Since the development of the correlation consistent composite approach (ccCA) in 2006, ccCA has been shown to be applicable across the periodic table, producing, on average, energetic properties (e.g., ionization potentials, electron affinities, enthalpies of formation, bond dissociation energies) within 1 kcal/mol for main group compounds. This dissertation utilizes ccCA in the investigation of several chemical systems including nitrogen-containing compounds, sulfur-containing compounds, and carbon dioxide complexes. The prediction and calculation of energetic properties (e.g., enthalpies of formation and interaction energies) of the chemical systems investigated within this dissertation has led to suggestions of novel insensitive highly energetic nitrogen-containing compounds, defined reaction mechanisms for sulfur compounds allowing for increased accuracy compared to experimental enthalpies of formation, and a quantitative structure activity relationship for altering the affinity of CO2 with substituted amine compounds. Additionally, a study is presented on the convergence of correlation energy and optimal domain criteria for local Møller–Plesset theory (LMP2).

<p> Partition Density Functional Theory (P-DFT) is a quantum chemistry method in which the system is fragmented into non-interacting components, and the energy is given by functionals of the fragment densities. The method is unique in the sense that it corrects for density functional approximation errors and sheds light on the individual structure of fragments within a molecule. In this work, we discuss the fundamental aspects of the theory as well as its challenges, and we introduce two software packages that were written to advance the understanding and applicability of the theory. The first, n2v focuses on the numerical procedure to obtain a potential that generates a given density, and the second, pyCADMium performs very accurate P-DFT calculations in diatomic molecules. Both packages are fully open-source and thus can be used and repurposed with any intention. We hope that these advances can be used to develop everyday embedding calculations. </p>

Quantum revolution has a great potential to impose massive impact on information technology. Point defects in solid-state materials such as NV center in diamond have been demonstrated to be promising qubit candidates. Defect levels in band gaps are analogous to molecular orbitals, serving as an excellent platform for quantum applications. Atomically thin two-dimensional materials are under the spotlight in recent years, as the sheet-like geometry brings advantages for operations of quantum defects. That includes the realization of patterned qubit fabrication, operation at room temperature, and improvement of coherence time through a highly-efficient isotope purification process. Although using point defects in 2D materials is a promising route toward quantum applications, searching for viable defects satisfying the criteria of magneto-optical properties for quantum applications is challenging. Thanks to the continued development of density functional theory, sophisticated multi-electron systems can be accurately simulated on the atomistic level to evaluate multiple ground-state properties, including total energy, magnetic polarization, and atomic orbitals. In addition to that, implementing constrained DFT renders the insight of excited-state properties. Benefited from the application of data-science tools in material science, we are now capable of performing data-driven analysis based on high-throughput computational techniques, including data mining/storage and automatic discovery workflow. Adopting the above tools and physical-principle-enabled symmetry analysis, we are able to identify a large set of quantum defects in a vast material space. We show that antisite defects in 2D transition metal dichalcogenides (TMDs) can provide a general platform for controllable solid-state spin qubit systems. Using high-throughput atomistic simulations that are enabled by a symmetry-based hypothesis, we identify several neutral antisite defects in TMDs that create defect levels deep in the bulk band gaps and host a paramagnetic triplet ground state. Our in-depth analysis reveals the presence of optical transitions and triplet-singlet intersystem crossing processes for fingerprinting these defect qubits. Finally, as an illustrative example, we discuss the initialization and readout principles of an antisite qubit in WS2, which is expected to be stable against interlayer interactions in a multilayer structure for qubit isolation and protection in future qubit-based devices. Motivated by the insight gained from the study of antisite defect qubits in TMDs, we significantly expanded the searching domain to all the binary 