Classical And Quantum Mechanical Simulations Of Condensed Systems And Biomolecules

This work describes the fundamental study of two enzymes of Fe(II)/-KG super family enzymes (TET2 and AlkB) by applying MD and QM/MM approaches, as well as the development of multipolar-polarizable force field (AMOEBA/GEM-DM) for condensed systems (ionic liquids and water). TET2 catalytic activity has been studied extensively to identify the potential source of its substrate preference in three iterative oxidation steps. Our MD results along with some experimental data show that the wild type TET2 active site is shaped to enable higher order oxidation. We showed that the scaffold stablished by Y1902 and T1372 is required for iterative oxidation. The mutation of these residues perturbs the alignment of the substrate in the active site, resulting in “5hmC-stalling” phenotype in some of the mutants. We provided more details on 5hmC to 5fC oxidation mechanism for wild type and one of the “5hmC-stallling” mutants (E mutant). We showed that 5hmC oxidizes to 5fC in the wild type via three steps. The first step is the hydrogen atom abstraction from hydroxyl group of 5hmC, while the second hydrogen is transferred from methylene group of 5hmC through the third transition state as a proton. Our results suggest that the oxidation in E mutant is kinetically unfavorable due to its high barrier energy. Many analyses have been performed to qualitatively describe our results and we believed our results can be used as a guide for other researchers. In addition, two MD approaches (explicit ligand sampling and WHAM) are used to study the oxygen molecule diffusion into the active site of AlkB. Our results showed that there are two possible channels for oxygen diffusion, however, diffusion through one of them is thermodynamically favorable. We also applied multipolar-polarizable force field to describe the oxygen diffusion along the preferred tunnel. We showed that the polarizable force field can describe the behavior of the highly polarizable systems accurately. We also developed a new multipolar-polarizable force field (AMOEBA/GEM-DM) to calculate the properties of imidazolium- and pyrrolidinium- based ionic liquids and water in a range of temperature. Our results agree well with the experimental data. The good agreement between our results and experimental data is because our new parameters provide an accurate description of non-bonded interactions. We fit all the non-bonded parameters against QM. We use the multipoles extracted from fitted electron densities (GEM) and we consider both inter- and intra-molecular polarization. We believe this method can accurately calculate the properties of condensed systems and can be helpful for designing new systems such as electrolytes

Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field

Hydration free energy (HFE) calculations are often used to assess the performance of biomolecular force fields and the quality of assigned parameters. The AMOEBA polarizable force field moves beyond traditional pairwise additive models of electrostatics and may be expected to improve upon predictions of thermodynamic quantities such as HFEs over and above fixed point charge models. The recent SAMPL4 challenge evaluated the AMOEBA polarizable force field in this regard, but showed substantially worse results than those using the fixed point charge GAFF model. Starting with a set of automatically generated AMOEBA parameters for the SAMPL4 dataset, we evaluate the cumulative effects of a series of incremental improvements in parameterization protocol, including both solute and solvent model changes. Ultimately the optimized AMOEBA parameters give a set of results that are not statistically significantly different from those of GAFF in terms of signed and unsigned error metrics. This allows us to propose a number of guidelines for new molecule parameter derivation with AMOEBA, which we expect to have benefits for a range of biomolecular simulation applications such as protein ligand binding studie

Description of Potential Energy Surfaces of Molecules using FFLUX Machine Learning Models

yesA new type of model, FFLUX, to describe the interaction between atoms has been developed as an alternative to traditional force fields. FFLUX models are constructed from applying the kriging machine learning method to the topological energy partitioning method, Interacting Quantum Atoms (IQA). The effect of varying parameters in the construction of the FFLUX models is analyzed, with the most dominant effects found to be the structure of the molecule and the number of conformations used to build the model. Using these models the optimization of a variety of small organic molecules is performed, with sub kJ mol-1 accuracy in the energy of the optimized molecules. The FFLUX models are also evaluated in terms of their performance in describing the potential energy surfaces (PESs) associated with specific degrees of freedoms within molecules. While the accurate description of PESs presents greater challenges than individual minima, FFLUX models are able to achieve errors of <2.5 kJ mol-1 across the full C-C-C-C dihedral PES of n-butane, indicating the future possibilities of the technique

