Rozprawy doktorskie na temat „Computational Chemistry Method”

Brief explanation and history of cinchona based Phase Transfer Catalysis (PTC). Studied aryl acetates in PTC, encompassing napthoyl, 6-methoxy napthoyl, phenyl and protected 4-hydroxy phenyl acetates. Investigated means of controlling the selectivity of the PTC reaction by changing the electrophile size, the ether side group size or by addition of inorganic salts. Found that either small or aromatic electophiles increased enantioselectivity more than aliphatic electrophiles, and that increasing the size of ether protecting group also increased selectivity. Positive effects of salt addition included either decreasing reaction time or increasing enantiomeric excess. Applied findings towards the synthesis of S-equol. Computational experiments working towards deducing the transition state between PTC and aryl acetate substrates.

Solubility is the concentration of a solute in a saturated solution at a given temperature and pressure. Solubility of a drug in aqueous media is a pre-requisite to achieve desired concentration of a drug in the systemic circulation. Low aqueous solubility is a major problem encountered with formulation development of recently designed new chemical entities. Solubility of poorly soluble drugs is enhanced by physical and chemical modifications of drug. Shake flask method is the most commonly used experimental method to determine solubility. However, this method has several limitations. A single solubility experiment can go on for several days and even weeks. Besides this, a large amount of drug is required to carry out the experiment. In order to overcome this and make initial screening easier, computational method can be used to predict solubility. In this study, the solubility of 12 small molecules of BCS class II having a wide range of physicochemical properties were studied to enhance their solubility by hot melt method. Three different grades of PEG (1450, 4000, 8000), PVP K17 and Urea as the hydrophilic carriers was employed for the solubility enhancement. The overall objective of this investigation is to develop a model that could estimate enhanced solubility using physicochemical descriptors. Multiple linear regression (MLR), a statistical tool, was used to generate a equation for the solubility by correlating physicochemical properties of the drug like- molecular size, logP, pKa, HBA, HBD, melting point, polar surface area, and number of rotatable bonds. Solubility enhancement is also influenced by the carrier used, we included the physicochemical properties of the carriers like molecular weight and solubility parameter in the development of the model. MLR analysis model, resulted in an equation, where, Log solubility = 5.982-0.010 MW (drug)-0.452 LogP-0.320 HBA-0.095 ?solubility parameter+0.015 MV. A regression analysis yielded a good fit with a regression value (adjusted R2) of 0.74. The model has been validated by leave one out method. This model has the potential to estimate the solubility of a physically modified drug in screening stages of drug development.

The data presented in this thesis is a comprehensive study on the nature of peptide structure and how subtle and systematic changes in sequence and sidechain affect the basicity, ion stability, and conformation of a peptide. The peptides characterized were acetylated polyalanine di-, tri-, and tetra- peptides containing a proton-accepting probe: lysine and or the non-proteinogenic lysine-homologs: ornithine, 2,4-diaminobutyric acid, and 2,3-diaminopropionic acid. Peptides were studied in isomeric pairs for which the basic amino acid was placed closest to the N-terminus or the C-terminus of each peptide family (A n Probe vs. ProbeA n ). Using a variety of mass spectrometry based techniques and infrared multiphoton dissociation ion spectroscopy, the isomeric families of polyalanine peptides were characterized. Quantum chemical techniques were employed in parallel to provide theoretical predictions of three-dimensional structure, physical properties (dipole moment, polarizability, and accessible surface area), thermochemical values, and vibrational IR spectra, to gain further understanding of the peptides studied and to push the limits of current theoretical models. Overall it was found that the AnProbe peptide was more basic than their ProbeAn isomer. For the dipeptide systems, the greater basicity of AProbe peptides was due to efficiently charge-solvated ions which formed more compact structures compared to their ProbeA counterpart. For the tri- and tetra- peptide systems, greater basicity of the A 2,3 Probe peptides was likely due to formation of α or 3 10 helix-like structures in the protonated forms., introducing the macrodipolar effect, which cooperatively encouraged helical formation while stabilizing the charged site. On the other hand, ProbeA 2,3 peptides formed charge-solvated coils which do not exhibit any kind of dipole effect, resulting in lower basicity than their A2,3Probe counterpart.

Numerous enzymatic reactions are controlled by the chemistry of metallic ions. This dissertation investigates the electronic properties of three transition metal (copper, chromium, and nickel) complexes and describes modeling studies performed on glutathione synthetase. (1) Copper nitrene complexes were computationally characterized, as these complexes have yet to be experimentally isolated. (2) Multireference calculations were carried out on a symmetric C2v chromium dimer derived from the crystal structure of the [(tBu3SiO)Cr(µ-OSitBu3)]2 complex. (3) The T-shaped geometry of a three-coordinate β-diketiminate nickel(I) complex with a CO ligand was compared and contrasted with isoelectronic and isosteric copper(II) complexes. (4) Glutathione synthetase (GS), an enzyme that belongs to the ATP-grasp superfamily, catalyzes the (Mg, ATP)-dependent biosynthesis of glutathione (GSH) from γ-glutamylcysteine and glycine. The free and reactant forms of human GS (wild-type and glycine mutants) were modeled computationally by employing molecular dynamics simulations, as these currently have not been structurally characterized.