2D materials. As mentioned above, searching for defects with triplet ground states is one of the most crucial steps to identify more quantum defects that support multiple quantum functionalities. We design a comprehensive workflow for screening promising quantum defects based on the site-symmetry-based hypothesis. The discovery efforts reveal that the symmetry-enabled discovery workflow of quantum defects significantly increases the probability of finding triplet defects. To identify multiple functionalities for these quantum defects, including qubits and quantum emitters, the magneto-optical properties of triplet defects are comprehensively calculated. We demonstrate that 45 antisite defects in the various hosts, including post-transition metal monochalcogenides (PTMCs) and transition metal dichalcogenides (TMDs) are promising quantum defects. Most importantly, we propose that 16 antisites (both anion and cation based) in PTMCs can serve as the most promising quantum defect platform based on 2D materials, due to their well-defined defect levels, optimal magneto-optical properties, and the availability of host materials. This set of data-driven discovery efforts opens a new pathway for creating scalable, room-temperature spin qubits in 2D materials, including TMDs, PTMCs, and beyond. The comprehensive defect data created in this work, combined with experimental verification and demonstration in the future, will eventually lead to the fertilization of a 2D defect design platform that facilitates the design of point defects in 2D material families for multiple quantum functionalities, including quantum emitters, quantum sensor, transductor, and more. / Physics

Nowadays, computational-aided investigations become an essential part in the chemical, biochemical or pharmaceutical research. With increasing computing power, the calculation of larger biological systems becomes feasible. In this work molecular mechanical (MM) and quantum mechanical approaches (QM) and the combination of both (QM/MM) have been applied to study several questions which arose from different working groups. Thus, this work comprises eight different subjects which deals with chemical reactions or proton transfer in enzymes, conformational changes of ligands or proteins and verification of experimental data. This work firstly deals with reaction mechanisms of aromatic inhibitors of cysteine proteases which can be found in many organisms. These enzymes are responsible for various cancer or diseases as for example Human African Trypanosomiasis (HAT) or the Chagas disease. Aromatic SNAr-type electrophiles might offer a new possibility to covalently modify these proteases. Quantum mechanical calculations have been performed to gain insights into the energetics and possible mechanisms. The next chapter also deals with Trypanosomiasis but the focus was set on a different enzyme. The particularity of Trypanosomiasis is the thiol metabolism which can also be modified by covalent inhibitors. In this context, the wild type and point mutations of the enzyme tryparedoxin have been investigated via molecular dynamic (MD) simulations to examine the influence of specific amino acids in regard to the inhibitor. Experimental data showed that a dimerization of the enzyme occurs if the inhibitor is present. Simulations revealed that the stability of the dimer decreases in absence of the inhibitor and thus confirms these experiments. Further investigations concerning cysteine proteases such as cruzain and rhodesain have been conducted with respect to experimental kinetic data of covalent vinylsulfone inhibitors. Several approaches such as QM or QM/MM calculations and docking, MD or MMPBSA/MMGBSA simulations have been applied to reproduce these data. The utilization of force field approaches resulted in a qualitatively accurate prediction. The kinase AKT is involved in a range of diseases and plays an important role in the formation of cancer. Novel covalent-allosteric inhibitors have been developed and crystallized in complex with AKT. It was shown that depending on the inhibitor a different cysteine residue is modified. To investigate these differences in covalent modification computational simulations have been applied. Enoyl-(acyl carrier) (ENR) proteins are essential in the last step of the fatty acid biosynthesis II (FAS) and represent a good target for inhibition. The diphenylether inhibitor SKTS1 which was originally designed to target the ENR’s of Staphylococcus aureus was also crystallized in InhA, the ENR of Mycobacterium tuberculosis (TB). Crystal structures indicate a change of the inhibitor's tautomeric form. This subject was investigated via MD simulations. Results of these simulations confirmed the tautomerization of the inhibitor. This work also deals