Non-empirical Force-Field Development for Weakly-Bound Organic Molecules

This thesis pioneers the development of non-empirical anisotropic atom-atom force-fields for organic molecules, and their use as state-of-the-art intermolecular potentials for modelling the solid-state. The long-range electrostatic, polarization and dispersion terms have been derived directly from the molecular charge density, while the short-range terms are obtained through fitting to the symmetry-adapted perturbation theory (SAPT(DFT)) intermolecular interaction energies of a large number of different dimer configurations. This study aims to establish how far this approach, previously used for small molecules, could be applied to specialty molecules, and whether these potentials improve on the current empirical force-fields FIT and WILLIAMS01. The scaling of the underlying electronic structure calculations with system size means many adaptions have been made. This project aims to generate force-fields suitable for use in Crystal Structure Prediction (CSP) and for modelling possible polymorphs, particularly high-pressure polymorphs. By accurately modelling the repulsive wall of the potential energy surface, the high pressure/temperature conditions typically sampled by explosive materials could be studied reliably, as shown in a CSP study of pyridine using a non-empirical potential. This thesis also investigates the transferability of these potentials from the gas to condensed-phase, as well as the transferability and importance of the intermolecular interactions of flexible functional groups, in particular NO2 groups. The charge distribution was found to be strongly influenced by variations in the observed NO2 torsion angle and the conformation of the rest of the molecule. This conformation dependence coupled with the novelty of the methods and size of the molecules has made developing non-empirical models for flexible nitro-energetic materials very challenging. The thesis culminates in the development of a bespoke non-empirical force-field for rigid trinitrobenzene and its use in a CSP study

Computational modeling of protein-ion binding and nucleic acids

Metal ions and nucleic acids are essential for a variety of biological functions. Metal ions play roles in enzyme catalysis, signal transduction and muscle contraction, and the stabilization of protein and nucleic acids structures. Nucleic acids are integral to gene expression and regulation. There are many unsolved questions regarding the function and thermodynamics of metal ions and nucleic acids. Molecular modeling has been an indispensable tool for microscopic understanding of biological processes. While tremendous success has been achieved for the modeling of proteins and organic molecules, it remains challenging to accurate model charged molecules, such as metal ions and nucleic acids. The difficulty mainly arises from the inadequate description of electrostatic interaction and polarization. In this work, accurate models for metal ions and nucleic acids based on AMOEBA polarizable force field were developed. These models along with advanced quantum mechanical methods were then used to study some practical problems. First, the principles underlying Ca²⁺/Mg²⁺ selectivity in ion-binding proteins were studied. It was shown that the Ca²⁺/Mg²⁺ selectivity can be explained by many-body polarization, which depends on the chemistry and geometry of the binding pocket. Second, an existing controversial question regarding the conduction mechanism of potassium channels was resolved by molecular dynamics (MD) simulations with AMOEBA. Contrary to previous beliefs, the conduction operates through nearly ion-saturated states. This mechanism is compatible with almost all existing experimental data. Third, free energy calculation with AMOEBA was used to predict the effect of chemical modifications on the stability of DNA-RNA hybrids, which has implications for the development of gene therapy. Overall, the AMOEBA polarizable force field significantly improves the accuracy for modeling of metal ions and nucleic acids. It is expected that application of polarizable force field will lead to more exciting findings on biological systems.Biomedical Engineerin

Computational studies of protein-ligand recognition

Molecular recognition between biomolecules and ligands is very specific in living cells. The functions of all biochemical processes and cell mechanisms are dependent upon complex but specific non-covalent intermolecular interactions. As essential building blocks in protein and nucleic acid, phosphate groups are commonly found in nucleic acids, proteins, and lipids. Nearly half of known proteins have been shown to interact with ligands containing a phosphate group. Binding of a phosphoryl group is fundamental to a range of biological processes including metabolism, biosynthesis, gene regulation, signal transduction, muscle contraction, and antibiotic resistance. Phosphorylation is one of the most common forms of reversible posttranslational modification of protein and, nearly 30% of all proteins are phosphorylated on at least one residue in cells. However, phosphate binding sites are less well defined and fundamental principles of why and how proteins recognize phosphate groups are not yet fully understood. Molecular modeling is a common tool for studying biomolecular structure, dynamics, interaction and function. Due to the complex electrostatics, high concentration of ions and intricate interactions with environment, however, the modeling and designing of highly charged drug-like molecules and nucleic acid derivatives are extremely difficult. This thesis will focus on the highly charged phosphate, including its different protonation states, and energetic and thermodynamic driving forces behind protein-phosphate recognition. This thesis work will also discuss the development of more sophisticated computational models, AMOEBA+, that are necessary for a better understanding and prediction of the physical properties of small organic molecules. Four projects will be discussed in this dissertation: two projects on force field development, and two on applying molecular dynamic simulations to understand biological processes. These projects have led to new insights into understanding of physical and chemical principles and mechanisms underlying highly protein-phosphate binding and nucleic acid stability. In addition, this thesis work will enhance the capability to develop and apply computational and theoretical frameworks to model, predict and design proteins, therapeutics, and diagnostic strategies targeting phosphates, phosphate-containing biomoleculesBiomedical Engineerin