The development and approval of new drugs is an expensive process. The total cost for the approval of a new compound is on average 1.0 - 1.2 billion dollars and the entire process lasts about 12 - 15 years. The main difficulties are related to poor pharmacokinetics, lack of efficacy and unwanted side effects. These problems have naturally led to the question if new and alternative methodologies can be developed to find reliable and low cost alternatives to existing practices. Nowadays, computer-assisted tools are used to support the decision process along the early stages of the drug discovery path leading from the identification of a suitable biomolecular target to the design/optimization of drug-like molecules. This process includes assessments about target druggability, screening of molecular libraries and the optimization of lead compounds where new drug-like molecules able to bind with sufficiently affinity and specificity to a disease-involved protein are designed. Existing computational methods used by the pharmaceutical industry are usually focused on the screening of library compounds such as docking, chemoinformatics and other ligand-based methods to predict and improve binding affinities, but their reliable application requires improvements in accuracy. New quantitative methods based on molecular simulations of drug binding to a protein could greatly improve prospects for the reliable in-silico design of new potent drug candidates. A common parameter used by medicinal chemists to quantify the affinity between candidate ligands and a target protein is represented by the free energy of binding. However, despite the increased amount of structural information, predicting binding free energy is still a challenge and this technique has found limited use beyond academia. A major reason for limited adoption in the industry is that reliable computer models of drug binding to a protein must reproduce the change in molecular conformations of the drug and protein upon complex formation and this includes the correct modelling of weak non-covalent interactions such as hydrogen bonds, burials of hydrophobic surface areas, Van der Waals interactions, fixations of molecular degrees of freedom solvation/desolvation of polar groups and different entropy contributions related to the solvent and protein interactions. For several classes of proteins these phenomena are not easy to model and often require extremely computationally intensive simulations. The main goal of the thesis was to explore efficient ways of computing binding affinities by using molecular simulations. With this aim, novel software to compute relative binding free energies has been developed. The implementation is based on alchemical transformations and it extended a preexisted piece of software Sire, a molecular modeling framework, by using the OpenMM APIs to run fast molecular dynamics simulations on the latest GPGPU technology. This new piece of software has equipped the scientific community with a flexible and fast tool, not only to predict relative binding affinities, but also a starting point to develop new sampling methods for instance hybrid molecular dynamics and Monte Carlo. The implementation has been validated on the prediction of relative hydration free energy of small molecules, showing good agreement with experimental data. In addition, non-additive effects to binding affinities in series of congeneric Thrombin inhibitors were investigated. Although excellent agreement between predicted and experimental relative binding affinities was achieved, it was not possible to accurately predict the non-additivity levels in most of the examined inhibitors, thus suggesting that improved force fields are required to further advance the state-of-the art of the field.

Alzheimer's disease is the leading cause of senile dementia in the elderly, and as life expectancy increases across the globe, incidence of the disease is continually increasing. Current estimates place the number of cases at 25-30 million worldwide, with more than 5.4 million of these occurring in the United States. While the exact cause of the disease remains a mystery, it has become clear that the amyloid β-peptide (Aβ) is central to disease pathogenesis. The aggregation and deposition of this peptide in the brain is known to give rise to the hallmark lesions associated with Alzheimer's disease, but its exact mechanism of toxicity remains largely uncharacterized. Molecular dynamics (MD) simulations have achieved great success in exploring molecular events with atomic resolution, predicting and explaining phenomena that are otherwise obscured from even the most sensitive experimental techniques. Due to the difficulty of obtaining high-quality structural data of Aβ and its toxic assemblies, MD simulations can be an especially useful tool in understanding the progression of Alzheimer's disease on a molecular level. The work contained herein describes the interactions of Aβ monomers and oligomers with lipid bilayers to understand the mechanism by which Aβ exerts its toxicity. Also explored is the mechanism by which flavonoid antioxidants may prevent Aβ self-association and destabilize toxic aggregates, providing insight into the chemical features that give rise to this therapeutic effect. / Ph. D.