with the development of a covalent inhibitor originating from a non-covalent ligand. The target FadA5 is an essential enzyme for the degradation of steroids in TB and is responsible for chronic tuberculosis. This enzyme was crystallized in complex with a non-covalent ligand which served as starting point for this study. Computations on QM or QM/MM level and docking and MD simulations have been applied to evaluate potential candidates. The next chapter focuses on the modification of the product spectrum of Bacillus megaterium levansucrase, a polymerase which catalyzes the biosynthesis of fructans. The covalent modification of the wild type or mutants of the enzyme lead to an accumulation of oligosaccharides but also to polymers with higher polymerization degree. To understand these changes in product spectra MD simulations have been performed. Finally, the proton transfer in catalytic cysteine histidine dyads was investigated. The focus was set on the influence of the relaxation of the protein environment to the reaction. Calculations of the enzymes FadA5 and rhodesain revealed that the preferred protonation state of the dyade depends on the protein environment and has an impact on the reaction barrier. Furthermore, the adaptation of the environment to a fixed protonation state was analyzed via MD simulations. / Heutzutage sind computergestützte Untersuchungen ein essentieller Teil in der chemischen, biochemischen oder pharmazeutischen Forschung. Durch die in den Jahren gestiegene Rechenleistung ist die Berechnung biologischer Systeme möglich. Im Rahmen dieser Arbeit wurden molekularmechanische (MM) und quantenmechanische (QM) Methoden sowie die Kombination beider (QM/MM) für verschiedene Studien eingesetzt, die teilweise aus Fragestellungen verschiedener Arbeitsgruppen hervorgegangen sind. Dadurch umfasst diese Arbeit acht verschiedene Themenkomplexe, bei denen chemische Reaktionen, aber auch der Protonentransfer in Enzymen, Konformationsänderungen von Liganden oder Proteinen und die Verifizierung experimenteller Daten im Fokus standen. Die Arbeit befasst sich anfangs mit Reaktionsmechansimen aromatischer Inhibitoren für Cysteinproteasen, Enzyme, welche in vielen Organismen enthalten sind. Diese Enzyme sind für verschiedene Karzinome oder Krankheiten wie der Afrikanischen Trypanosomiasis oder der Chagas-Krankheit verantwortlich. Aromatische SNAr-Elektrophile bieten hierbei eine neue Möglichkeit der kovalenten Modifikation dieser Proteasen. Quantenmechanische wurden durchgeführt, um Einblicke in die Energetik und mögliche Mechanismen zu erhalten. Das nächste Kapitel befasst sich ebenfalls mit Trypanosomiasis, setzt aber den Fokus auf ein anderes Enzym. Die Besonderheit von Trypanosomiasis ist der Thiol Metabolismus, welcher durch kovalente Inhibitoren modifiziert werden kann. In diesem Kontext wurden der Wildtyp und Punktmutationen des Enzyms Tryparedoxin mittels Molekulardynamik Simulationen untersucht, um Interaktionen einzelner Aminosäuren mit dem kovalenten Inhibitor zu evaluieren. Experimentelle Daten zeigten, dass eine Dimerisierung des Enzyms in Anwesenheit des Inhibitors stattfindet. Durch MD-Simulationen konnte gezeigt werden, dass die Stabilität des Dimers in Abwesenheit des Inhibitors sinkt, wodurch experimentellen Daten bestätigt wurden. Weitere Untersuchungen zu Cysteinproteasen wie Cruzain und Rhodeasin wurden durchgeführt, um experimentelle kinetische Daten von kovalenten Vinylsulfon Inhibitoren zu reproduzieren. Hierbei wurden Methoden wie QM oder QM/MM Rechnungen aber auch Docking, MD und MMPBSA/MMGBSA Simulationen angewandt, um diese Daten zu reproduzieren. In den Untersuchungen zeigte sich, dass die Verwendung der Kraftfeld-basierten Methoden zu qualitativ richtigen Vorhersagen führte. Die Kinase AKT ist in einer Reihe von Krankheiten involviert und spielt eine wichtige Rolle bei der Entstehung von Krebs. Neue kovalent-allosterische Inhibitoren wurden entwickelt und im kovalenten Komplex mit AKT kristallisiert. Die Kristallstrukturen zeigten, dass je nach Inhibitor ein anderes Cystein adressiert wurde. Um diese Unterschiede zu untersuchen, wurden computergestützte Simulationen verwendet. Enoyl-(acyl carrier) (ENR) Proteine sind essentiell für den letzten Schritt in der Fettsäurebiosynthese II (FAS) und bilden ein gutes Target zur Inhibition. Der Diphenylether Inhibitor SKTS1, welchen man ursprünglich als Target für den ENR von Staphylococcus aureus entwarf, wurde auch in InhA, dem ENR von Mycobacterium Tuberculosis (TB), kristallisiert. Die Kristallstrukturen weisen je nach Protein auf einen Wechsel der tautomeren Form des Inhibitors hin. Dieser Sachverhalt wurde mittels MD Simulationen untersucht. Hierbei zeigten die Ergebnisse eine Übereinstimmung mit den experimentellen Daten. Diese Arbeit