecule database (including molecule standardization and efficient exact, substructure and similarity searching capabilities), for use in our virtual screening experiments. We generated conformers and descriptors for the molecules in the database. We tagged a subset of the database as `drug-like' and clustered this to provide a reduced, diverse set of molecules for use in more computationally-intensive virtual screening protocols. We next describe a novel virtual screening method we developed, called Ligity, that makes use of known protein-ligand holo structures as queries to search the small-molecule database for putative actives. Ligity has been validated against targets from the DUD-E dataset, and has shown, on average, better performance than other 3D methods. We also show that performance improved when we fused the results from multiple input structures. This bodes well for Ligity's future use, especially when considering that protein structure databases such as the Protein Data Bank are growing exponentially every year. Lastly, we describe the fruitful application of structure-based and ligand-based virtual screening methods to Plasmodium falciparum Subtilisin-like Protease 1 (PfSUB1), an important drug target in the human stages of the life-cycle of the malaria parasite. Our ligand-based virtual screening study resulted in the discovery of novel PfSUB1 inhibitors. Further lead optimization of these compounds, to improve binding affinity in the nanomolar range, may promote them as drug candidates. In this thesis we postulate that the accuracy of computational tools in drug discovery may be enhanced to take advantage of the exponential increase of experimental data and the availability of cheaper computational power such as cloud computing.

Concerns over industrial emissions and nuclear waste have led to the need to study ways to sequester industrial gasses, and recycle nuclear fuel. Two projects were done to study solvent systems for these two problems using computational methods. Current methods for SO₂ sequestration are wasteful in that the gasses cannot be extracted from the solvent, and the solvent cannot be reused. One possible solution, which this work focuses on, is the use of an ionic liquid as a sequestration agent for the adsorption of SO₂. Separation technology for heavy elements has not changed for over 60 years and issues with radiation contamination and low efficiency lead to high solvent waste. Biphasic alkane-water extraction systems are a possible solution as they have been used for the extraction of heavy elements. This work focuses on characterizing the factors that control partitioning in biphasic systems which increase extraction efficiency.

Interactions between single and double stranded oligonucleotides with SiO2 surfaces and the interactions between oligonucleotides and immobilized oligomers have been studied computationally. The oligonucleotide is the 18-base-pair sequence for the survival motor neuron gene SMN1. The oligomer consisted of a 50 unit 2-hydroxyethyl methacrylate (PHEMA) molecule. A linker used to tether the oligonucleotide was either a 10 Å or a 30 Å long succinimdyl 4-[N-maleimidomethyl]cyclohexane-1-caroxylate (sulfo-SMCC-Cn). The surface consisted of a SiO2 crystal that was 50 Å long and 50 Å wide, one unit thick and covered with modified-(3-aminopropyl)trimethoxysilane (m-APTMS) molecules. It was determined that explicit water, sodium counterions and excess salt were necessary to produce computationally stable oligonucleotide structures on surfaces. Artificial partial charges were introduced to the surface, and linkers, oligomers and oligonucleotides were immobilized and studied. The linkers collapsed onto a positive but not onto a negative surface. Oligomers moved closer to the SiO2 surface regardless of the surface charge. Immobilized oligonucleotides tilted significantly from an initial upright position but did not collapse completely onto the surfaces. The interactions between immobilized oligonucleotides and oligomers were examined. The number of oligomers surrounding the oligonucleotide was varied between two and four. Single stranded oligonucleotides were prevented from interacting with the surface as they were inhibited by the presence of oligomers. Double stranded oligonucleotides collapsed onto the surface when only two oligomers were present but remained upright when four oligomers were present. This was due to the four oligomers interacting with one another and effectively shielding the surface. The oligomers interacted with the bases in the single stranded oligonucleotides, making them energetically accessible. Presence of a high density of oligomers prevented the dsDNA from collapsing onto the surface. These results suggest design criteria for preparation of mixed oligonucleotide and oligomer films for use in biosensors.

