Noncovalent interactions are vital for functioning of biological systems. For instance, they facilitate DNA base pairing or protein folding. Recently, in addition to classical noncovalent interactions such as hydrogen bond, nonclassical noncovalent interactions have been discovered. An example of these interactions is halogen bond belonging to the class of σ-hole interactions, the knowledge of which is already being useful for medical compound design. The aim of this work is to find out if the chalcogen bond, also a σ-hole interaction, plays a role in the binding of existing viral inhibitors, too. Following that, we are also interested whether or to what extent can these existing chalcogen bonds be optimized for a greater affinity of the inhibitor binding. Several protein-ligand crystal structures exhibiting geometrical properties favoring a chalcogen bond have been found in the PDB database. We examined the interaction energies and the interaction energy geometrical dependencies of model systems derived from these crystal structures by means of quantum chemical calculations. Further we have optimized their strength by a series of substitutions. We thus propose that chalcogen bond can become a player in rational design of inhibitors of viral enzymes and their protein target. Keywords: Noncovalent...

<div> <div> <div> <p>The Effective Fragment Potential (EFP) is a quantum-mechanical based model potential for accurate calculations of non-covalent interactions between molecules. It can be coupled with ab initio methods in so-called QM/EFP models to explore the electronic properties of extended molecular systems by providing rigorous description of surrounding environments. The current EFP formulation is, however, not well suited for large-scale simulations due to its inherent limitation of representing effective fragments as rigid structures. The process of utilizing EFP method for the molecular systems with flexible degrees of freedom entails multiple sets of parameter calculations requiring intensive computational resources. This work presents development of the EFP method for describing flexible molecular systems, so-called Flexible EFP. To validate the applicability of the Flexible EFP method, extensive benchmark studies on the amino acid interactions, binding energies, and electronic properties of flavin chromophore of the cryptochrome protein have been demonstrated. In addition to methodological developments, excitonic properties of the Fenna-Matthews-Olson (FMO) photosynthetic pigment-protein complex are explored. In biological systems where intermolecular interactions span a broad range from non-polar to polar and ionic forces, EFP is superior to the classical force fields. In the present study, we demonstrate excellent performance of the QM/EFP model for predicting excitonic interactions and spectral characteristics of the FMO wildtype complex. We characterize the key factors for accurate modeling of electronic properties of bacteriochlrophyll a (BChl a) photosynthetic pigments and suggest a robust computational protocol that can be applied for modeling other photosynthetic systems. Developed computational procedures were also successfully utilized to elucidate photostability and triplet dynamics in the FMO complex and spectroscopic effects of single-point mutagenesis in FMO. A combination of polarizable EFP molecular dynamics and QM/EFP vibrational frequency calculations were also applied to understanding and interpreting structures and Raman spectroscopy of tert-butyl alcohol solutions. </p> </div> </div> </div>

This Thesis deals with simulations of chiroptical spectra using a combination of molecular dynamics and quantum chemistry. Molecular dynamics was used to explore conformational behaviour of studied systems (proteins), quantum chemistry for calculation of spectral prop- erties. The Quantum chemical methods are limited to relatively small systems. We overcome this problem mostly by a fragmentation of studied systems, when smaller, computationally feasible, fragments are created and used for the quantum chemical calculations. Calculated properties were then transferred to the big molecule. Vibrational Optical Activity (VOA) spectra of poly-L-glutamic acid fibrils (PLGA), insulin prefibrillar form and native globular proteins were studied. The simulated spectra provided satisfactory agreement with the experiment and were used for its interpretation. Experimental Vibrational Circular Dichroism (VCD) spectra of poly-L-glutamic acid fibrils were only qualitatively reproduced by the simulation. We could reproduce the major amide I band and a smaller negative band associated with the side chain carboxyl group. Our simulation procedure was then extended to a set of globular proteins and their Raman Optical Activity (ROA) spectra. Here we achieved an exceptional precision. For example, we were able to reproduce...