befasst sich ebenfalls mit der Entwicklung eines kovalenten Inhibitors ausgehend von einem nicht-kovalenten Liganden. Das Target FadA5 ist ein integrales Enzym zur Degradation von Steroiden in TB und ist für die chronische Tuberkulose verantwortlich. Dieses Enzym wurde im Komplex mit einem nicht-kovalenten Liganden kristallisiert, welches als Startpunkt dieser Untersuchungen diente. QM, QM/MM, Docking und MD Simulationen wurden hierbei verwandt, um potentielle Kandidaten zu evaluieren. Das nächste Kapitel befasst sich mit der Modifikation des Produktspektrums von Bacillus megaterium Levansucrase, eine Polymerase, welche die Biosynthese von Fruktanen katalysiert. Durch kovalente Modifikatoren im Wildtyp oder bei Mutanten des Enzyms konnte sowohl eine Anreicherung von Oligosacchariden, aber auch von Polymeren mit höherem Polymerisationsgrad erzielt werden. Um diese Änderungen im Produktspektrum zu verstehen, wurden MD Simulationen durchgeführt. Schließlich wurde die Untersuchung des Protonentransfers in katalytischen Cystein Histidin Dyaden durchgeführt. Hierbei stand der Einfluss der Relaxation der Proteinumgebung auf diese Reaktion im Fokus. Berechnungen in den Enzymen FadA5 und Rhodesain zeigten, dass der präferierte Protonierungszustand der Diade von der Proteinumgebung abhängt und einen großen Einfluss auf die Reaktionsbarriere hat. Um dynamische Effekte einzubeziehen, wurde die Adaption der Umgebung auf einen fixierten Protonierungszustand mittels MD Simulationen analysiert.

Atmospheric aerosols are made up of suspended liquids and solids in the atmosphere. These aerosols play a very important role in the solar energy exchange in Earth’s atmosphere as well have dramatic impact on human health. Different aerosols have different effects on the atmosphere depending on the physical properties of the aerosols. The purpose of this research project is to understand how the structure of molecular chromophores impacts the solar absorption properties of aerosols. We propose a series of laboratory studies to investigate the outcomes from solar absorption of brown carbon chromophores: 1-phenylpyrrole, 2-phenyl-1-H-pyrrole, 2-phenylimadazole, as well as water complexes. Ultimately, we aim to reveal molecular-level insights into solar absorption processes of aerosols. Many forms of experimental analysis were performed on the compounds of interest. UV-Vis spectroscopy and fluorescence spectroscopy were used to provide useful information for further analysis such as the region in which the compound fluoresces and the compounds affinity to water for water complex analysis. These compounds were further analyzed using resonant two-photon ionization (R2PI) spectroscopy and computational methods to determine structural characteristics of the compounds with and without water complexes.

Kohn-Sham density functional theory is a widely-used method to predict the ground-state total energies and densities of interacting correlated electrons in atoms, molecules, clusters, solids, and liquids. In principle, exact results for these properties can be found by solving self-consistent one-electron Schrödinger equations based upon density functionals for the energy. In practice, the density functional for the exchange-correlation contribution to the energy must be approximated for the sake of computational efficiency. More accurate but still computationally efficient approximations are being developed by the satisfaction of exact constraints. These include the SCAN (strongly constrained and appropriately normed) semi-local density functional. We used the pressure induced structural phase transition of solids to validate SCAN. To predict an accurate critical pressure, a method must account for a small energy difference between close-lying phases which have very different electronic structures. We computed the critical pressure for the structural phase transition of 25 group IV, III-V, and II-VI compounds using the local density approximation (LDA), Perdew-Burke-Ernzerhof (PBE), and SCAN. LDA systematically underestimates the critical pressures as reported in a previous study. PBE which often improves upon LDA performances yields under- or overestimated pressures in many cases. SCAN, on the other hand, predicts accurate critical pressures with an accuracy comparable to the computationally expensive methods like the quantum Monte Carlo (QMC), random phase approximation (RPA), and the hybrid functional HSE06, in the cases where pressures with these methods are reported. The impressive success of the approximate density functionals, however, comes at a price. There is an incomplete cancellation of the hartree and approximate exchange energies for one-electron densities, giving rise to a spurious interaction of an electron with itself. This is called