Water monomer and dimer encapsulations into D-2(22)-C-84 fullerene are evaluated. The encapsulation energy is computed at the M06-2X/6-31++G** level, and it is found that the monomer and dimer storage in C-84 yields an energy gain of 10.7 and 17.4kcalmol(-1), respectively. Encapsulation equilibrium constants are computed by using partition functions based on the M06-2X/6-31G** and M06-2X/6-31++G** molecular data. Under high-temperature/high-pressure conditions, similar to that for the encapsulation of rare gases in fullerenes, the computed (H2O)(2)@C-84-to-H2O@C-84 ratio is close to 1:2.

Computer-based drug design is a vital area of pharmaceutical chemistry; Quantitative Structure-Activity Relationships (QSARs), determined computationally from experimental observations, are crucial in identifying candidate drugs by early screening, saving time on synthesis and in vivo testing. This thesis investigates the viability and the practicalities of using Mass Spectra-based pseudo-molecular descriptors, in comparison with other molecular descriptor systems, to predict the carcinogenicity, mutagenicity and the Cltransport inhibiting ability of a variety of molecules, and in the first case, of chemotherapeutic drugs particularly. It does so by identifying a number of QSARs which link the physical properties of chemicals with their concomitant activities in a reliable and mathematical manner. First, this thesis confirms that carcinogenicity and mutagenicity are indeed predictable using a variety of Artificial Intelligence techniques, both supervised and unsupervised, information germane to pharmaceutical research groups interested in the preliminary screening of candidate anti-cancer drugs. Secondly, it demonstrates that Mass Spectral intensities possess great descriptive fidelity and shows that reducing the burden of dimensionality is not only important, but imperative; selecting this smaller set of orthogonal descriptors is best achieved using Principal Component Analysis as opposed to the selection of a set of the most frequent fragments, or the use of every peak up to a number determined by the boundaries of supervised learning. Thirdly, it introduces a novel system of backpropagation and demonstrates that it is more efficient than its principal competitor at monitoring a series of connection weights when applied to this area of research, which requires complex relationships. Finally, it promulgates some preliminary conclusions about which AI techniques are applicable to certain problem-scenarios, how these techniques might be applied, and the likelihood that that application will result in the identification of series of reliable QSARs.

The most critical biochemistry in an organism supports the central dogma of molecular biology: transcription of DNA to RNA and translation of RNA to peptide sequence. Proteins are then responsible for catalyzing, regulating and ensuring the fidelity of transcription and translation. At the heart of these processes lie selective biomolecular interactions and specific dynamics that are necessary for complex formation and catalytic activity. Through advanced biophysical and computational methods, it has become possible to probe these macromolecular dynamics and interactions at the molecular and atomic levels to tease out their underlying physical bases. To the end of a more thorough understanding of these physical bases, we have performed studies to probe the motions and interactions intrinsic to the function of biomolecular complexes: modeling the dual-base flipping strategy of alkylpurine glycosylase D, dynamically tracing evolution and epistasis in the 3-ketosteroid family of nuclear receptors, discovering the allosteric and conformational aspects of transcription regulation in liver receptor homologue 1, leveraging specific contacts in tyrosyl-DNA phosphodiesterase 2 for the development of novel inhibitor scaffolds, and detailing the experimentally observed connection between solvation and sequence-specific binding affinity in PU.1-DNA complexes at the atomic level. While each study seeks to solve system-specific problems, the collection outlines a general and broadly applicable description of the biophysical motivations of biochemical processes.