<p>Drug-drug interactions (DDIs) occur when multiple drugs are used concurrently. Caused by one drug inhibiting or inducing the metabolism of a second drug, DDIs often alter plasma concentrations and could seriously impact efficacy and safety of co-administered medications. Cytochrome P450 (CYP), a superfamily of enzymes, plays an important role in metabolizing a majority of FDA approved drugs currently on the market. 70% of predicable DDIs are associated with CYP enzymes inhibition. In-silico methods are increasingly adopted as a cost-effective complement to guide and prioritize efforts in drug discovery. Recent emerging applications of artificial intelligence algorithms have demonstrated promising results capable of prioritizing the selection of large chemical libraries, thereby outlining the future of in-silico methods assisting in drug discovery. Nevertheless, current methods rely on molecular descriptors that almost exclusively focus on chemical properties and atomic structures that fail to capture critical conformation and biological interaction related properties. There is also a lack of trainable molecular descriptors with feature specificity that reflect detailed protein-ligand binding energy and enable biological activity prediction. The overall objective of this dissertation is to understand molecular biological binding activity through electronic structure-based local descriptors derived from quantum based conceptual density functional theory (CDFT). This method will be used to assess the correlation of intermolecular interaction energy with ligand-protein binding with 2D feature maps reduced from the 4D molecular surfaces of the binding site and ligand (3D molecular surface with 1D electronic property). Additionally, it will be used to explore the possibility of predicting CYP related DDIs using descriptors generated using first principles including protein-ligand binding with specificity and strength and deep learning algorithms. Using quantum chemistry to interpret topological molecular information residing on 3D molecular surface permits the extraction of interacting features directly from the ligand structure. To achieve that, a set of curatable data containing consistent measurements was accessed through publicly accessible libraries. A series of novel Manifold Embedding of Molecular Surface (MEMS) descriptors were generated containing local electronic properties residing on the 3D molecule structure surface of each ligand using manifold learning. Major information were captured featuring electronic characteristics on the molecular 3D surface. Shape context was employed to derive transnational invariance feature vectors from MEMS with high granularity, thus preserving molecular information with specificity. DeepSet was utilized to perform permutation equivariance model training and validation. Powerful model learning is observed with an F-measure for all targets above 75% with the highest of 87% from external testing. Despite their promising prediction performance, molecular conformation changes and analytical featurization methods need to be implemented to expand model applicability and improve model reliability.</p>

This thesis focuses on the theoretical investigation of the electronic structure and magnetic interactions present in 3d and 4d/5d transition metal compounds. We use many-body quantum chemistry methods that provide a theoretical frame for the rigorous construction and systematic improvement of correlated N-electron wave-functions. In Chapter 3 we compute d-d transitions fully ab initio and assign excitation peaks of experimental spectra measured in spin-Peierls TiPO4 compound. In this material we find that the d1 ground state is composed of an admixture of dz2 and dxz orbital character, which is related to the large positive ionic charge at P sites in the xz plane (defining the shortest Ti-P links) and of Ti nearest-neighbors along the z axis. In addition, the magnitude of the nearest-neighbors Heisenberg magnetic coupling calculated by quantum chemistry methods compares well with resonant inelastic X-ray scattering (RIXS) experimental data. We further demonstrate that the intersite exchange is very sensitive to the Ti-Ti interatomic distance, which is relevant in the context of spin-Peierls physics in TiPO4. In Chapter 4 we have studied the magnetic anisotropy of Fe ions within the Li3N lattice. The calculated magnetic anisotropy splitting of 26.3 meV for Fe2+ d6 ions in D6h symmetry compares favorably to values measured or computed by similar theoretical methods for Fe1+ d7 species with linear coordination. This substantial spin-reversal energy barrier of the Fe2+ ion is associated with a a^1_{1g}e^3_{2g}e^2_{1g} ground-state electron configuration. Our study therefore puts into the spotlight the linearly coordinated Fe2+ d6 ion as candidate for viable single molecule magnet behavior. In Chapter 5 we address the effect of electron-lattice interactions on the magnetic properties of 4d and 5d TM ions with a formally degenerate t^1_{2g} electron configuration in the double-perovskite materials Ba2YMoO6, Ba2LiOsO6 and Ba2NaOsO6. Our analysis indicates that the sizable magnetic moments and g-factors found experimentally are due to both strong TM d -- ligand p hybridization and dynamic Jahn-Teller effects. Our results also point out that cation charge imbalance in the double-perovskite structure allows a fine tuning of the gap between the t2g and eg levels. The mechanism has not been explored so far experimentally but seems to hold much potential in the context of orbital engineering in transition metal compounds. In Chapter 6 we report a study of magnetic exchange interactions in the S=3/2 orthorhombic perovskite NaOsO3. We mapped the ab initio quantum chemistry results onto model Hamiltonians including both isotropic Heisenberg interactions and anisotropic Dzyaloshinskii-Moriya exchange. We found antiferromagnetic nearest-neighbors Heisenberg exchange interactions of J_ac = 24.4 meV and J_b = 20.9 meV, twice larger than the J extracted from the magnon excitation spectra. The quantum chemistry results motivate further experimental measurements or theoretical analysis to clarify the magnitude of the nearest-neighbors Heisenberg couplings. In Chapter 7 we provide valuable insights on the effective magnetic interactions in 5d and 4d oxides with face-sharing oxygen octahedra, BaIrO3 and BaRhO3, for different bond-angles and bond-lengths. The large antiferromagnetic Heisenberg interactions computed here emphasize the subtle interplay among strong spin-orbit interactions, direct intersite orbital overlap and orbital bonding, and couplings to the lattice degrees of freedom in face-sharing compounds. In Chapter 8 we apply a computational scheme for computing intensities as measured in X-ray absorption and RIXS experiments. We take into account the readjustment of the charge distribution in the vicinity of an excited electron for the modeling of RIXS. For L3-edge spectra of Cu2+ 3d9 ions in KCuF3, we discuss the way to consider orbital ordering effects (alternately occupied d_x2-z2 and d_y2-z2 orbitals). For L3-edge spectra of Ni2+ 3d8 ions in La2NiO4, the computed spectra reproduce trends found experimentally for the incoming-photon incident-angle and polarization dependence.

