Abstract Electrostatic interactions are very important in biomolecular systems. Electrostatic forces have received a great deal of attention due to their long-range nature and the trade-off between desolvation and interaction effects. It remains a challenging task to study and to predict the effects of electrostatic interactions in biomolecular systems. Computer simulation techniques that account for such interactions are an important tool for the study of biomolecular electrostatics. This study is largely concerned with the role of electrostatic interactions in biomolecular systems and with developing novel models to estimate the strength of such interactions. First, a novel formulation based upon continuum electrostatics to compute the electrostatic potential in and around two biomolecules in a solvent with ionic strength is presented. Many, if not all, current methods rely on the (non)linear Poisson-Boltzmann equation to include ionic strength. The present formulation, however, describes ionic strength through the inclusion of explicit ions, which considerably extends its applicability and validity range. The method relies on the boundary element method (BEM) and results in two very similar coupled integral equations valid on the dielectric boundaries of two molecules, respectively. This method can be employed to estimate the total electrostatic energy of two protein molecules at a given distance and orientation in an electrolyte solution with zero to moderately high ionic strength. Secondly, to be able to study interactions between biomolecules and membranes, an alternative model partly based upon the analytical continuum electrostatics (ACE) method has been also formulated. It is desirable to develop a method for calculating the total solvation free energy that includes both electrostatic and non-polar energies. The difference between this model and other continuum methods is that instead of determining the electrostatic potential, the total electrostatic energy of the system is calculated by integrating the energy density of the electrostatic field. This novel approach is employed for the calculation of the total solvation free energy of a system consisting of two solutes, one of which could be an infinite slab representing a membrane surface.

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Este trabalho teve como objetivo, desenvolver um modelo molecular que possa descrever propriedades de equilíbrio, bem como as forças de interação envolvidas em um sistema enzima-inibidor, onde a enzima é a 5-Enolpiruvil-Shikimato-3-Fosfato Sintase (EPSPs) e seu inibidor o herbicida glifosato (GPJ). A participação do substrato Shikimato-3- Fosfato (S3P) também foi estudada. A estabilidade e a distribuição de cargas ao longo da superfície da enzima EPSPs foram analisadas para subsidiar o desenvolvimento de um nanobiossensor específico para a detecção do herbicida glifosato através da funcionalização da ponta de um microscópio de força atômica (AFM) com a enzima EPSPs. A parametrização de dois ângulos diedros para o herbicida GPJ foram obtidos através de cálculos mecânico- quânticos ao nível de Hartree Fock, utilizando como conjunto de bases o 6-31G*. Os parâmetros obtidos, relacionados aos coeficientes de Ryckaert-Bellemans, foram implementados no campo de força OPLS-AA, utilizado pelo programa GROMACS. Simulações de dinâmica molecular direcional (SMD), foram realizadas em três possíveis caminhos de retirada do herbicida do sítio ativo, aplicando-se forças harmônicas externas com constante de força equivalente à do cantiléver do AFM, com o objetivo de simular experimentos de detecção do herbicida por microscopia de força atômica. Uma expansão cumulante de segunda ordem da igualdade de Jarzynski foi utilizada para os cálculos do perfil de energia livre ao longo da coordenada de reação e, portanto, para se obter o Potencial de Força Média (PMF) das simulações de SMD. Os três caminhos escolhidos apresentaram diferentes barreiras energéticas relacionadas com o rompimento das interações do inibidor com a enzima. Estas barreiras energéticas calculadas pelas simulações estão na mesma ordem de magnitude das energias livres de ligação para sistemas semelhantes obtidas a partir das constantes de inibição experimentais. / This work aims to developed a molecular model that can describe equilibrium properties, as well as the interacting forces involved in an enzyme-inhibitor system, where the enzyme is the 5-Enolpyruvyl-Shikimate-3-Phosphate Synthase (EPSPs) and its inhibitor is the glyphosate herbicide (GPJ). The participation of the substrate Shikimate-3-Phosphate (S3P) was also studied. The stability and distribution of charges along the surface of the EPSPs enzyme were analyzed for the development of a specific nanobiosensor for glyphosate herbicide detection through the functionalization of the tip of an atomic force microscope (AFM) with the enzyme EPSPs. The parameterization of two dihedral angles for the GPJ herbicide was obtained through mechanical-quantum calculations at the Hartree Fock level using the 6-31G* base set. The parameters obtained, related to the Ryckaert-Bellemans coefficients, were implemented in the OPLS-AA force field, used by the GROMACS program. Steered Molecular Dynamics Simulations (SMD) were performed in three possible unbinding pathways, to remove the herbicide from the active site, applying external harmonic forces with a force constant equivalent to that of the AFM cantilever, in order to simulate experiments to detect the herbicide by atomic force microscopy. A second-order cumulant expansion of the Jarzynski’s equation was used to calculate the free energy profile along the reaction coordinate and to obtain the potential of mean force (PMF) of the SMD simulations. The three paths chosen presented different energetic barriers related to the disruption of inhibitor interactions with the enzyme. These energy barriers calculated by the simulations are in the same order of magnitude as the bond free energies for similar systems obtained from the experimental inhibition constants. / Tese (Doutorado)