Science is an area of study with unique particularities concerning what “counts” as scientific practices where some learners are legitimized, while other learners are not. Such is the case for preservice elementary teachers (hereafter PSETs) –a population characterized by the literature as being in-need of science intervention. However, most of the literature deficiently conceptualizes PSETs’ science learning, so I sought for ways to refigure their learning positively. Drawing from Van Horne and Bell’s (2017) constructs of practice-linked and disciplinary identity, I offer that PSETs have nuanced, complex science identities that are influenced by their lived experiences inside and outside the classroom. To investigate the lived experiences of PSETs both inside and outside the classroom, 10 video-recorded, focus-group interviews were done while PSETs were undertaking an undergraduate chemistry-content course. Students were asked about their relationships with science as past elementary and high school students, as well as current undergraduate students. Students were also asked how they perceived their learning in the chemistry-content course. The research questions this work seeks to answer are:<div><br><div>• How do PSETs construct their science practice-linked identities?</div><div>• How does Fundamentals of Chemistry afford identity resources that contribute to PSETs’ science practice-linked identities?</div><div><br></div><div>The data was coded for themes surrounding their science identities, teaching identities, and learning of each individual PSET. Using narrative analysis, I synthesized three allegories, “I am a science person,” and “I am not a science person,” and Ambiguous which aim to elucidate the spectrum of ways PSETs navigate science learning as a science person, a non-science person, and an unsure person. In addition to the PSETs’ stories, I also analyzed how the chemistry-content course curriculum afforded PSETs with identity-building resources that helped science learning as current students and as future elementary teachers. I found that PSETs’ science identities formed before the course impacted the ways they participated in the chemistry-content course (practice-linked identity), but the curriculum offered students opportunities to renegotiate their science identities and practice science in ways that felt more legitimate to themselves and their prospective careers. Overall, I hope this work informs how instructors can design courses that are sensitive towards the needs of their students and highlight the importance of having a curriculum that affords students with the chance to re-engage with disciplinary practices in which their identities are legitimized as meaningful for their learning.If science determines practices that “count,” science must also acknowledge whose practices are accounted.<br><div><br></div></div></div>

Als Hilfsstoffe in der Arzneimittelentwicklung können Cyclodextrine und ihre Derivate aufgrund der Fähigkeit zur Bildung von Wirt-Gast-Komplexen mit organischen Molekülen zu unterschiedlichsten Zwecken verwendet werden. Ein Verständnis aller Einflussfaktoren auf die Komplexbildung wäre von großem Wert, weil man so gegebenenfalls vorab entscheiden könnte, ob ein Einsatz von Cyclodextrinen überhaupt in Betracht käme, und wenn ja, welches Cyclodextrin den beabsichtigten Effekt brächte. In der vorliegenden Arbeit wurden mit Hilfe verschiedener Methoden Informationen zu den Einschlusskomplexen gesammelt, die natürliche Cyclodextrine mit einer Reihe typischer Arzneistoffmoleküle bilden. Als Modellsubstanzen wurden die Sulfonamide Sulfadiazin, Sulfadimidin, Sulfafurazol, Sulfaguanidin, Sulfamerazin, Sulfameter, Sulfamethoxazol, Sulfanilamid und Sulfathiazol gewählt. Aufgrund ihrer Molekülgröße bilden die gewählten Gäste in wässriger Lösung bevorzugt mit dem siebengliedrigen β-Cyclodextrin Komplexe, die Wechselwirkungen sind im Vergleich mit anderen Gastmolekülen jedoch relativ schwach. Im Rahmen von Löslichkeitsstudien wurden verschiedene Einflüsse (pH, Temperatur) auf die Komplexbildung in Lösung untersucht. Mit Hilfe von Van’t Hoff Plots wurden die thermodynamischen Größen der Komplexbildung bestimmt, wo das Phänomen der Enthalpie-Entropie-Kompensation beobachtet werden konnte. Die Stöchiometrie der Komplexe wurde unter anderem in Job’s Plots mit Hilfe der 1H-NMR-Spektroskopie bestimmt. Die Komplexbildung geht im Fall der Sulfonamide meist nicht nur mit einer Löslichkeitssteigerung des Gastes, sondern auch des nur eingeschränkt wasserlöslichen β-Cyclodextrins einher. Dieser Effekt wurde bei verschiedenen pH-Werten quantifiziert und tritt bei allen Gastmolekülen, mit Ausnahme von Sulfathiazol, in vergleichbarem Umfang auf. Unter Ausnutzung dieses Phänomens kann je nach Gast eine Konzentration des Wirtes in Lösung erreicht werden, die ein Vielfaches seiner intrinsischen Löslichkeit beträgt. Sowohl in Lösung als auch im Feststoff wurde die Struktur der Einschlusskomplexe mit spektroskopischen Verfahren untersucht. ROESY-Spektren zeigten, dass die chemisch sehr ähnlichen Gastmoleküle teilweise erheblich von einander abweichende Positionen und Orientierungen in der Kavität des Cyclodextrins einnehmen. FTIR-Spektren