Noncovalent interactions in complex chemical systems are examined by considering model systems which capture the essential physics of the interactions and applying correlated electronic structure techniques to these systems. Noncovalent interactions are critical to understanding a host of energetic and structural properties in complex chemical systems, from base pair stacking in DNA to protein folding in organic solids. Complex chemical and biophysical systems, such as enzymes and proteins, are too large to be studied using computational techniques rigorous enough to capture the subtleties of noncovalent interactions. Thus, the larger chemical system must be truncated to a smaller model system to which rigorous methods can be applied in order to capture the essential physics of the interaction. Computational methodologies which can account for high levels of electron correlation, such as second-order perturbation theory and coupled-cluster theory, must be used. These computational techniques will be used to study several types (pi stacking, S/pi, and C-H/pi) of noncovalent interactions in two chemical contexts: biophysical systems and organic solids.

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods typically assess the pocket as a whole, doing little to suggest which regions and interactions are the most important for binding. This thesis introduces Fragment Hotspot Maps, a grid-based method that samples atomic propensities derived from interactions in the Cambridge Structural Database (CSD) with simple molecular probes. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores, offering more precision over other binding site prediction methods. The method is validated by scoring the positions of 21 fragment and lead pairs. Fragment atoms are found in the highest scoring parts of the map corresponding to their atom type, with a median percentage rank of 98%. This is reduced to 72% for lead atoms, showing that the method can differentiate between the hotspots, and the warm spots later used during fragment elaboration. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. These calculations are easily accessible through a simple to use web application, which only requires an input PDB structure or code. High scoring specific interactions predicted by the Fragment Hotspot Maps can be used to guide existing computer aided drug discovery methods. The Hotspots Python API has been created to allow these work flows to be executed programmatically through a single Python script. Two of the functions use scores from the Fragment Hotspot Maps to guide virtual screening methods, docking and field-based ligand screening. Docking virtual screening performance is improved by using a constraint selected from the highest scoring polar interaction. The field-based ligand screener uses modified versions of the Fragment Hotspot Maps directly to predict and score the binding pose. This workflow gave comparable results to docking, and for one target, Glucocorticoid receptor (GCR), showed much better results, highlighting its potential as an orthogonal approach. Fragment Hotspot Maps can be used at multiple stages of the drug discovery process, and research into these applications is ongoing. Their utility in the following areas are currently being explored: to assess ligandability for both individual structures and across proteomes, to aid in library design, to assess pockets throughout a molecular dynamics trajectory, to prioritise crystallographic fragment hits and to guide hit-to-lead development.

Realizamos uma caracterização estrutural e eletrônica dos inibidores enzimáticos E-64 e CA030 utilizando técnicas de química quântica. Otimizações de geometria são realizadas em nível ab initio com os métodos Hartree-Fock e Teoria do Funcional da Densidade e estas estruturas são então comparadas com os resultados cristalográficos obtidos do Protein Data Bank. O cálculo do espectro de vibração infravermelho foi realizado para assegurar que as estruturas eram pontos de mínimo. Nós também fizemos a atribuição das freqüências vibracionais aos grupos funcionais das moléculas. A caracterização eletrônica é obtida com o cálculo do espectro de absorção ultravioleta-visível. Efeitos de solvente são contabilizados através da teoria de Campo de Reação Auto-Consistente. Uma análise detalhada das excitações do espectro calculado do E-64 e do CA030 é realizada e nós estudamos particularmente as transições características em torno de 200 nm. Tanto para o E-64 como para o CA030 nós identificamos o cromóforo responsável pela transição característica dos inibidores. Adicionalmente, nós levamos em consideração a influência da interação do CA030 com a catepsina B através do cálculo do espectro ultravioleta-visível do inibidor com o aminoácido cisteína. / We have made a structural and electronic characterization of the enzyme inhibitors E-64 and CA030 using quantum chemistry techniques. Geometry optimizations are performed in the ab initio level with the Hartree-Fock and Density Functional Theory methods and these structures are then compared with crystallographic results obtained from the Protein Data Bank. The infrared vibration spectrum calculation has been carried out to assure that the theoretical structures are true minima. We also have made an assignment of the vibrational frequencies to the functional groups of the molecules. The electronic characterization is performed with the calculation of the ultraviolet-visible absorption spectrum. Solvent effects are taken into account the Self Consistent Reaction Field theory. A detailed analysis of the calculated spectra of E-64 and CA030 excitations is given and we have particularly studied the characteristic transitions around 200 nm. For both the E-64 and the CA030 we have identified the chromophore responsible for the characteristic transition of the inhibitors. In addition, we have considered the influence of the interaction of the CA030 with the enzyme cathepsin B by calculating the ultraviolet-visible spectrum of the inhibitor with the cysteine amino acid.