[ES] En este trabajo estudiamos dos reacciones catalíticas relevantes para la industria y la localización del anión fluoruro en la zeolita RTH, sintetizada en medio fluoruro. El capítulo 3 es el primer capítulo de resultados, donde se estudia la reducción quimioselectiva del nitroestireno en las superficies Ni(111), Co(111), Cu(111) y Pd(111). El mecanismo generalmente aceptado de esta reacción está basado en el esquema propuesto por Haber en 1898, en el que la reacción puede transcurrir por dos rutas, la directa y la de condensación. En este capítulo exploramos ambas rutas, y observamos que la ruptura de los enlaces N-O y la consecuente formación de enlaces metal-O está más favorecida que la formación de enlaces N-H en las superficies Ni(111) y Co(111), debido al carácter oxofílico de ambos metales. Las etapas más lentas involucran la formación de enlaces N-H. En las superficies de metales nobles como Pt(111) y Pd(111) se observa el comportamiento contrario. La superficie Cu(111) es un caso intermedio comparado con los metales nobles y no nobles. Además, el nitroestireno interactúa con los átomos de Cu de la superficie solo a través de grupo nitro, con lo cual es un candidato ideal para alcanzar selectividades cerca del 100%. Sin embargo, la superficie Cu(111) no es capaz de activar la molécula de H2. En este sentido, proponemos un catalizador bimetálico basado en Cu, dopado con otro metal capaz de activar al H2, tales como el Pd o el Ni. En los capítulos 4 y 5 se ha estudiado la reducción catalítica selectiva de los óxidos de nitrógeno (SCR, en inglés) con amoníaco. Usando métodos de DFT, hemos encontrado rutas para la oxidación de NO a NO2, nitritos y nitratos con energías de activación relativamente bajas. También, hemos encontrado que la reducción de Cu2+ a Cu+ requiere la participación simultánea de NO y NH3. Posteriormente, hemos estudiado la influencia del NH3 en este sistema con métodos de dinámica molecular. El NH3 interacciona fuertemente con el Cu+ de forma que dos moléculas de este gas son suficientes para romper la coordinación del catión Cu+ con los oxígenos del anillo 6r, y formar el complejo lineal [Cu(NH3)2]+. Además, los cationes Cu2+ pueden ser estabilizados fuera de la red mediante la formación del complejo tetraamincobre(II). Debido a la presencia de los cationes Cu+ y Cu2+ coordinados a la red de la zeolita, aparecen bandas en la región entre 800-1000 cm-1 del espectro infrarrojo. El análisis de las frecuencias IR de varios modelos con Cu+ y Cu2+ coordinados al anillo 6r, o formando complejos con amoniaco indica que cuando los cationes Cu+ y Cu2+ están coordinados a los oxígenos del anillo 6r aparecen vibraciones entre 830 y 960 cm-1. Frecuencias en esta zona también se obtienen en los casos en que NO, NO2, O2 y combinaciones de dos de ellos están adsorbidos en Cu+ y Cu2+. Sin embargo, cuando los cationes Cu+ y Cu2+ están fuera del anillo (no hay enlaces entre los cationes de cobre y los oxígenos del anillo 6r) no se obtienen vibraciones de IR en esta región del espectro. Estos resultados indican que con el seguimiento del espectro IR durante la reacción SCR es posible determinar si los cationes Cu+ y Cu2+ están coordinados o no al anillo de 6r en las etapas de oxidación y reducción. Por último, hemos simulado el desplazamiento químico de 19F, δiso,, en la zeolita sintetizada RTH. El análisis del δiso de los distintos modelos utilizados nos ha permitido reconocer la simetría del material sintetizado, el cual pertenece al grupo espacial P1 y la nueva celda unidad ha sido confirmada experimentalmente por difracción de rayos X. Finalmente, hemos asignado la señal experimental que aparece en el espectro de 19F a -67.2_ppm, al F- localizado en un sitio T2, el cual es a su vez la posición más estable. Además, la señal a -71.8 ppm se ha asignado al anión F- localizado en un sitio T4.
[CA] En aquest treball estudiem dues reaccions catalítiques rellevants per a la indústria i la localització de l'anió fluorur en la zeolita RTH, sintetitzada al mig fluorur. El capítol 3 és el primer capítol de resultats, on s'estudia la reducció quimioselectiva del nitroestireno en les superfícies Ni(111), Co(111), Cu(111) i Pd(111). El mecanisme generalment acceptat d'aquesta reacció està basat en l'esquema proposat per Haver-hi en 1898, en el qual la reacció pot transcórrer per dues rutes, la directa i la de condensació. En aquest capítol explorem totes dues rutes, i observem que la ruptura dels enllaços N-O i la conseqüent formació d'enllaços metall-O està més afavorida que la formació d'enllaços N-H en les superfícies Ni(111) i Co(111), a causa del caràcter oxofílico de tots dos metalls. Les etapes més lentes involucren la formació d'enllaços N-H. En les superfícies de metalls nobles com Pt(111) i Pd(111) s'observa el comportament contrari. La superfície Cu(111) és un cas intermedi comparat amb els metalls nobles i no nobles. A més, el nitroestireno interactua amb els àtoms de Cu de la superfície sol a través de grup nitre, amb la qual cosa és un candidat ideal per a aconseguir selectivitats prop del 100%. No obstant això, la superfície Cu(111) no és capaç d'activar la molècula d'H2. En aquest sentit, proposem un catalitzador bimetàl·lic basat en Cu, dopat amb un altre metall capaç d'activar a l'H2, com ara el Pd o el Ni. En els capítols 4 i 5 hem estudiat la reducció catalítica selectiva dels òxids de nitrogen (SCR, en anglés) amb amoníac. Usant mètodes de DFT, hem trobat rutes per a l'oxidació de NO a NO2, nitrits i nitrats amb energies d'activació relativament baixes. També, hem trobat que la reducció de Cu2+ a Cu+ requereix la participació simultània de NO i NH3. Posteriorment, hem estudiat la influència del NH3 en aquest sistema amb mètodes de dinàmica molecular. El NH3 interacciona fortament amb el Cu+ de manera que dues molècules d'aquest gas són suficients per a trencar la coordinació del catió Cu+ amb els oxígens de l'anell 6r, i formar el complex lineal [Cu(NH3)2]+. A més, els cations Cu2+ poden ser estabilitzats fora de la xarxa mitjançant la formació del complex tetraamincobre(II). A causa de la presència dels cations Cu+ i Cu2+ coordinats a la xarxa de la zeolita, apareixen bandes a la regió entre 800-1000 cm-1 de l'espectre infraroig. L'anàlisi de les freqüències IR de diversos models amb Cu+ i Cu2+ coordinats a l'anell 6r, o formant complexos amb amoníac indica que quan els cations Cu+ i Cu2+ estan coordinats als oxígens de l'anell 6r apareixen vibracions entre 830 i 960 cm-1. Freqüències en aquesta zona també s'obtenen en els casos en què NO, NO2, O2 i combinacions de dues d'ells estan adsorbidos en Cu+ i Cu2+. No obstant això, quan els cations Cu+ i Cu2+ estan fora de l'anell (no hi ha enllaços entre els cations de coure i els oxígens de l'anell 6r) no s'obtenen vibracions d'IR en aquesta regió de l'espectre. Aquests resultats indiquen que amb el seguiment de l'espectre IR durant la reacció SCR és possible determinar si els cations Cu+ i Cu2+ estan coordinats o no a l'anell de 6r en les etapes d'oxidació i reducció. Finalment, hem simulat el desplaçament químic de 19F, δiso, en la zeolita sintetitzada RTH. L'anàlisi del δiso dels diferents models utilitzats ens ha permés reconéixer la simetria del material sintetitzat, el qual pertany al grup espacial P1 i la nova cel·la unitat ha sigut confirmada experimentalment per difracció de raigs X. Finalment, hem assignat el senyal experimental que apareix en l'espectre de 19F a -67.2 ppm, al F- localitzat en un lloc T2, el qual és al seu torn la posició més estable. A més, el senyal a -71.8 ppm s'ha assignat a l'anió F- localitzat en un lloc T4.
[EN] In this work, we have studied two heterogeneous catalytic reactions and the localization of the fluoride anion in the as-made RTH framework, synthesized in fluoride medium. The first results, included in chapter 3, correspond to the chemoselective reduction of nitrostyrene on different metal surfaces, i.e, Ni(111), Co(111), Cu(111) and Pd(111). Until very recently, the reduction of the nitro group was explained on the basis of the general mechanism proposed by Haber in 1898 where the reaction can follow two routes, the direct and condensation route. We have explored the relevant elementary steps of both routes and found that because of the oxophilic nature of Ni and Co, the steps involving the dissociation of N-O bonds and formation of metal-O bonds are significantly favored compared with the other steps on both metal surfaces. In addition, the most demanding steps in terms of energy involve the formation of N-H bonds. These findings are in contrast to those of noble metals such as Pt and Pd, where the opposite behavior is observed. The behavior of Cu(111) lies in between the aforementioned cases, and also no chemical bonds between the carbon atoms of the aromatic ring of nitrostyrene and the Cu(111) surface is formed. For this reason, it might be an ideal candidate to achieve nearly 100 % selectivity. However, the Cu(111) surface does not seem to activate the H2 molecule. In this regard, we propose a bimetallic Cu-based catalyst whose surface is doped with atoms of a H2-activating metal, such as Ni or Pd. On another matter, we have also investigated the selective catalytic reduction of nitrogen oxides (SCR-NOx) and the main results are presented in the following two chapters, 4 and 5. By using static DFT methods, we found pathways for the oxidation of NO to NO2, nitrites and nitrates with relatively low activation energies. We also found, in agreement with experimental reports, that the reduction of Cu2+ to Cu+ requires the simultaneous participation of NO and NH3. Later, molecular dynamics simulations allowed us to assess the influence of NH3. The strong interaction of NH3 with the Cu+ cation is evidenced by its ability to detach Cu+ from the zeolite framework and form the mobile linear complex [Cu(NH3)2]+. Cu+ is no longer coordinated to the zeolite framework in the presence of two NH3 molecules. This observation and the fact that the T-O-T vibrations of the framework produce bands in the 800-1000 cm-1 region of the IR spectrum when perturbed by the coordination of Cu+ and Cu2+ cations, indicate that bands in the 800-1000 cm-1 regions should be observed when both copper cations are bonded to the framework oxygens. Finally, we have also studied NMR properties of the as-made pure silica RTH framework, aiming at locating the compensating fluoride anion. The calculation of the 19F chemical shift in different T sites and comparison with the experimental NMR spectra shows that the as-made RTH belongs to the P-1 space group with 16 Si, 32 O atoms, one fluoride anion and one OSDA cation. These results have been confirmed experimentally by XRD. In addition, we have assigned the experimental signal of 19F at -67.2 ppm to the fluoride anion in a T2 site, which in turn is the most stable location found, and the signal of -71.8 ppm to a fluoride anion sitting in a T4 site.
My acknowledgements to “La Caixa foundation” for the financial support through “La Caixa−Severo Ochoa” International PhD Fellowships (call 2015), to the Spanish Supercomputing Network (RES), to the Centre de Càlcul de la Universitat de València, to the Flemish Supercomputer Center (VSC) of Ghent University for the computational resources and technical support, and to the Spanish Government through the MAT2017-82288-C2-1-P programme
Millan Cabrera, R. (2021). Computational study of heterogeneous catalytic systems. Kinetic and structural insights from Density Functional Theory [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/161934
TESIS