Molecular dynamics simulation was used to study ion permeation through different membrane proteins embedded in a lipid bilayer (DMPC) with different saline solutions. The potential of mean force (PMF) for ion transport was obtained by umbrella sampling simulations. A revised MacKerell force field for tryptophan residues was studied using gramicidin A (gA) channel as a test model. The revised force field contribution to the Na+ PMF was consonant with the prediction from the experimental results, but in stark contrast to the prediction of the CHARMM force field, version 22, for the tryptophan side-chain. A new grid-based correction map algorithm by MacKerell group, called CMAP, was introduced into the CHARMM force field, version 31. The CMAP algorithm focused on optimizing phi, psi dihedral parameters for the peptide backbone. The CMAP corrections reduced the excessive translocation barrier. Decomposition demonstrated the reduction in the translocation barrier was due to effects on the K+ PMFH2O rather than on K+ PMFgA. The presence of negatively charged sulfonate group at the entrance and exit of the gA channel affected the depth and the location of the highly occupied sites. The negatively charged sulfonate group produced a strong attraction for the cations in the bulk towards the channel mouth. In the M2 transmembrane domain channel (M2-TMD), three M2-TMD structures were studied, differing only in whether the selectivity-filter (four His37 side-chains) was uncharged, +2 charged, or +3 charged. M2-TMD structural properties were compared with the structural properties of other models extracted from NMR and X-ray studies. The spontaneous cation and anion entry into the charged selectivity-filter was different from that into a neutral selectivity-filter. Cl- ions had a lower free-energy barrier in the selectivity-filter than either Na+ or NH4+ ions through the M2-TMD channel. NH4+ ions had a lower free-energy barrier in the selectivity-filter than Na+ ions. Based on accessible rotamer conformations, a revised conductance mechanism was proposed. In this conductance mechanism, the His37 side-chain functioned as an acceptor and donor group, whereas the Trp41 side-chain functioned as a carrying group.

Solubility prediction usually refers to prediction of the intrinsic aqueous solubility, which is the concentration of an unionised molecule in a saturated aqueous solution at thermodynamic equilibrium at a given temperature. Solubility is determined by structural and energetic components emanating from solid-phase structure and packing interactions, solute–solvent interactions, and structural reorganisation in solution. An overview of the most commonly used methods for solubility prediction is given in Chapter 1. In this thesis, we investigate various approaches to solubility prediction and solvation model development, based on informatics and incorporation of empirical and experimental data. These are of a knowledge-based nature, and specifically incorporate information from the Cambridge Structural Database (CSD). A common problem for solubility prediction is the computational cost associated with accurate models. This issue is usually addressed by use of machine learning and regression models, such as the General Solubility Equation (GSE). These types of models are investigated and discussed in Chapter 3, where we evaluate the reliability of the GSE for a set of structures covering a large area of chemical space. We find that molecular descriptors relating to specific atom or functional group counts in the solute molecule almost always appear in improved regression models. In accordance with the findings of Chapter 3, in Chapter 4 we investigate whether radial distribution functions (RDFs) calculated for atoms (defined according to their immediate chemical environment) with water from organic hydrate crystal structures may give a good indication of interactions applicable to the solution phase, and justify this by comparison of our own RDFs to neutron diffraction data for water and ice. We then apply our RDFs to the theory of the Reference Interaction Site Model (RISM) in Chapter 5, and produce novel models for the calculation of Hydration Free Energies (HFEs).

Humic acids and humates are principal components of humic substances major organic constituents of soil, peat, coal and water around the world. I was involved in research into molecular dynamics simulations of interactions of quartz surfaces with aqueous solutions of ions and small organic molecules representing basic building blocks of larger biomolecules and functional groups of organic matter. We studied interactions of molecules with surfaces for a set of surface charge densities corresponding to the experimentally or environmentally relevant ranges of pH values employing molecular mechanics, molecular dynamics and ab initio techniques. Simulated quartz surfaces covered the range of surface charge densities 0.00, -0.03, -0.06 and -0.12 C-m-2, approximately corresponding to pH values 4.5, 7.5, 9.5 and 11. As model molecules, benzoic acid, phenol, o-salicylic acid and their conjugated bases were chosen. My task was to prepare topologies and parametric models of selected organic matter basic building blocks organic molecules. I focused on studying interactions of these molecules in an aqueous environment with mineral surface quartz. The aim was to process simulation results and analyse conformations of the adsorption complexes and their thermodynamic properties such as interaction energies, free energies and adsorption geometries.