When the states of a system can be described by the extrema of a high-dimensional function, the characterisation of its complexity, i.e. the enumeration of the accessible stable states, can be reduced to a sampling problem. In this thesis a robust numerical protocol is established, capable of producing numerical estimates of the total number of stable states for a broad class of systems, and of computing the a-priori probability of observing any given state. The approach is demonstrated within the context of the computation of the configurational entropy of two and three-dimensional jammed packings. By means of numerical simulation we show the extensivity of the granular entropy as proposed by S.F. Edwards for three-dimensional jammed soft-sphere packings and produce a direct test of the Edwards conjecture for the equivalent two dimensional systems. We find that Edwards’ hypothesis of equiprobability of all jammed states holds only at the (un)jamming density, that is precisely the point of practical significance for many granular systems. Furthermore, two new recipes for the computation of high-dimensional volumes are presented, that improve on the established approach by either providing more statistically robust estimates of the volume or by exploiting the trajectories of the paths of steepest descent. Both methods also produce as a natural by-product unprecedented details on the structures of high-dimensional basins of attraction. Finally, we present a novel Monte Carlo algorithm to tackle problems with fluctuating weight functions. The method is shown to improve accuracy in the computation of the ‘volume’ of high dimensional ‘fluctuating’ basins of attraction and to be able to identify transition states along known reaction coordinates. We argue that the approach can be extended to the optimisation of the experimental conditions for observing certain phenomena, for which individual measurements are stochastic and provide little guidance.

Molecular modeling has come a long way during the past decades and in the current thesis modeling of biological membranes is the focus. The main method of choice has been classical Molecular Dynamics simulations and for this technique a model Hamiltonian, or force field (FF), has been developed for lipids to be used for biological membranes. Further, ways of more accurately simulate the interactions between solutes and membranes have been investigated. A FF coined Slipids was developed and validated against a range of experimental data (Papers I-III). Several structural properties such as area per lipid, scattering form factors and NMR order parameters obtained from the simulations are in good agreement with available experimental data. Further, the compatibility of Slipids with amino acid FFs was proven. This, together with the wide range of lipids that can be studied, makes Slipids an ideal candidate for large-scale studies of biologically relevant systems. A solute's electron distribution is changed as it is transferred from water to a bilayer, a phenomena that cannot be fully captured with fixed-charge FFs.  In Paper IV we propose a scheme of implicitly including these effects with fixed-charge FFs in order to more realistically model water-membrane partitioning. The results are in good agreement with experiments in terms of free energies and further the differences between using this scheme and the more traditional approach were highlighted. The free energy landscape (FEL) of solutes embedded in a model membrane is explored in Paper V. This was done using biased sampling methods with a reaction coordinate that included intramolecular degrees of freedom (DoF). These DoFs were identified in different bulk liquids and then used in studies with bilayers. The FELs describe the conformational changes necessary for the system to follow the lowest free energy path. Besides this, the pitfalls of using a one-dimensional reaction coordinate are highlighted.

Orientador: Maurice de Koning / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-27T17:09:46Z (GMT). No. of bitstreams: 1 Leite_RodolfoPaula_M.pdf: 4064445 bytes, checksum: 15e944e3607ec0d3b8cb66d00b6ea4f3 (MD5) Previous issue date: 2015 / Resumo: Neste trabalho, apresentamos um estudo a respeito do modelo de Uhlenbeck-Ford como um sistema de referencia para calculos de energia livre de sistemas na fase fluida, utilizando metodos de simulacao molecular. Este sistema artificial, que e caracterizado por um potencial puramente repulsivo e que diverge rapidamente, foi originalmente proposto como um modelo para o estudo teorico de gases imperfeitos. Este modelo foi motivado pelo fato de que todas as integrais de muitos corpos, envolvidas no calculo dos coeficientes viriais, podem ser facilmente calculadas analiticamente. Entretanto apenas oito coeficientes eram conhecidos. Dois novos coeficientes (..10 e ..11) foram determinados para o modelo neste trabalho, alem de uma expressao essencialmente exata para a equacao de estado e energia livre de Helmholtz em funcao de um parametro adimensional. Este nos permitira reunir todas as informacoes a respeito da energia livre do sistema em uma unica expressao, independentemente da escolha de parametros do potencial. Por fim, exploraremos a aplicabilidade deste modelo como um sistema de referencia para calculos de energia livre de sistemas na fase fluida, usando tecnicas de simulacao molecular a partir de processos fora de equilibrio. Nossos resultados para o fluido de Lennard-Jones e para o silicio liquido, descrito pelo potencial de Stillinger-Weber, demonstraram que o modelo de Uhlenbeck-Ford servira como um sistema de referencia para o calculo de energia livre de sistemas na fase fluida / Abstract: In this work, we present a study of the Uhlenbeck-Ford model as a reference system for freeenergy calculations of fluid-phase systems by molecular simulation methods. This artificial system, which is characterized by a rapidly-decaying purely repulsive potential, was originally proposed as a model for the theoretical study of imperfect gases, enabled by the fact that all the many-center integrals involved in the virial coefficients can be easily computed analytically. Although only eight coefficients were known. Two new coefficients (..10 e ..11) were determined for the model in this work, in addition to an essentially accurate expression to the equation of state and Helmholtz free-energy as a function of a dimensionless parameter. This will allow us to gather all information regarding the system of free-energy in a single expression, regardless of the choice of potential parameters. In the end, we explore the applicability of this model as a reference system for free-energy calculations of fluid-phase systems, using non equilibrium process with molecular simulation techniques. Our results for thevLennard-Jones fluid and liquid silicon, described by Stillinger-Weber potential, demonstrate that the Uhlenbeck-Ford model can be used as a reference system for free-energy calculations of fluid-phase systems / Mestrado / Física / Mestre em Física