Orientador: Rubens Maciel Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Qumica / Made available in DSpace on 2018-08-09T18:17:35Z (GMT). No. of bitstreams: 1 Pinto_JeffersonFerreira_D.pdf: 2614838 bytes, checksum: 839b2ff15752c4919e502eaf94e81822 (MD5) Previous issue date: 2006 / Resumo: As indústrias vêm mudando profundamente nos últimos anos, principalmente para redução de consumo energético, melhoria na qualidade dos produtos e adequação às leis ambientais. Estas mudanças podem ser auxiliadas pelas técnicas de modelagem e simulação, incluindo o detalhamento do modelo em nível atômico, quando então recebe o nome de química computacional. Diversas ferramentas abrangendo todas as áreas de química computacional, em sua maioria gratuitas ou de domínio público, foram implementadas em um microcomputador e analisadas para aplicação no desenvolvimento de processos. Foi analisado também o desempenho computacional em função do sistema operacional, que apresentou diferenças no desempenho de até 353% para cálculos de ponto flutuante, 18% para acesso a memória RAM e 67% para acesso a disco. Para melhorar o desempenho computacional, foi elaborado o projeto de um ambiente computacional paralelo de alto desempenho, no qual o custo ficou limitado à aquisição de hardware, de fácil disponibilidade no mercado, sendo que os softwares utilizados são gratuitos ou de domínio público / Abstract: lndustries are changing in the last years, mainly for reduction of energy consumption, improvement in the product quality and adequacy to the environmental laws. These changes can be assisted by the modeling and simulation techniques, including the detailing of the model in atomic leveI, when then it receives the name of computational chemistry. Several tools enclosing all the areas of computational chemistry, in its mainly free or of public domain, had been implemented in a microcomputer and analyzed for application in the processes development. The computational performance in function of the operational system was also analyzed, that presented differences in the performance of up to 353% for floating-point calculations, 18% for access the RAM memory and 67% for access the hard disk. To improve the computational performance the project of high performance computer system was elaborated, in which the cost was limited the acquisition of the hardware, of easy availability in the market, being that software used is free or of public domain / Doutorado / Desenvolvimento de Processos Químicos / Doutor em Engenharia Química

Indium nitride has many applications as a semiconductor. High quality films of indium nitride can be grown using Chemical Vapour Deposition (CVD) and Atomic Layer Deposition (ALD), but the availability of precursors and knowledge of the underlaying chemical reactions is limited. In this study the gas phase decomposition of a new indium precursor, N,N-dimethyl-N',N''-diisopropylguanidinate, has been investigated by quantum chemical methods for use in both CVD and ALD of indium nitride. The computations showed significant decomposition at around 250°C, 3 mbar indicating that the precursor is unstable at ALD conditions. A computational study of the surface chemical mechanism of the adsorption of trimethylindium and ammonia on indium nitride was also performed as a method development for other precursor surface mechanism studies. The results show, in accordance with experimental data, that the low reactivity of ammonia is a limiting factor in thermal ALD growth of indium nitride with trimethylindium and ammonia.

As the demand for clean and renewable energy sources continues to grow, much attention has been given to solid oxide fuel cells (SOFCs) due to their efficiency and low operating temperature. However, the components of SOFCs must still be improved before commercialization can be reached. Of particular interest is the solid electrolyte, which conducts oxygen ions from the cathode to the anode. Samarium-doped ceria (SDC) is the electrolyte of choice in most SOFCs today, due mostly to its high ionic conductivity at low temperatures. However, the underlying principles that contribute to high ionic conductivity in doped ceria remain unknown, and so it is difficult to improve upon the design of SOFCs. This thesis focuses on identifying the atomistic interactions in SDC which contribute to its favourable performance in the fuel cell. Unfortunately, information as basic as the structure of SDC has not yet been found due to the difficulty in experimentally characterizing and computationally modelling the system. For instance, to evaluate 10.3% SDC, which is close to the 11.1% concentration used in fuel cells, one must investigate 194 trillion configurations, due to the numerous ways of arranging the Sm ions and oxygen vacancies in the simulation cell. As an exhaustive search method is clearly unfeasible, we develop a genetic algorithm (GA) to search the vast potential energy surface for the low-energy configurations, which will be most prevalent in the real material. With the GA, we investigate the structure of SDC for the first time at the DFT+U level of theory. Importantly, we find key differences in our results from prior calculations of this system which used less accurate methods, which demonstrate the importance of accurately modelling the system. Overall, our simulation results of the structure of SDCagree with experimental measurements. We identify the structural significance of defects in the doped ceria lattice which contribute to oxygen ion conductivity. Thus, the structure of SDC found in this work provides a basis for developing better solid electrolytes, which is of significant scientific and technological interest. Following the structure search, we perform an investigation of the electronic properties of SDC, to understand more about the material. Notably, we compare our calculated density of states plot to XPS measurements of pure and reduced SDC. This allows us to parameterize the Hubbard (U) term for Sm, which had not yet been done. Importantly, the DFT+U treatment of the Sm ions also allowed us to observe in our simulations the magnetization of SDC, which was found by experiment. Finally, we also study the SDC surface, with an emphasis on its structural similarities to the bulk. Knowledge of the surface structure is important to be able to understand how fuel oxidation occurs in the fuel cell, as many reaction mechanisms occur on the surface of this porous material. The groundwork for such mechanistic studies is provided in this thesis.