Enzymes play a crucial role in modern biotechnology, industry, food processing and medical applications. Since their first discovered industrial use, man has attempted to discover new enzymes from Nature to catalyze different chemical reactions. In modern times, with the advent of computational methods, protein structure solutions, protein sequencing and DNA synthesis methods, we now have the tools to enable new approaches to rational enzyme engineering. With an enzyme structure in hand, a researcher may run an in silico experiment to sample different amino acids in the active site in order to identify new combinations which likely stabilize a transition-state-enzyme model. A suggested mutation can then be encoded into the desired enzyme gene, ordered, synthesized and tested. Although this truly astonishing feat of engineering and modern biotechnology allows the redesign of existing enzymes to acquire a new substrate specificity, it still requires a large amount of time, capital and technical capabilities.

Concurrently, while making strides in computational protein design, the cost of sequencing DNA plummeted after the turn of the century. With the reduced cost of sequencing, the number of sequences in public databases of naturally occurring proteins has grown exponentially. This new, large source of information can be utilized to enable rational enzyme design, as long as it can be coupled with accurate modeling of the protein sequences.

This work first describes a novel approach to reengineering enzymes (Genome Enzyme Orthologue Mining; GEO) that utilizes the vast amount of protein sequences in modern databases along with extensive computation modeling and achieves comparable results to the state-of-the-art rational enzyme design methods. Then, inspired by the success of this new method and aware of it's reliance on the accuracy of the protein models, we created a computational benchmark to both measure the accuracy of our models as well as improve it by encoding additional information about the structure, derived from mechanistic studies (Catalytic Geometry constraints; CG). Lastly, we use the improved accuracy method to automatically model hundreds of putative enzymes sequences and dock substrates into them to extract important features that are then used to inform experiments and design. This is used to reengineer a ribonucleotide reductase to catalyze a aldehyde deformylating oxygenase reaction.

These chapters advance the field of rational enzyme engineering, by providing a novel technique that may enable efficient routes to rationally design enzymes for reactions of interest. These chapters also advance the field of homology modeling, in the specific domain in which the researcher is modeling an enzyme with a known chemical reaction. Lastly, these chapters and techniques lead to an example which utilizes highly accurate computational models to create features which can help guide the rational design of enzyme catalysts.

In this thesis I described the theory and application of several computational methods in solving medicinal chemistry and biophysical tasks. I pointed out to the valuable information which could be achieved by means of computer simulations and to the possibility to predict the outcome of traditional experiments. Nowadays, computer represents an invaluable tool for chemists. In particular, the main topics of my research consisted in the development of an automated docking protocol for the voltage-gated hERG potassium channel blockers, and the investigation of the catalytic mechanism of the human peptidyl-prolyl cis-trans isomerase Pin1.

In this thesis I described the theory and application of several computational methods in solving medicinal chemistry and biophysical tasks. I pointed out to the valuable information which could be achieved by means of computer simulations and to the possibility to predict the outcome of traditional experiments. Nowadays, computer represents an invaluable tool for chemists. In particular, the main topics of my research consisted in the development of an automated docking protocol for the voltage-gated hERG potassium channel blockers, and the investigation of the catalytic mechanism of the human peptidyl-prolyl cis-trans isomerase Pin1.

One of the central concerns of computational chemistry is that of efficiency (i.e. the development of methodologies which will yield increased accuracy of prediction without requiring additional computational resources – RAM, disk space, computing time). Though the equations of quantum mechanics are known, the solutions to these equations often require a great deal of computing power. This dissertation primarily concerns the theme of improved computational efficiency (i.e. the achievement of greater accuracy with reduced computational cost). Improvements in the efficiency of computational chemistry are explored first in terms of the correlation consistent composite approach (ccCA). The ccCA methodology was modified and this enhanced ccCA methodology was tested against the diverse G3/05 set of 454 energetic properties. As computational efficiency improves, molecules of increasing size may be studied and this dissertation explored the issues (differential correlation and size extensivity effects) associated with obtaining chemically accurate (within 1 kcal mol-1) enthalpies of formation for hydrocarbon molecules of escalating size. Two applied projects are also described; these projects concerned the theoretical prediction of a novel rare gas compound, FKrOH, and the mechanism of human glutathione synthetase’s (hGS) negative cooperativity. The final work examined the prospect for the parameterization of the modified embedded atom method (MEAM) potential using first principles calculations of dimer and trimer energies of nickel and carbon systems. This method of parameterization holds promise for increasing the accuracy of simulations for bulk properties within the field of materials science.

Computational methods have become an integral part of drug development and can help bring new and better drugs to the market faster. The process of predicting the biological activity of large compound collections is known as virtual screening, and has been instrumental in the development of several drugs today in the market. Computational methods can also be used to elucidate the energies associated with chemical reactivity and predict how to improve a synthetic protocol. These two applications of computational medicinal chemistry is the focus of this thesis. In the first part of this work, quantum mechanics has been used to probe the energy surface of palladium(II)-catalyzed decarboxylative reactions in order to gain a better understating of these systems (paper I-III). These studies have mapped the reaction pathways and been able to make accurate predictions that were verified experimentally. The other focus of this work has been to develop virtual screening methodology. Our first study in the area (paper IV) investigated if the results from several virtual screening methods could be combined using data fusion techniques in order to get a more consistent result and better performance. The study showed that the results obtained from data fusion were more consistent than the results from any single method. The data fusion methods also for several target had a better performance than any of the included single methods. Next, we developed a dataset suitable for evaluating the performance of virtual screening methods when applied to large compound collection as a replacement or complement for high throughput screening (paper V). This is the first benchmark dataset of its kind. Finally, a method for using computationally derived reaction coordinates as basis for virtual screening was developed. The aim was to find inhibitors that resemble key steps in the mechanism (paper VI). This initial proof of concept study managed to locate several known and one previously not reported reaction mimetics against insulin regulated amino peptidase.