the self-interaction error (SIE). Perdew-Zunger self-interaction correction (PZ SIC) makes an approximate density functional SIE free for all one-electron density. The transition states, which involve stretched bonds, are poorly described by the semilocal density functionals. Thus LDA, PBE, and SCAN predict too low barrier height for a chemical reaction. We tested the Perdew-Zunger self-interaction correction (PZ SIC) for the barrier heights of the representative test set BH6. We found that the barrier heights are greatly improved when we go from LDA to PBE to SCAN. We also tested the PZ SIC for the atomization energies of the molecular test set AE6. SCAN predicts very accurate atomization energies, whereas SCAN-SIC severely worsens the atomization energies. We attribute such worsening to the noded localized orbitals, over which the PZ energy is minimized. The nodality of the orbital density is a consequence of the orthogonality criterion for overlapping real orbitals, and this nodality increases when free atoms bind to form a molecule. This explains why the error in the atomization energies is reduced when the PZ energy is minimized using complex orbitals, which yield nodeless orbital densities. The complex orbitals, however, do not completely eliminate the error. The remaining error is attributed to the fact that PZ SIC loses the exactness of LDA, PBE, or SCAN for densities that vary slowly over space, calling for a generalization of the PZ theory. / Physics

Nonlinear optics is a field with new applications being regularly discovered, which leads to a growing interest in computing these properties. In this work, we attempt to determine new methods of computationally determining the properties of biologically relevant systems. We do so through testing a novel finite-field method to compute these properties. To facilitate the computation of molecular energies required for finite-field calculations, we tested a hypergeometric resummation scheme. Together, these projects form a strong step into being able to compute the nonlinear optical properties for larger systems of biological relevance. / Thesis / Master of Science (MSc)

Universite de Lille, McMaster University / The main question of this thesis is: do we have today the tools to efficiently describe the structure, the bonding and the thermodynamics of actinide systems? This broad question is answered thanks to three studies. The first two are directly applied to the plastic industry and the nuclear plant safety. The last one, more fundamental, concerns the benchmarking of newly developed theoretical approach on f-element systems. First, actinides and transition metal arene-coordinated alkyl cations have been recently proven to be efficient catalysts for ethylene polymerizations. Interestingly, thorium, uranium and zirconium alkyl cations? catalytic activity depends on the solvent. To understand these behaviors and to confirm the tendency of these complexes to engage in unusual-arene coordination, relativistic DFT calculations combined with a characterization of the interaction thanks to the ETSNOCV method are used. Second, in accident scenario along the reprocessing of spent nuclear fuel, plutonium can be released in various volatile forms (PuO2, PuO3 or PuO2(OH)2, ...). The exploration of these scenarios by the use of simulations requires, among the various parameters, the knowledge of the thermodynamic properties of the possibly formed elements. Our insilico study focusses on the determination of the enthalpies of formation of the former two species for which experimental uncertainties remain, using multi-configurational relativistic wavefunction method. The last part of the thesis focusses on the benchmark of the B2-PLYP functional for f-element systems, which turns out quite accurate with respect to the experimental data and the gold-standard CCSD(T) method. La question générale traitée dans cette thèse est de déterminer si, aujourd’hui, nous disposons d óutils théoriques efficaces pour d’ écrire la structure, la liaison et les propriétés thermodynamiques de système comprenant un actinide. Cette large question va être abordée à láide de trois études différentes. Les deux premières sont directement liées à l?industrie plastique et à la sureté nucléaire. La dernière, plus fondamentale concerne une analyse comparative d?une approche théorique nouvellement développée sur des systèmes comprenant des éléments f. Tout dábord, les cations alkyles contenant un actinide (Th, U) ou un métal de transition (Zr) coordonné à un arène se sont révélés efficaces pour la catalyse de la synthèse du polyéthylène. étonnamment, les activités catalytiques des cations alkyles dépendent du solvant. Pour comprendre cela et confirmer la tendance quónt ces complexes à se lier à