The prime objectives of contrast agents in Magnetic Resonance Imaging(MRI) is to accelerate the relaxation rate of the solvent water protons in the surrounding tissue. Paramagnetic relaxation originates from dipole-dipole interactions between the nuclear spins and the fluctuating magnetic field induced by unpaired electrons. Currently Gadolinium(III) chelates are the most widely used contrast agents in MRI, and therefore it is incumbent to extend the fundamental theoretical understanding of parameters that drive the relaxation mechanism in these complexes. Traditionally the Solomon-Bloembergen-Morgan equations have been utilized to describe relaxation times in terms, primarily of the Zeeman interaction, which is the splitting of degenerate energy levels due to an applied magnetic field. However, in compounds such as Gadolinium(III) complexes with total electron spins higher than 1 (in this case S=7/2) other interactions such as the Zero-Field Splitting(ZFS) play a significant role. ZFS is the splitting of degenerate energy levels in the absence of an external magnetic field. For this purpose, the current research delves into an understanding of the relaxation process, focusing on ZFS in various complexes of interest, using quantum chemical methods as well as molecular dynamic simulations.

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Metal Organic Materials (MOM) are composed of transition metal ions as connectors and organic ligands as linkers. MOMs have been found to have high porosity, catalytic, and optical properties. Here we study the gas adsorption, color change, and non-linear optical properties of MOMs. These properties can be predicted using theoretical methods, and the results may provide experimentalists with guidance for rational design and engineering of novel MOMs. The theory levels used include semi-empirical quantum mechanical calculations with the PM7 Hamiltonian and, Density Functional Theory (DFT) to predict the geometry and electronic structure of the ground state, and Time Dependent DFT (TD-DFT) to predict the excited states and the optical properties. The molecular absorption capacity of aldoxime coordinated Zn(II) based MOMs (previously measured experimentally) is predicted by using PM7 Theory level. The 3D structures were optimized with and without host molecules inside the pores. The absorption capacity of these crystals was predicted to be 8H2 or 3N2 per unit cell. When going beyond this limit, the structural integrity of the bulk material becomes fractured and microcrystals are observed both experimentally and theoretically. The linear absorption properties of Co(II) based complexes are known to change color when the coordination number is altered. In order to understand the mechanism of this color change TD-DFT methods are employed. The chromic behavior of the Co(II) based complexes studied was confirmed to be due to a chain in coordination number that resulted in lower metal to ligand distances. These distances destabilize the occupied metal d orbitals, and as a consequence of this, the metal to ligand transition energy is lowered enough to allow the crystals to absorb light at longer wavelengths. Covalent organic frameworks (COFs) present an extension of MOM principles to the main group elements. The synthesis of ordered COFs is possible by using predesigned structures andcarefully selecting the building blocks and their conditions for assembly. The crystals formed by these systems often possess non-linear optical (NLO) properties. Second Harmonic Generation (SHG) is one of the most used optical processes. Currently, there is a great demand for materials with NLO optical properties to be used for optoelectronic, imaging, sensing, among other applications. DFT calculations can predict the second order hyperpolarizability ?2 and tensor components necessary to estimate NLO. These calculations for the ?2 were done with the use of the Berry's finite field approach. An efficient material with high ?2 was designed and the resulting material was predicted to be nearly fivefold higher than the urea standard. Two-photon absorption (2PA) is another NLO effect. Unlike SHG, it is not limited to acentric material and can be used development of in vivo bio-imaging agents for the brain. Pt(II) complexes with porphyrin derivatives are theoretically studied for that purpose. The mechanism of 2PA enhancement was identified. For the most efficient porphyrin, the large 2PA cross-section was found to be caused by a HOMO-LUMO+2 transition. This transition is strongly coupled to 1PA allowed Q-band HOMO-LUMO states by large transition dipoles. Alkyl carboxyl substituents delocalize the LUMO+2 orbital due to their strong ?-acceptor effect, enhancing transition dipoles and lowering the 2PA transition to the desirable wavelengths range. The mechanism 2PA cross-section enhancement of aminoxime and aldoxime ligands upon metal addition of is studied with TD-DFT methods. This mechanism of enhancement is found to be caused by the polarization of the ligand orbitals by the metal cation. After polarization an increase in ligand to ligand transition dipole moment. This enhancement of dipole moment is related to the increase in 2PA cross-sections.

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