The research described in this dissertation concerns two fields of theoretical chemistry: Part I concerns applications of Density Functional Theory, and part II high accuracy calculations within the Born-Oppenheimer approximation using explicitly correlated Gaussian functions.In the first part, after a brief introduction to Density Functional Theory and Hartree Fock methods, the candidate's research in Density Functional Theory is described in two chapters. One treats the charge transport in B-DNA, specifically (GC)$_N$ oligomers solvated by water. The second chapter treats the charge transfer between the Lithium atom and Fullerene-C$_{60}$ in the endohedral complex Li@C$_{60}$. In both applications Density Functional Theory was the central quantum mechanical technique that allowed the approaching of such large molecular systems.In the second part of this dissertation, the candidate's development of a FORTRAN code using explicitly correlated Gaussian functions within the Born-Oppenheimer approximation is presented.Every item of the author's research during his graduate studies has been published in co-authorship with the author's scientific advisor and other collaborators in peer-reviewed journals. A total of 8 scientific articles and one letter have been published by the author while at The University of Arizona.

At the atomic scale, interactive physically-based modeling tools are more and more in demand. Unfortunately, solving the underlying physics equations at interactive rates is computationally challenging. In this dissertation, we propose new algorithms that allow for interactive modeling of chemical structures. We first present a modeling tool to construct structural models of hydrocarbon systems. The physically-based feedbacks are based on the Brenner potential. In order to be able to interactively edit systems containing numerous atoms, we introduce a new adaptive simulation algorithm. Then, we introduce what we believe to be the first interactive quantum chemistry simulation algorithm at the Atom Superposition and Electron Delocalization Molecular Orbital (ASED-MO) level of theory. This method is based on the divide-and-conquer (D&C) approach, which we show is accurate and efficient for this non-self-consistent semi-empirical theory. We then propose a novel Block-Adaptive Quantum Mechanics (BAQM) approach to interactive quantum chemistry. BAQM constrains some nuclei positions and some electronic degrees of freedom on the fly to simplify the simulation. Finally, we demonstrate several applications, including one study of graphane formation, interactive simulation for education purposes, and virtual prototyping at the atomic scale, both on desktop computers and in virtual reality environments.

In recent years, advances in computer technology combined with new ab initio computational methods have allowed for dramatic improvement in the prediction of energetic properties. Unfortunately, even with these advances, the extensive computational cost, in terms of computer time, memory, and disk space of the sophisticated methods required to achieve chemical accuracy - defined as 1 kcal/mol from reliable experimental data effectively - limits the size of molecules [i.e. less than 10-15 non-hydrogen atoms] that can be studied. Several schemes were explored to help reduce the computational cost while still maintaining chemical accuracy. Specifically, a study was performed to assess the accuracy of ccCA to compute atomization energies, ionization potentials, electron affinities, proton affinities, and enthalpies of formation for third-row (Ga-Kr) containing molecules. Next, truncation of the correlation consistent basis sets for the hydrogen atom was examined as a possible means to reduce the computational cost of ab initio methods. It was determined that energetic properties could be extrapolated to the complete basis set (CBS) limit utilizing a series of truncated hydrogen basis sets that was within 1 kcal/mol of the extrapolation of the full correlation consistent basis sets. Basis set truncation for the hydrogen atom was then applied to ccCA in the development of two reduced basis set composite methods, ccCA(aug) and ccCA(TB). The effects that the ccCA(aug) and ccCA(TB) methods had upon enthalpies of formation and the overall percent disk space saved as compared to ccCA was examined for the hydrogen containing molecules of the G2/97 test suite. Additionally, the Weizmann-n (Wn) methods were utilized to compute the several properties for the alkali metal hydroxides as well as the ground and excited states of the alkali monoxides anion and radicals. Finally, a multi-reference variation to the correlation consistent Composite Approach [MR-ccCA] was presented and utilized in the computation of the potential energy surfaces for the N2 and C2 molecules.

L’hydrogénation sélective de l’acétylène est un processus fondamental pour l’industrie pétrochimique qui permet la purification de l’éthylène utilisé dans les réactions de polymérisation. Ce processus est promu par des catalyseurs au palladium, qui présentent une bonne sélectivité en éthylène par rapport au produit d’hydrogénation totale, c’est-à-dire l’éthane. Les catalyseurs de palladium pur sont malheureusement désactivés par des oligomères qui se forment comme sous-produits de la réaction d’hydrogénation. Les catalyseurs d’usage industriel sont, pour cette raison, plutôt des alliages de palladium avec d’autres métaux, comme par exemple, l’argent. Ces alliages réduisent la production des oligomères, sans pour autant les supprimer complètement. Ce travail de thèse a été focalisé sur la compréhension à l’échelle moléculaire de la formation de ce mélange d’oligomères, souvent appelée « huile verte ». Pour commencer, une approche de champ moyen a été développée pour déterminer rapidement l’état de la surface catalytique de l’alliage Pd-Ag en condition de réaction. Ce modèle a montré que l’acétylène est capable de réorganiser la couche de la surface et de générer des îles de palladium. Pour confirmer cette prédiction, nous avons effectué des simulations Monte Carlo en utilisant un Hamiltonien modèle. Ces calculs ont produits des résultats similaires au modèle analytique simple. Ayant attribué la formation des oligomères aux domaines de palladium ainsi obtenus, les étapes de d’oligomérisation ont été étudies et comparés à celles qui décrivent l’hydrogénation de l’acétylène. Les calculs, réalisé avec l’approximation de la théorie de la fonctionnelle de la densité (DFT), ont montré que la formation des oligomères est compétitive avec l’hydrogénation. En plus, les oligomères sont plus faciles à hydrogéner que l’acétylene et pourraient, donc, impacter négativement sur l’hydrogénation sélective de l’acétylène. Le rôle exact des îles de palladium sous conditions réalistes est encore à clarifier, sachant que le palladium est recouvert d’une grande variété d’espèces chimiques. Les techniques d’intelligence artificielle peuvent aider à atteindre ce but : nous avons ainsi démontré qu’il est possible d’interpoler les résultats des calculs DFT d’une façon automatique et de décrire l’énergie du système en série de coefficients « cluster ». Ceci permet de prendre en compte les interactions latérales entre espèces chimiques à la surface du palladium
Selective hydrogenation of acetylene in ethylene-rich flows is a fundamental process in the petrochemical industry since it allows the purification of ethylene for polymer applications. The reaction is catalyzed by Pd, which features acceptable selectivity towards ethylene compared to the total hydrogenation product, ethane. Pure Pd is, however, deactivated by oligomeric byproducts, known as ”green oil” in the literature. Therefore, most industrial catalysts are Pd-Ag alloys, where Ag helps to suppress the secondary reactions. This work addresses the formation of initial oligomers on Pd and Ag-Pd catalysts. A mean field based theoretical model was built to efficiently screen the topology of the topper most layer of the alloy catalyst under relevant conditions. This model gave evidence for strongly favored Pd island formation. To confirm this result, the system was then re-investigated by means of Monte Carlo simulations including the effect of segregation. Emergence of large domains of Pd were confirmed over large ratios of Ag to Pd. Green oil is expected to form on these catalytically active islands. To obtain a detailed view on the oligomerization process, activation energies were computed both for hydrogenation and oligomerization steps by periodic density functional theory on Pd(111). Oligomerization was found to be competitive with hydrogenation, with the hydrogenation of the oligomers being among the fastest processes. The role of Pd domains to green oil formation is still to be clarified under realistic conditions, where the surface is covered by many different species. A step forward to this goal was taken by developing a machine-learning tool which automatically interpolates model Hamiltonians on graphical lattices based on DFT computations, accounting for lateral interactions and distorted adsorption modes on crowded surfaces