fester Komplexzubereitungen unterstützen die detaillierteren NMR-Ergebnisse für die meisten Gäste. Ergänzend wurden mit Hilfe von molekularmechanischen Methoden theoretisch plausible Komplexstrukturen erstellt. Dabei wurde die Flexibilität der Cyclodextrinmoleküle und das mögliche Auftreten eines induced-fit durch die Generierung verschiedenartiger Konformere des β-Cyclodextrins in einer Molekulardynamikstudie berücksichtigt. In Dockingstudien (Autodock 3.0) wurde nach dem Bindungsmodus gesucht. Unter den Versuchsbedingungen dominieren Orientierungen, bei denen die aromatische Aminogruppe und die schwefelgebundenen Sauerstoffatome mit den Hydroxylgruppen des Wirtes Wasserstoffbrückenbindungen aufbauen können. Die resultierende Störung der intra- und intermolekularen Wechselwirkungen des Cyclodextrins stellt eine mögliche Erklärung der synergistischen Löslichkeitseffekte zwischen Wirt und Gast dar. Die gewonnenen Daten stellen eine Grundlage zur Charakterisierung der Komplexbildung von Sulfonamiden mit natürlichen Cyclodextrinen dar. Alle Modellsubstanzen wurden mit denselben Methoden untersucht, was eine vergleichende Betrachtung ermöglicht. Insgesamt wurde durch die Betrachtung einer so großen Gruppe an Modellsubstanzen ähnlicher chemischer Eigenschaften und Molekülstruktur ein Eindruck gewonnen, wie stark die Vorgänge bei der Komplexbildung mit Cyclodextrinen schon innerhalb einer relativ homogenen Gruppe variieren können. Aus den Ergebnissen der vorliegenden Arbeit ist zu folgern, dass Vorhersagen zur Komplexbildung mit Cyclodextrinen anhand von Untersuchungen mit vergleichbaren Modellsubstanzen nicht endgültig zu treffen sind, sondern immer von einem vom Gastmolekül abhängigen Einzelfall auszugehen ist. / Cyclodextrins and their derivatives with their ability to form host-guest-complexes with organic molecules can be applied for various purposes in drug development. Understanding all effects on complex formation one could be able to predict if the use of cyclodextrins is indicated and which cyclodextrin is appropriate. In this thesis various methods were applied to gather information about complexes formed by natural cyclodextrins and a set of typical drug molecules. Sulfa drugs - sulfadiazine, sulfadimidine, sulfafurazole, sulfaguanidine, sulfamerazine, sulfameter, sulfamethoxazole, sulfanilamide and sulfathiazole - were chosen as model substances. Owing to their molecular size these guests form complexes preferably with β-cyclodextrin in aqueous solution. The interactions are relatively weak compared with other guest molecules. Phase solubility analysis was used to investigate several effects (pH, temperature) on complexation in solution. The thermodynamic parameters for the complexation were derived from linear van’t Hoff plots which indicate the presence of the enthalpy-entropy-compensation phenomenon. The complex stoichiometry was derived amongst others from Job’s plots employing 1H-NMR-spectroscopy. For most sulfa drugs complexation not only results in a solubility enhancement of the guest, but also increases the low intrinsic solubility of β-cyclodextrin itself. This effect was quantified at several pH values. It is of comparable extent for all guest molecules with exception of sulfathiazole. Making use of the described phenomenon one can achieve β-cyclodextrin concentrations many times higher than its intrinsic solubility in solution. The structure of the inclusion complexes was examined in solution and in the solid state using the means of spectroscopy. ROESY spectra of some model substances show that the chemically related molecules occupy considerably different positions and orientations inside the cyclodextrin’s cavity. FTIR spectra of solid complex formulations support the more detailed NMR-results in most cases. In addition, theoretical structures for the inclusion complexes were created by molecular mechanics. Cyclodextrin flexibility and a possible ‘induced-fit’ were simulated by generating multiple conformations of β-cyclodextrin by molecular dynamics. Docking experiments were carried out in order to characterize the inclusion mode of the sulfonamides. Under the experimental conditions we observed those orientations to be predominant where the aromatic amino group and the oxygen atoms of the sulfonamide are able to establish H-bonds to the host’s hydroxyl groups. The resulting disturbance of the intermolecular and intramolecular H-bonds of β-cyclodextrin is one possible explanation for the synergistic solubility effects between host and guest. The data obtained forms a foundation for the characterization of the complexation process of sulfonamides and natural cyclodextrins. All model substances were investigated applying the same methods allowing a comparative interpretation. Overall, studying a larger group of model substances of similar chemical properties und molecular structure showed the variations of the inclusion process even in such a homogenous group of guests. The results of this thesis make it obvious that predictions concerning complex formation with cyclodextrins are not possible by considering investigations of related model substances. Instead, complex formation should always be regarded as an individual case.