It is well established that the morphology and physical properties of an organic semiconducting (OSC) material regulate its electronic properties. However, structure-function relationships remain difficult to describe in polymer-based OSC, which are of particular interest due to their robust mechanical properties. If relationships among the molecular and bulk levels of structure can be found, they can aid in the design of improved materials. To explore and detail important structure-function relationships in polymer-based OSC, this work employs molecular dynamics (MD) simulations to study various π-conjugated polymers in different environments. Two independent investigations are discussed in this work. One investigation examines how the purposeful disruption of the π-conjugated backbone to increase the chain flexibility impacts the chain structure and packing in the condensed phase. This is done by adding a conjugation break spacer (CBS) unit of one to ten carbons in length into the monomer structure of diketopyrrolopyrrole-based polymers. It is found that trends in the folding and glass structure follow the increase and the parity (odd versus even) of the CBS length. The second investigation analyzes a variety of polymers and small molecule acceptor (SMA) blends to observe the effects of changing the shape of either component and the physical properties of the material, as well as the structure of the polymer chains. It is found that the conjugated core, the side chains, and the planarity or sphericity each influence the density and diffusion of the materials made.

abstract: Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them have been explored theoretically or experimentally. Studying this new type of 2D materials with density functional theory (DFT) will inspire the discovery of new 2D materials and open up applications of these materials in electronic and magnetic devices.In this dissertation, DFT is applied to discover novel 2D materials with pentagonal structures. Firstly, I examine the possibility of forming a 2D nanosheet with the vertices of type 15 pentagons occupied by boron, silicon, phosphorous, sulfur, gallium, germanium or tin atoms. I obtain different rearranged structures such as a single-layer gallium sheet with triangular patterns. Then the exploration expands to other 14 types of pentagons, leading to the discoveries of carbon nanosheets with Cairo tessellation (type 2/4 pentagons) and other patterns. The resulting 2D structures exhibit diverse electrical properties. Then I reveal the hidden Cairo tessellations in the pyrite structures and discover a family of planar 2D materials (such as PtP2), with a chemical formula of AB2 and space group pa ̄3. The combination of DFT and geometries opens up a novel route for the discovery of new 2D materials. Following this path, a series of 2D pentagonal materials such as 2D CoS2 are revealed with promising electronic and magnetic applications. Specifically, the DFT calculations show that CoS2 is an antiferromagnetic semiconductor with a band gap of 2.24 eV, and a N ́eel temperature of about 20 K. In order to enhance the superexchange interactions between the ions in this binary compound, I explore the ternary 2D pentagonal material CoAsS, that lacks the inversion symmetry. I find out CoAsS exhibits a higher Curie temperature of 95 K and a sizable piezoelectricity (d11=-3.52 pm/V). In addition to CoAsS, 34 ternary 2D pentagonal materials are discovered, among which I focus on FeAsS, that is a semiconductor showing strong magnetocrystalline anisotropy and sizable Berry curvature. Its magnetocrystalline anisotropy energy is 440 μeV/Fe ion, higher than many other 2D magnets that have been found. Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices. / Dissertation/Thesis / Doctoral Dissertation Materials Science and Engineering 2020

Recent research has shown that small hydrogen bonding catalysts can catalyze the hetero Diels-Alder reaction. In this thesis such hydrogen bonding catalysts in conjunction with varying functional groups and their effect on the hetero Diels-Alder reaction have been investigated. The influence of the different solvents has been investigated as well. The activation barriers for the different region- and stereo isomeric pathways have been compared in order to determine the stereo specificity of the reactions. These calculations have been done using the B3LYP functional for the geometry optimizations and then M06-2X for single point calculations. For the solvated cases the cPCM model and the M06-2X functional were used. It was shown that for the catalyzed systems bulkier groups in the endo position tend to have a lower activation barrier, allowing for control over the stereoselectivity. Electron withdrawing groups have an activating effect and are also synergistic with the hydrogen bonding catalysts. The solvent with the lowest dielectric constant gave the lowest activation barrier.

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