Styrene production by a (FlDAB)PdII(TFA)(η2-C2H4) complex was modeled using density functional theory (DFT). Benzene C-H activation by this complex was studied via five mechanisms: oxidative addition/reductive elimination, sigma-bond metathesis, concerted metalation deprotonation (CMD), CMD activation of ethylene, and benzene substitution of ethylene followed by CMD of the ligated benzene. Calculations provided evidence that conversion of benzene and ethylene to styrene was initiated by the fifth pathway, arylation via CMD of coordinated benzene, followed by ethylene insertion into the Ru-Ph bond, and then β-hydrogen elimination. Also, monomer (active species)/dimer equilibrium concentrations were analyzed. The results obtained from present study were compared with that of a recently reported RhI complex to help identify more suitable catalysts for the direct production of styrene from ethylene and benzene. Second, theoretical studies of heterobimetallic {Ag–Fe(CO)5}+ fragments were performed in conjunction with experiments. The computational models suggested that for this first example of a heterodinuclear, metal-only FeAg Lewis pair (MOLP) that Fe(CO)5 acts as a Lewis base and AgI as a Lewis acid. The ῡCO bands of the studied molecules showed a blue shift relative to those measured for free Fe(CO)5, which indicated a reduction in Fe→CO backbonding upon coordination to silver(I). Electrostatic interaction is predicted via DFT as the dominant mode of Fe—Ag bonding augmented by a modest amount of charge transfer between Ag+ and Fe(CO)5. Third, computational analyses of hypothetical transition metal-terminal boride [MB(PNPR)] complexes were reported. DFT, natural orbital analysis (NBO), and multiconfiguration self-consistent field (MCSCF) calculations were employed to investigate the structure and bonding of terminal boride complexes, in particular the extent of metal dπ - boron pπ bonding. Comparison of metal-boride, -borylene and –boryl bond lengths confirms the presence of metal-boron π bonds, albeit the modest shortening (~ 3%) of the metal-boron bond suggests that the π-bonding is weak. Their instabilities, as measured by free energies of H2 addition to make the corresponding boryl complexes, indicate terminal boride complexes to be thermodynamically weak. It is concluded that for the boride complexes studied, covering a range of 4d and 5d metals, that the metal-boride bond consisted of a reasonably covalent σ and two very polarized π metal-boron bonds. High polarization of the boron to metal π-bonds indicated that a terminal boride is an acceptor or Z type ligand. Finally, anti-Markovnikov addition of water to olefins has been a long-standing goal in catalysis. The [Rh(COD)(DPEphos)]+ complex was found as a general and regioselective group 9 catalyst for intermolecular hydroamination of alkenes. The reaction mechanism was adapted for intermolecular hydration of alkenes catalyzed by a [Rh(DPEphos)]+ catalyst and studied by DFT calculations. Olefin hydration pathways were analyzed for anti-Markovnikov and Markovnikov regioselectivity. On the basis of the DFT results, the operating mechanism can be summarized as follows: styrene activation through nucleophilic attack by OHδ− of water to alkene with simultaneous Hδ+ transfer to the Rh; this is then followed by formation of primary alcohol via reductive elimination. The competitive formation of phenylethane was studied via a β-elimination pathway followed by hydrogenation. The origin of the regioselectivity (Markovnikov vs anti-Markovnikov) was analyzed by means of studying the molecular orbitals, plus natural atomic charges, and shown to be primarily orbital-driven rather than charge-driven.

Chemical risk assessment for human health effects is performed in order to establish safe exposure levels of chemicals to which individuals are exposed. The process of risk assessment traditionally involves the generation of toxicological studies from which health based guidance values are derived for a specific chemical. For low level exposures to chemicals, where there are no or limited chemical specific toxicity data, the application of the Threshold of Toxicological Concern (TTC) approach may estimate whether the exposure levels can be considered safe. The TTC approach has recently gained increasing interest as new requirements, under different regulatory frameworks, emerge for the safety assessment of chemicals and to assess chemicals for which testing is not routinely required. The application of TTC relies heavily on computational (in silico) methods. In silico tools are computer implemented models that, based on commonalities in the toxicity of “similar” chemical structures, may predict hazard. In silico methods are rapidly evolving and gaining importance within the context of Integrated Approaches to Testing and Assessment (IATA) and their acceptance for regulatory purposes is expanding. The work presented in this thesis has focused on the use and applicability of a wide range of computational approaches to assist in the application of the TTC concept. In the TTC approach, the identification of genotoxic chemicals is a primary requirement. In silico approaches apply expert knowledge and/or statistical methods to either predict genotoxicity or to identify structural alerts associated with it. This thesis focused, in part, on a group of important environmental pollutants, nitrobenzenes, to assess the applicability of in silico tools to predict genotoxicity. For this purpose a dataset containing 252 nitrobenzenes including Ames test results was compiled. Based on these test results a case study for sodium nitro-guaiacolate, a pesticide active substance, was developed. The case study demonstrated that (Q)SAR and a category approach incorporating read-across, are applicable for the prediction of genotoxicity and supports their use within a weight of evidence approach. Another aspect of the TTC approach is the evaluation of repeat dose, non-cancer endpoints. For that purpose chemicals are separated into groups related to three levels of concern based on the Cramer classification. For each level, namely the Cramer Classes (I, II and III), a safe exposure level has been established. Therefore, as interest to apply TTC expands to new groups of chemicals, the reliability and conservativeness of the established thresholds relative to Cramer Classes for the new chemistries must be established. In this thesis the TTC approach was evaluated for 385 cosmetic ingredients, 77 biocides and 102 compounds classified as reproductive and developmental toxicants. To support the evaluation at different levels, chemical datasets containing toxicological data were utilised and computational tools were applied to compare datasets. The results indicated, that the historical “Munro” dataset is broadly representative for cosmetics and biocides. In addition, that the threshold levels for Cramer Class III are within the range of Munro’s threshold further supports the validity of the TTC approach and its conservativeness for the groups of chemicals analysed. Cramer Class I thresholds were found to be valid only for classified developmental and reproductive toxicants. The results also supported the validity of the classification of chemicals into Cramer class III. It is foreseen that the TTC approach will gain increasing acceptance in the risk assessment of different groups of chemicals. Therefore it is emphasised that the future work should focus on the identification of the limitations of the application of TTC, including the identification of groups of chemicals to which TTC cannot be applied, the expansion of the underlying toxicological datasets, and the development of tools to support the application of TTC so that is transparent and acceptable for regulatory purposes.