Developing a sustainable energy infrastructure for the 21st century requires the large scale development of renewable energy resources. Fully exploiting these inherently intermittent supplies will require advanced energy storage technologies, with rechargeable Li-ion and Na-ion batteries considered highly promising for both vehicle electrification and grid storage applications. However, the performance required of battery materials has not been achieved, and significant improvements are needed. Modern computational techniques allow the elucidation of structure-property relationships at the atomic level and are valuable tools in providing fundamental insights into novel materials. Therefore, in this thesis a combination of atomistic simulation and ab initio density functional theory (DFT) techniques have been used to study a number of potential battery cathode materials. Firstly, Na2FePO4F and NaFePO4 are interesting materials that have been reported recently as attractive positive electrodes for Na-ion batteries. Here, we report their Na-ion conduction behaviour and intrinsic defect properties using atomistic simulation methods. Na+ ion conduction in Na2FePO4F is predicted to be two-dimensional (2D) in the interlayer plane. Na ion migration in NaFePO4 is restricted to the [010] direction along a curved trajectory, leading to quasi-1D Na+ diffusion. Furthermore, Na/Fe antisite defects are predicted to have a lower formation energy in NaFePO4 than Na2FePO4F. The higher probability of tunnel occupation with a relatively immobile Fe2+ cation - along with a greater volume change on redox cycling - contributes to the poor electrochemical performance of NaFePO4. Secondly, work on the Na2FePO4F system is extended to include investigation of the surface structures and energetics. The equilibrium morphology is found to be essentially octagonal, compressed slightly along the [010] direction, and is dominated by the (010), (021), (122) and (110) surfaces. The calculated growth morphology is a more ``rod-like'' nanoparticle, with the (021), (023), (110) and (112) planes predominant. The (010) surface lies parallel to the Na layers in the ac plane and is unlikely to facilitate Na+ intercalation. As such, its prominence in the equilibrium morphology, and absence from the growth morphology, suggests nanoparticles synthesised in a kinetically limited regime should provide higher rate performance than those synthesised in close to equilibrium conditions. Surface redox potentials for Na2FePO4F derived using DFT vary between 2.76 - 3.37 V, in comparison to a calculated bulk cell voltage of 2.91 V. Most significantly, the lowest energy potentials are found for the (130) and (001) planes suggesting that upon charging Na+ will first be extracted from these surfaces, and inserted lastly upon discharging. Thirdly, the mixed phosphates Na4M3(PO4)2P2O7 (M=Fe, Mn, Co, Ni) are explored as a fascinating new class of materials reported to be attractive Na-ion cathodes, displaying low volume changes upon cycling indicative of long lifetime operation. Key issues surrounding intrinsic defects, Na-ion migration mechanisms and voltage trends have been investigated through a combination of atomistic energy minimisation, molecular dynamics and DFT simulations. The MD results suggest Na+ diffusion extends across a 3D network of migration pathways with an activation barrier of 0.20-0.24 eV, and diffusion coefficients (DNa) of 10-10-10-11 cm2s-1 at 325 K, suggesting high rate capability. The cell voltage trends, explored using DFT methods, indicate that doping the Fe-based cathode with Ni can significantly increase the voltage, and hence energy density. Finally, DFT simulations of K+-stabilised α-MnO2 have been combined with aberration corrected-STEM techniques to study the surface energetics, particle morphologies and growth mechanism. α-K0.25MnO2 grown through a hydrothermal synthesis method is found to produce primary nanowires with preferential growth along the [001] direction. Primary nanowires attach through a shared (110) interface to form larger secondary nanowires. This is in agreement with DFT simulations with the {100}, {110} and {211} surfaces displaying the lowest surface energies. The ranking of surface energies is driven by Mn coordination environments and surface relaxation. The calculated equilibrium morphology of α-K0.25MnO2 is consistent with the observed primary nanowires from high resolution electron microscopy images.