l?arène, une étude en DFT dans un contexte relativiste combinée à une caractérisation de liaison avec la méthode ETS-NOCV fut faite. La deuxième étude vise à étoffer les bases de données thermodynamiques qui servent à explorer numériquement les scénarios d?accidents. Notre étude in silico porte sur la détermination des enthalpies de formation des deux espèces pour lesquelles des incertitudes expérimentales subsistent (PuO3 ou PuO2(OH)2, ...), en utilisant une méthode quantique multiconfigurationnelle et relativiste. La dernière partie de la théorie se concentre sur l?estimation de la précision de la fonctionnelle B2-PLYP pour les éléments f, qui sávère assez précise en comparaison aux données expérimentales et à la méthode de référence CCSD(T). / Thesis / Doctor of Philosophy (PhD)

<p dir="ltr">In computer-aided drug discovery, methods that are approximate, but computationally inexpensive play an essential role during the initial phase of the discovery process. Although often inaccurate, they enable the screening of vast drug libraries to identify potential inhibitors with favorable activities, before large amounts of computational resources could be dedicated to studying these individual molecules. This thesis presents<b> </b>such an approach, based on the concept of hydrogen bond wrapping, to study protein-ligand interactions in the context of drug discovery. The ‘wrapping’ refers to the tendency of hydrophobic groups to surround a hydrogen bond in water, leading to its desolvation, thereby stabilizing it.</p><p dir="ltr">Herein, a molecular descriptor was employed, which quantifies the extent of hydrophobic wrapping around a protein’s backbone hydrogen bonds (BHBs) and could help speed up the discovery process by providing cues for the design or optimization of inhibitors. Additionally, these insights could help tailor not just the binding affinity of inhibitors, but also their specificity toward an intended target protein. The human transmembrane protease serine 2 (TMPRSS2) was used as an illustrative target protein due to the pressing need for COVID-19 therapeutics, and since the current understanding of the binding mechanisms of known TMPRSS2 inhibitors is limited.</p><p dir="ltr">Molecular docking with a Generalized Born - surface area (GBSA) scoring function was first performed to virtually screen for TMPRSS2 inhibitors. The molecular descriptor was then used to analyze the change in wrapping groups of TMPRSS2 BHBs due to docked ligands, with the aim of identifying BHBs with a high propensity for desolvation. The BHBs involving residues Cys437, Gln438, Asp440, and Ser441 of TMPRSS2 were seen to have some of the largest average increases in wrapping. These general results were also compared to results from docking of the known TMPRSS2 inhibitors, camostat, and nafamostat.</p><p dir="ltr">The data generated from docking were then used to examine potential applications of the wrapping molecular descriptor using machine learning techniques: (i) for prediction of the solvent-accessible surface area term ΔG_sa of the GBSA score using regression and (ii) for classifying the solvent interactions of a TMPRSS2-inhibitor complex as favorable or unfavorable. The descriptor was seen to be only weakly related to ΔG_sa; the best-performing regression model had a Pearson correlation coefficient of 0.76 between the predictions and the actual values. The ability of the descriptor to classify solvent interactions was more satisfactory, with a highest value for area under the receiver operating characteristic curve of 0.75.</p><p dir="ltr">The descriptor was then used to analyze the effect of inhibitor binding on the dynamics of TMPRSS2 BHBs. For this, molecular dynamics simulation was carried out for the uncomplexed TMPRSS2, as well as its complex with known inhibitors and hit molecules from docking. The binding of these ligands was seen to improve the stability of TMPRSS2; certain BHBs which were unstable or not formed in the uncomplexed case, showed increased stability. These prominently included a couple of BHBs identified from docking as having gained a large increase in wrapping. The improved stability coincided with an increase in wrapping groups in several cases. The descriptor also successfully rationalized the desolvation of a few BHBs due to inhibitor binding.</p><p dir="ltr">This work demonstrates the potential application of the concept of hydrogen bond wrapping in understanding the mechanism of inhibitor binding and the resultant desolvation effects on a protein’s BHBs, without computationally expensive calculations. While the analysis methods require further improvement, the wrapping descriptor shows promising results and could be developed into a simple, yet powerful tool for drug discovery.</p>

No / No Abstract