In recent years, as the progress of computational abilities has increased, computational chemistry has become an interesting tool for researchers for investigating mechanisms of environmental reactions when results of experimental explorations are not sufficiently clear. In this research, several environmental reactions have been investigated using ab initio and density functional theory (DFT) methods.This research investigated the effect of the reaction energy on the reaction pathway for C-Cl bond cleavage in carbon tetrachloride (CT). Ab initio and density functional theories were used to study adiabatic electron transfer to aqueous phase CT. The potential energies associated with fragmentation of the CT anion radical into a trichloromethyl radical and a chloride ion were explored as a function of the C-Cl bond distance during cleavage. The effect of aqueous solvation was simulated using a continuum conductor-like screening model. Solvation significantly lowered the energies of the reaction products, indicating that the dissociative electron transfer was enhanced by solvation. It was found that reductive dissociation electron transfer of CT undergoes a change from an inner-sphere to an outer-sphere mechanism as the reaction energy is increased. The results showed a liner relationship between the activation energy for the dissociation and the overall energy change, which is in good agreement with the results of the Marcus model.This research also investigated the thermodynamic favorability and resulting structures for chemisorption of trichloroethylene (TCE) and perchloroethylene (PCE) on iron surfaces using periodic DFT with the non-local Perdew-Burke-Enzerhof (PBE) functional. Chemisorption structures were obtained for four physically adsorbed initial configurations. An initial configuration with two carbons (C-bridge) physically adsorbed at bridge sites between adjacent iron atoms was shown to be the most stable configuration for TCE, while the mode with two carbons (C-hollow) physically adsorbed at hollow site was verified to be the most stable configuration for PCE. C-Fe bonds were formed via sigma or pi bonds in the complexes formed at C-bridge, top and hollow site. Upon binding with the iron surface, the interaction of the C=C bond still remained as sp2 hybridization. Moreover, the strong chemisorption induced dissociations of C-Cl bonds and formation of Cl-Fe bonds. For both TCE and PCE, modes with two Cl atoms (Cl-bridge) physically adsorbed at bridge sites were found to be the least favorable configuration, in which only two Cl atoms formed bonds with the Fe surface and no C-Fe bonds were formed. Negative net Mulliken charges on TCE and PCE indicated they are reduced upon adsorption to the iron surface.Finally, in this research, we evaluated the accuracies and costs of several DFT methods including Harris, PWC LDA, and BLYP GGA functionals for interaction of arsenite with ferric hydroxides by comparison to calculated and experimental properties of surface complexes. It was found that the approach of using low-level structures coupled with high level single-point energies was much less expensive than the approach of using high level functionals for both structures and energies and could obtain similar computed binding energies. Further work has been done to investigate the appropriate models for interaction of arsenite with ferric hydroxide between pH values of -4 through +4. The effect of solvation on single point energy was calculated using COSMO models. The bidentate corner-sharing complexes were more energetically favorable than monodentate corner-sharing complexes for the entire pH range. Lower binding energies at some pH values indicated monodentate binding may contribute to adsorption at low pH values and at high pH values. Adsorbed arsenite species were found to be fully protonated at low pH values and partly protonated at high pH values for the most favorable complex. Models for the interaction of arsenite with ferric hydroxide provided a relationship of adsorption and pH values that the adsorption of arsenite increased as pH value increased and there was a maximum point around pH 8.5-9.

This thesis improves computational efficiency in two domains of quantum chemistry. Firstly, we improve the efficiency of computing atomic orbital (AO) integrals. We efficiently compute effective core potential integrals, relying on novel recursion relations and rigorous screening strategies. Inspired by PRISM, we create an adaptive algorithm to compute two-electron Gaussian geminal integrals, efficiently handling the contracted nature of both the contracted Gaussian-type orbital and geminal. We implement an efficient non-robust density fitting (DF) algorithm for computing the three-electron energy term in the Unsöld-W12 functional using new integral and screening routines. Secondly, we develop low computational scaling and highly parallel algorithms for MP2 energies. These algorithms rely on spatial quadratures of the electronic co-ordinates. We begin with a Localised Molecular Orbital formalism. This algorithm computes the opposite-spin (OS) MP2 energy and scales formally O(N^6) but, with screening strategies, scales asymptotically O(N^2). Unfortunately, the screened quantities reach their asymptotic scaling too slowly. Instead, we adopt a more local AO formalism. This algorithm demonstrates an almost ideal parallel speedup with more than 800 cores and competitive timings against DF-MP2-OS. In our improved AO algorithm, we develop rigorous screening strategies for eliminating insignificant AOs, extend the method to computing the same-spin MP2 energy, remove the prior sparse memory access bottleneck and implement a hybrid parallelisation strategy. We demonstrate a 51% parallel efficiency on 4644 cores, competitive timings and accuracy compared to DF-MP2. Finally, we extend this methodology to compute the MP2-F12(3*A) correction. We present a novel scaled Coulomb-like term approximation and develop efficient quadrature methods and screening strategies. Our scaled approximation and algorithm achieves chemical accuracy across a range of test sets.

Quantum chemistry methodologies can be used to address a wide variety of chemical problems. Key to the success of quantum chemistry methodologies, however, is the selection of suitable methodologies for specific problems of interest, which often requires significant assessment. To gauge a number of methodologies, the utility of density functionals (BLYP, B97D, TPSS, M06L, PBE0, B3LYP, M06, and TPSSh) in predicting reaction energetics was examined for model studies of C-O bond activation of methoxyethane and methanol. These species provide excellent representative examples of lignin degradation via C-O bond cleavage. PBE0, which performed better than other considered DFT functionals, was used to investigate late 3d (Fe, Co, and Ni), 4d (Ru, Rh, and Pd), and 5d (Re, Os, and Ir) transition metal atom mediated Cβ -O bond activation of the β–O–4 linkage of lignin. Additionally, the impact of the choice of DFT functionals, basis sets, implicit solvation models, and layered quantum chemical methods (i.e., ONIOM, Our Own N-layered Integrated molecular Orbital and molecular Mechanics) was investigated for the prediction of pKa for a set of Ni-group metal hydrides (M = Ni, Pd, and Pt) in acetonitrile. These investigations have provided insight about the utility of a number of theoretical methods in the computation of thermodynamic properties of transition metal hydrides in solution. As single reference wavefunction methods commonly perform poorly in describing molecular systems that involve bond-breaking and forming or electronic near-degeneracies and are typically best described with computationally costly multireference wavefunction-based methods, it is imperative to a priori analyze the multireference character for molecular systems so that the proper methodology choice is applied. In this work, diagnostic criteria for assessing the multireference character of 4d transition metal-containing molecules was investigated. Four diagnostics were considered in this work, including the weight of the leading configuration of the CASSCF wavefunction, C02; T1, the Frobenius norm of the coupled cluster amplitude vector related to single excitations and D1, the matrix norm of the coupled cluster amplitude vector arising from coupled cluster calculations; and the percent total atomization energy, %TAE. This work demonstrated the need to have different diagnostic criteria for 4d molecules than for main group molecules.

