The development of hybrid quantum classical computational methods for carbohydrate and hypervalent phosphoric systems

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

Crystal structure solution of hydrogen bonded systems : a validation and an investigation using historical methodologies followed by a review of crystal structure prediction methodologies to date

There are many chemicals that crystallize into more than one form. This phenomenon is called polymorphism. In each form or polymorph, inter and intra-molecular binding differ to varying degrees. As a result of this structural variation, the physical properties of the solid phases may also differ. Even the smallest of changes at the molecular level can result in a significant change in the final adopted crystal structure. Polymorphism in crystal structures allows studies of structure-property relationships since it is only the packing motifs that differ between polymorphs. In this thesis, a ‘computationally assisted’ approach to crystal structure solution was taken. X-ray powder diffraction was used to generate unit cell dimensions and space groups while historical in-house molecular modelling methods were used to generate possible trial structures that would be the starting point for refinement. Finally, a review of the latest methodologies for crystal structure prediction and consideration of polymorphism within the pharmaceutical industry completes this work

Clay Minerals For Nanocomposites and Biotechnology: Surface Modification, Dynamics and Responses to Stimuli

Clay minerals find a wide range of application in composites, paints, drilling liquids, cosmetics, and medicine. This article reviews chemical and physical properties of natural and organically modified clay minerals to understand the nanometre-scale structure, surface characteristics, and application in functional materials. The relation between fundamental properties and materials design is emphasized and illustrated by examples. The discussion comprises the following: an overview; surface structure and cation density; solubility and solubility reversal by surface modification; the degree of covalent and ionic bonding represented by atomic charges; the distribution of metal substitution sites; measurements and simulations of interfacial properties at the nanometre scale; self-assembly, packing density, and orientation of alkylammonium surfactants on the clay mineral surface; the density and chain conformation of surfactants in organic interlayer spaces; the free energy of exfoliation in polymer matrices and modifications by tuning the cleavage energy; thermal transitions, diffusion, and optical responses of surfactants on the mineral surface; elastic moduli and bending stability of clay layers; and the adsorption mechanism of peptides onto clay mineral surfaces in aqueous solution. Potential applications in biotechnology and other future uses are described

Experimental and theoretical investigation of chiral separation by crystallisation

Chiral molecules often show different pharmacological and toxicological properties, making their separation crucial for pharmaceutical companies. The resolution of racemic mixtures is often achieved via crystallisation methods. The lack of experimental data has been a major constraint in validating proposed computational methods for aiding the design of crystallisation processes for chiral resolution. This thesis provides both structural and thermodynamic data, and uses it to assess the limitations of current computer modelling methods. Progress in computational methods might eventually result in the design of resolving agents and hence reduce production costs of drugs and fine chemicals. Previous studies of naproxen have concentrated on the marketed enantiopure form of this anti-inflammatory drug. A crystallisation screen was conducted to identify all possible crystal phases of racemic and enantiopure naproxen. No polymorphs were detected and the crystal structure of the racemic compound was solved from powder X-ray diffraction data. The nature of the racemic species was confirmed with thermal methods, and differential scanning calorimetric and solubility measurements were used to estimate the enthalpy difference between the crystals at 156 °C and in the range of 10 to 40 °C. These data were used to test the different approximations involved in determining the energy differences between the racemic and enantiopure crystals. An extensive crystallisation screen was also performed for (1R,2S)-ephedrine 2-phenylpropionate salts. The crystal structure of the least soluble salt and three polymorphs of the most soluble salt were determined by low temperature single crystal X-ray diffraction or powder X-ray diffraction. Solubility measurements and differential scanning calorimetry were used to determine the relative stability of the salt pairs and polymorphs. These results showed the inadequacies of lattice energy calculations of the diastereomeric salt pair and their polymorphs. Experimental work on related diastereomeric salt pairs emphasised the difficulty in fully structurally and thermodynamically characterising these systems