Kohn-Sham Density Functional Theory (DFT) provides a method for electronic structure calculations applicable to a wide variety of systems. Traditional implementations of DFT are cubic-scaling which limits the size of the systems that can be studied. However recently developed linear-scaling methods, such as onetep, are available which allow much larger systems to be considered. Regardless of scaling DFT has limitations as the exact exchange-correlation functional (a key term in the Kohn-Sham equations) is not known and so approximations have to be made. These approximate functionals generally describe dispersion interactions poorly. In this thesis empirical corrections for dispersion have been developed with parameters optimised for a large set of dispersion bound complexes for the onetep code. This provides a much improved description of dispersion forces which are especially important for biological systems. There is a hierarchy of exchange-correlation functionals available the most accurate of which include a portion of Hartree-Fock exchange. Methods for calculating Hartree- Fock exchange energy in onetep have been developed and are described in this thesis. A quadratic-scaling method using Fourier transforms has been implemented as a benchmark for other implementations. Hartree-Fock exchange may be calculated in a linear-scaling manner by using a numerical pointwise or auxiliary basis set method. Spherical waves have been used as an auxiliary basis set. Linear-scaling has been demonstrated for a polythene chain for these methods. Several hybrid functionals have also been implemented in onetep. These have been validated by comparison with a Gaussian basis set approach in calculations on the reaction paths of an organometallic system

Computational chemists are concerned about two aspects when choosing between the myriad of theoretical methodologies: the accuracy (the "truth") and the computational cost (the tractability). Among the least expensive methods are the Hartree-Fock (HF), density functional theory (DFT), and second-order Moller-Plesset perturbation theory (MP2) methods. While each of these methods yield excellent results in many cases, the inadequate inclusion of certain types of electron correlation (either high-orders or nondynamical) can produce erroneous results. The compromise for the computation of noncovalent interactions often comes from empirically scaling DFT and/or MP2 methods to fit benchmark data sets. The DFT method with an empirically fit dispersion term (DFT-D) often yields semi-quantitative results. The spin-component scaled MP2 (SCS-MP2) method parameterizes the same- and opposite-spin correlation energies and often yields less than 20% error for prototype noncovalent systems compared to chemically accurate CCSD(T) results. There is no simple fix for cases with a large degree of nondynamical correlation (such as transition metal-salen complexes). While testing standard and new DFT functionals on the spin-state energy gaps of transition metal-salen complexes, no DFT method produced reliable results compared to very robust CASPT3 results. Therefore each metal-salen complex must be evaluated on a case-by-case basis to determine which methods are the most reliable. Utilizing a combination of DFT-D and SCS-MP2 methods, the reaction mechanism for the addition of cyanide to unsaturated imides catalyzed by the Al(Cl)-salen complex was performed. Various experimental observations are rationalized through this mechanism.

Includes bibliographical references.
Ab initio, density functional theory, and semi-empirical methods serve as major computational tools for quantum mechanical calculations of medium to large molecular systems. Semi-empirical methods are most effectively used in a hybrid quantum mechanics/molecular mechanics (QM/MM) dynamics framework. However, semi-empirical methods have been designed to provide accurate results for organic molecules, but often fail to treat hypervalent species accurately due to their use of an sp basis. Recently, significant breakthroughs have been made with the incorporation of d-orbitals into the semi-empirical framework, thereby allowing for accurate modeling of both hypervalent and transition metal systems. Here I consider two methods that adopt this new methodology, namely AM1/d-PhoT and AM1*. Our major focus is the simulation of chemical biological and more specifically chemical glycobiological problems of biochemical interest. When I tested the ability of both AM1/d-PhoT and AM1* to reproduce key metrics in chemical glycobiology (i.e., sugar ring pucker, phosphate participation in transferase reactions) these methods, in combination with the published parameters, performed very poorly. Using the AM1/d-PhoT and AM1* Hamiltonians I set out to re-parameterize these methods aiming to produce holistic biochemical QM/MM toolsets able to simulate fundamental problems of binding and enzyme reactivity in chemical glycobiology. We called these methods AM1/d-CB1 and AM1*-CB1. In the development of these parameter sets I focused specifically on proton transfer, carbohydrate ring puckering, bond polarization, amino acid interactions, and phosphate interactions (facets important to chemical glycobiology). Both AM1/d-CB1 and AM1*-CB1 make use of a variable property optimization parameter approach for the glycan molecular class and its chemical environment. The accuracy of these methods is evaluated for carbohydrates, amino acids and phosphates present in catalytic domains of glycoenzymes, and the are shown to be more accurate for key performance indices (puckering, etc.) and on average across all simulation derived properties (QM/MM polarization, protein performance, etc.) than all other NDDO semiempirical methods currently being used. A major objective of the newly developed AM1/d-CB1 and AM1*-CB1 is to provide a platform to accurately model reactions central to chemical glycobiology using hybrid QM/MM molecular dynamics (MD) simulations. AM1/d-CB1 is applied to a well-known reaction involving purine nucleoside phosphorylase (PNP) and results lead me to conclude that the method shows promise for modelling glycobiological QM/MM systems.

This thesis focuses on current methods for nanoparticle characterisation and analysis of cellular interactions. The specific interaction between HeLa cells and 20 nm carboxylate-modified polystyrene nanoparticles is examined in detail, and the effects of serum proteins in corona formation is analysed. Fluorescence microscopy image acquisition is studied, with particular attention given to colocalisation analysis. An automated program is presented, making use of a novel de-noising algorithm which makes analysis of low signal-to-noise images possible without additional input. This is validated using computer generated images, and data acquired and analysed by hand. This program was used to analyse confocal microscopy images to quantify nanoparticle colocalisation with intracellular protein markers and membrane stains. A protocol is developed to enable use of total internal reflection fluorescence (TIRF) microscopy for the study of nanoparticle internalisation. Finally, innovative TIRF methods that permit identification of areas of local plasma membrane curvature and super-resolution analysis of fluorophore motion in Z are examined, and significant steps are made to combine these into a single imaging system. Thus, this project will develop computational analysis methods, novel biological assays, and physical enhancements to existing hardware with the aim of accelerating the characterisation of nanoparticle-cell interactions.

The search for new antiviral drugs for the treatment of clinical and emerging viruses is a delicate task. Drugs available today are developed to target a specific virus or viral strain, and only few prophylactics show a broad-spectrum activity that can be used to treat drug-resistant infections or in case of emergencies. Among the strategies that can be pursued to search for new antiviral drugs, there is the inhibition of a host protein involved in the viral replication cycle. The inhibition of DDX3X, a human ATP-dependent RNA helicase, allowed to discover the first broad-spectrum antiviral compound able to inhibit the replication of HIV resistant strains, HCV and of emerging viruses like West Nile Virus, Japanese Encephalitis Virus, Dengue Virus. In this project, several computational strategies have been applied to improve the biodistribution and pharmacokinetic properties of this compound and a fluorescent inhibitor was designed to understand the mode of action of DDX3X inhibitors in DENV infected cells. The selective inhibition of DDX3X can be pursued targeting a small pocket, peculiar to the human protein, called unique motif (UM). The study of the interactions established by the first active compound within UM, allowed to identify the amino acids responsible of its activity. Considering these findings, a small library of derivatives able to establish the fundamental interactions with the UM was designed. Moreover, a pharmacophore-based virtual screening procedure allowed to discover new compounds that will be biologically evaluated as new UM inhibitors. PROTAC is instead a potent strategy to target protein degradation. A PROTAC molecule, that is constituted by two active moieties hold together by a linker, allow the selective ubiquitination and degradation of the protein of interest by the proteasome. In this contest, the application of computational procedures on known SOCS2 binders, allowed to establish a SAR that will be used to design novel derivatives that can be used both as inhibitors of the protein and as binders of the E3 ligase. A pharmacophore-based virtual screening performed on the Elongin C allowed to discover new compounds that will be biologically evaluated to establish if they can be used as E3 ligase binders.

The work presented in my dissertation focuses on the conformational studies of bio-molecules including proteins and DNA using computational approaches. Conformational changes are important in numerous molecular bioprocesses such as recognition, transcription, replication and repair, etc. Proteins recognize specific DNA sequences and upon binding undergo partial or complete folding or partial unfolding in order to find the optimal conformational fit between molecules involved in the complex. In addition to sequence specific recognition, proteins are able to distinguish between subtle differences in local geometry and flexibility associated with DNA that may further affect their binding affinities. Experimental techniques provide high-resolution details to the static structures but the structural dynamics are often not accessible with these methods; but can be probed using computational tools. Various well-established molecular dynamics methods are used in this work to study differences in geometry and mechanical properties of specific systems under unmodified and modified conditions. Briefly, the studies of several protein and DNA systems investigated the importance of local interactions and modifications for the stability, geometry and mechanical properties using standard and enhanced molecular dynamics simulations. In addition to the conformational studies, the development of a new method for enhanced sampling of DNA step parameters and its application to DNA systems is discussed. Chapter 1 reviews the importance of the conformational changes in bioprocesses and the theory behind the computational methods used in this work. In the project presented in chapter 2 unbiased molecular dynamics and replica exchange molecular dynamics are employed to identify the specific local contacts within the inhibitory module of ETS-1. ETS-1 is a human transcription factor important for normal but also malignant cell growth. An increased concentration of this protein is related to a negative prognosis in many cancers. A part of the inhibitory module, inhibitory helix 1 (HI-1) is located on the site of the protein opposite to the DNA binding site and although loosely packed, stays folded in the apo state and unfolds upon ETS-1 binding to DNA. Our study investigated the character and importance of contacts between HI-1 and neighboring helices of the inhibitory module: HI-2 and H4. We also identified a mutant of HI-1, which possessed the higher helical propensity than the original construct. This study supported the experimental findings and enhanced the field by the identification of new potential target for experimental tests of the system, which plausibly inhibits binding to DNA. In the studies discussed in chapters 3-5 the conformational dynamics of DNA under normal conditions and upon specific epigenetic modifications are presented. Since DNA conformation can be accurately described by six base pair step parameters: twist, tilt, roll, shift, slide and rise, these were extensively analyzed and the results elucidated insights into the properties of the systems. In order to enhance unbiased simulations and allow for easier crossing of the energy barriers, we developed and implemented a novel method to control DNA base pair step parameters. With this approach we obtained the free energy estimates of e.g. DNA rearrangements in a more efficient manner. This advanced computational method, supported by standard and additional enhanced techniques, was then applied in the studies of DNA methylation on cytosine or adenine bases and oxidative damage of cytosine.

Kahn-Sham density functional theory (OFT) calculations yield reliable accuracy in a wide variety of molecules and materials. The advent of linear-scaling OFT methods, based on locality of the electronic matter, has enabled calculations on systems with tens of thousands of atoms. Localisation constraints are imposed by expanding the Kahn-Sham states in terms of a set of atom-centred, spherically-localised functions. Chemical accuracy is then achieved via a self-consistent optimisation using a high-resolution basis set. This formalism reduces the size of, and brings predictable sparsity patterns to, the matrices expressed in this representation, such as the Hamiltonian matrix. In this work, we used the ONETEP program for DFT calculations, which is based on the abovementioncd principles. The vision behind our research is to advance the method by developing new and robust algorithms to enable novel applications based on localised orbitals.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 2006.
Vita.
Includes bibliographical references (p. 207-230).
This thesis presents the development and application of several computational techniques to aid in the design and analysis of small molecules and peptides that bind to protein targets. First, an inverse small-molecule design algorithm is presented that can explore the space of ligands compatible with binding to a target protein using fast combinatorial search methods. The inverse design method was applied to design inhibitors of HIV-1 protease that should be less likely to induce resistance mutations because they fit inside a consensus substrate envelope. Fifteen designed inhibitors were chemically synthesized, and four of the tightest binding compounds to the wild-type protease exhibited broad specificity against a panel of drug resistance mutant proteases in experimental tests. Inverse protein design methods and charge optimization were also applied to improve the binding affinity of a substrate peptide for an inactivated mutant of HIV-1 protease, in an effort to learn more about the thermodynamics and mechanisms of peptide binding. A single mutant peptide calculated to have improved binding electrostatics exhibited greater than 10-fold improved affinity experimentally.
(cont.) The second half of this thesis presents an accurate method for evaluating the electrostatic component of solvation and binding in molecular systems, based on curved boundary-element method solutions of the linearized Poisson-Boltzmann equation. Using the presented FFTSVD matrix compression algorithm and other techniques, a full linearized Poisson-Boltzmann equation solver is described that is capable of solving multi-region problems in molecular continuum electrostatics to high precision.
Michael Darren Altman.
Ph.D.

The first study project is based on modeling Earth abundant 3d transition-metal methoxide complexes with potentially redox-noninnocent ligands for methane C–H bond activation to form methanol (LnM-OMe + CH4 → LnM–Me + CH3OH). Three types of complex consisting of tridentate pincer terpyridine-like ligands, and different first-row transition metals (M = Ti, V, Cr, Mn, Fe, Co, Ni, and Cu) were modeled to elucidate the reaction mechanism as well as the effect of the metal identity on the thermodynamics and kinetics of a methane activation reaction. The calculations showed that the d electron count of the metal is a more significant factor than the metal's formal charge in controlling the thermodynamics and kinetics of C–H activation. These researches suggest that late 3d-metal methoxide complexes that favor σ-bond metathesis pathways for methane activation will yield lower barriers for C–H activation, and are more profitable catalyst for future studies. Second, subsequently, on the basis of the first project, density functional theory is used to analyze methane C−H activation by neutral and cationic nickel-methoxide complexes. This study identifies strategies to further lower the barriers for methane C−H activation through evaluation of supporting ligand modifications, solvent polarity, overall charge of complex, metal identity and counterion effects. Overall, neutral low coordinate complexes (e.g. bipyridine) are calculated to have lower activation barriers than the cationic complexes. For both neutral and cationic complexes, the methane C−H activation proceed via a σ-bond metathesis rather than an oxidative addition/reductive elimination pathway. Neutralizing the cationic catalyst models by a counterion, BF4-, has a considerable impact on reducing the methane activation barrier free energy. Third, theoretical studies were performed to explore the effects of appended s-block metal ion crown ethers upon the redox properties of nitridomanganese(V) salen complexes, [(salen)MnV(N)(Mn+-crown ether)]n+, where, M = Na+, K+, Ba2+, Sr2+ for 1Na, 1K, 1Ba, 1Sr complexes respectively; A = complex without Mn+-crown ether and B = without Mn+). The results of the calculations reveal that ΔGrxn(e ̶ ) and thus reduction potentials are quite sensitive to the point charge (q) of the s-block metal ions. Methane activation by A, 1K and 1Ba complexes proceeds via a hydrogen atom abstraction (HAA) pathway with reasonable barriers for all complexes with ~ 4 kcal/mol difference in energy, more favorable free energy barrier for the complexes with higher point charge of metal ion. Changes in predicted properties as a function of continuum solvent dielectric constant suggest that the primary effect of the appended s-block ion is via "through space" interactions. Finally, a comprehensive DFT study of the electrocatalytic oxidation of ammonia to dinitrogen by a ruthenium polypyridyl complex, [(tpy)(bpy)RuII(NH3)]2+ (complex a), and its NMe2-substituted derivative (b), is presented. The thermodynamics and kinetics of electron (ET) and proton transfer (PT) steps and transition states are calculated. NMe2 substitution on bpy reduces the ET steps on average 8 kcal/mol for complex b as compared to a. The calculations indicate that N–N formation occurs by ammonia nucleophilic attack/H-transfer via a nitrene intermediate, rather than a nitride intermediate. Comparison of the free energy profiles of Ru-b with its first-row Fe congener reveals that the thermodynamics are less favorable for the Fe-b model, especially for ET steps. The N-H bond dissociation free energies (BDFEs) for NH3 to form N2 show the following trend: Ru-b