Raman Optical Activity of Biological Molecules

This thesis describes work that has helped to establish Raman optical activity (ROA) as a powerful new chiroptical spectroscopic technique for the study of molecular chirality and conformation of biological molecules in aqueous solution. The first chapter describes the background and recent developments of vibrational optical activity including both the infrared vibrational circular dichroism (VCD) and Raman optical activity approaches. In chapter two, the basic theory of vibrational Raman optical activity is briefly reviewed. It comprises the fundamental theory to describe the vibrational Raman optical activity phenomenon, the rationale of the choice of the backscattering geometry for ROA instrument set-up and the basis of the more advanced ab initio ROA theory for calculation of ROA spectra. A new ROA instrument based on the backscattering geometry and back thinned CCD (Charge-Coupled Device) light detector is detailed in chapter 3. The new ROA instrument represents the contemporary development of ROA instrumentation and the up-to-date sophisticated optical and electronic devices used in the ROA spectrometer. A few basic considerations in ROA instrumentation and the performance of the instrument are discussed. The breakthrough of the instrument sensitivity has enabled ROA spectroscopy to be applied to important biological molecules in aqueous solution for the first time. The following three chapters are devoted to the ROA study of a number of biological molecules including small peptides, polypeptides, proteins and carbohydrates. These ROA data constitute the basis of ROA study for more complicated biological molecules in the future. Chapter 4 deals with ROA studies on model peptides and polypeptides. They comprise L-alanine oligomers: di-L-alanine and tri-, tetra-L-alanine, and a tripeptide L-Pro-L-Leu-Gly-amide for model ?-turn structure plus two polyamino acids poly-L-glutamic acid and poly-L-lysine. Di-L-alanine and its enantiomer are investigated in detail in various aqueous solutions and the results suggest that di-L-alanine could be used as a good model peptide for vibrational optical activity spectra analysis of peptides and polypeptides. ROA is a very local effect that is related to the intrinsic chirality. The most important ROA bands of peptides are in the extended amide 111 region. In chapter 5, the first ROA spectra of eight globular proteins in aqueous solution are reported and a preliminary empirical analysis presented. These protein ROA data clearly demonstrate that ROA is now able to investigate protein structure in the solution phase. The dominant ROA features of proteins arise mainly from the polypeptide backbone. Proteins containing different secondary structure compositions show characteristic ROA patterns. The most prominent ROA features are concentrated in the extended amide III region and are particularly sensitive to reverse turn structure. The ROA band intensity and A value offer a sensitive probe of the rigidity or flexibility of the globular proteins. In the last chapter 6, the ROA spectra of a range of carbohydrates including fifteen monosaccharides, a disaccharide and a cyclodextrin are investigated. The overwhelming ROA spectral information convincingly demonstrates that carbohydrates are particularly favourable samples for vibrational ROA study. ROA measurements on carbohydrates can yield ample stereochemical information with respect to the glycosidic linkage, anomeric configuration, sugar ring chair conformation and intramolecular interaction between adjacent chiral centres. Of all the information available from carbohydrate ROA spectra, the characteristic ROA couplet of the glycosidic linkage is probably the most valuable, which may be used to probe the conformation of disaccharides, oligosaccharides and polysaccharides

Importance of Electrostatically Driven Non-Covalent Interactions in Asymmetric Catalysis

Computational chemistry has become a powerful tool for understanding the principles of physical organic chemistry and rationalizing and even predicting the outcome of catalytic and non-catalytic organic reactions. Non-covalent interactions are prevalent in organic systems and accurately capturing their impact is vital for the reliable description of myriad chemical phenomena. These interactions impact everything from molecular conformations and stability to the outcome of stereoselective organic reactions and the function of biological macromolecules. Driven by the emergence of density functional theory (DFT) methods that can account for dispersion-driven noncovalent interactions, there has been a renaissance in terms of computational chemistry shaping modern organic chemistry. DFT Studies of the origins of stereoselectivity in asymmetric organocatalytic reactions can not only provide key information on the mode of asymmetric induction, but can also guide future rational catalyst design. We start with an overview of weak intermolecular interactions and aromatic interactions. Special emphasis is given to the methods that one can use to study these ephemeral interactions. We next provide a brief account how computational chemistry has aided our understanding of chiral phosphoric acid (CPA) catalyzed reactions. Thereafter, three case studies showcasing the importance of non-covalent interactions in chiral NHC catalysis, CPA catalysis, and chiral nucleophilic catalysis has been elaborated. Each of these studies highlights the importance of electrostatically-driven non-covalent interactions in controlling reactivity and selectivity. Moreover, unprecedented activation modes are identified and new predictive selectivity models developed that can be used to rationalize the outcome of future reactions. Studying these reactions using state of art DFT methods, we aimed not only to contribute to the understanding of their selectivity and the importance of noncovalent interactions in catalysis, but also to bring a sound understanding that will enable the design of new reactions and better catalysts. Overall, this dissertation highlights the underappreciated role of electrostatic interactions in controlling reactivity and selectivity in asymmetric catalysis

Computational approaches to fragment based screening

Polarization is an often - neglected term in molecular modelling, and this is particularly the case in docking. However, the growing interest in fragment - based drug design, coupled with the small size of fragments that makes them amenable to quantum mechanical treatment, has created new opportunities for including polarization, anisotropic electrostatics and realistic repulsion potentials in docking. We have shown that polarization implemented as induced charges can offer in the region of a 10-15% improvement in native docking results, as judged by the percentage of poses within a rather tight threshold of 0.5 or 1.0 Å, where accurate prediction of binding interactions, are more likely. This is a significant improvement given the quality of current commercial docking programs (such as Glide use d here). This improvement is most apparent when the correct pose is known a priori, so that the extent of polarization is correctly modelled, and scoring is based on force - fields that do not scale the electrostatics. The introduction of specific active - sit e water molecules was shown to have a far greater effect than the polarization, probably because of the introduction of 3 additional full charges, rather than introduction of smaller charge perturbations. With active site waters , polarization is more likely to improve the docking when the water molecule is carefully orientated using quantum mechanical/molecular mechanics (QM/MM) methods. The placement of such water molecules is a matter of great current interest; we have shown that the water molecule can be placed with some degree of reliability simply by docking with the ligand present, provided that the water makes good hydrogen bonding interactions (these are the very conditions under which it is desirable to include the specific active-site water). Anisotropic electrostatics and exponential repulsion for rigid fragments was investigated using Orient and compared to QM/MM methods, all methods merited further research. The general hierarchy is that native docking using Glide (with polarization)> QM/MM (with MM polarization)> Orient-based methods. Thus, we expanded the Glide (with polarization) dataset to include more realistic crossdocking experiments on over 5000 structures. RMSD analysis resulted in many examples of clear improvement for including polarization