Orientador: Maurice de Koning / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-31T00:11:25Z (GMT). No. of bitstreams: 1 SantosFlorez_PedroAntonio_M.pdf: 3560756 bytes, checksum: 596fa8433415493ec218ee7c185319ea (MD5) Previous issue date: 2016 / Resumo: O modelo de Uhlenbeck-Ford, que é um sistema artificial caracterizado por um potencial interatômico logarítmico e repulsivo, foi definido originalmente para o estudo teórico de gases imperfeitos, baseado no fato de que todas as integrais de muitos corpos, envolvidas no cálculo de coeficientes viriais, podem ser calculadas analiticamente. Assim, este modelo possui uma expressão exata para a equação de estado e a energia livre de Helmholtz na fase fluida. Um potencial escalonado deste modelo já foi proposto como sistema de referência na implementação de métodos de simulação atomística, para cálculos de energia livre de sistemas na fase fluida. Neste trabalho, é construído o diagrama de fase do modelo de Uhlenbeck-Ford dependente deste fator de escalonamento, delimitando as fases fluida e sólida, com estruturas cristalinas (BCC e FCC). A estabilidade das diferentes fases foi estudada analisando as curvas de energia livre, que foram obtidas utilizando a técnica de simulação atomística da Dinâmica Molecular a partir de processos fora do equilíbrio. Nossos resultados mostraram que existem regiões para qualquer densidade onde a fase fluida é a mais estável, e portanto, o modelo de Uhlenbeck-Ford pode ser usado como sistema de referência para cálculos de energia livre de sistemas na fase fluida / Abstract: The Uhlenbeck-Ford model, which is an artificial system characterized by a logarithmic and repulsive interatomic potential, was originally defined for the theoretical study of imperfect gases, based on the fact that all the many-body integrals, involved in calculating virial coefficients, can be calculated analytically. Thus, this model has an exact expression for the equation of state and the Helmholtz free energy in the fluid phase. A modified potential by a scale factor of this model was proposed as a reference system in the implementation of atomistic simulation methods for free energy calculation in the fluid phase. In this paper, we construct the phase diagram of the Uhlenbeck-Ford model dependent on a scale factor, finding the coexistence lines between fluid and solid phases, with crystalline structures (BCC and FCC). The stability of the different phases was studied by analyzing the free energy curves, which were obtained using the atomistic simulation technique of Molecular Dynamics, using nonequilibrium processes. Our results show that for any density, there exist regions in which the fluid phase is the most stable and therefore the Uhlenbeck-Ford model can be used as a reference system for free energy calculations of systems in the fluid phase / Mestrado / Física / Mestre em Física / 1370441/2014 / CAPES

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Investigating interactions between proteins and small molecules at an atomic scale is fundamental towards understanding biological processes and designing novel candidates during the pre-clinical stages of drug discovery. By optimizing the methods used to study these interactions in terms of accuracy and computational cost, we can accelerate this aspect of biological research and contribute more readily to therapeutic design. While biological assays and other experimental techniques are invaluable in quantitatively determining in vitro and in vivo inhibition activity, as well as validating computational predictions, there is an inherent benefit in the possible throughput provided by molecular dynamics (MD) simulations and related computational methods. These calculations provide researchers with unparalleled access to large amounts of all-atom sampling of biological systems, including non-physical pathways and other enhanced sampling methods. This dissertation presents research into advancing the application of expanded ensemble and other simulation-based methods of ligand design towards reliable and efficient absolute free energy of binding calculations on the scale of hundreds to thousands of small molecule ligands. This culminates in a combined workflow that allows for an automated approach to the force-field parameterization of custom systems, simulation preparation, optimization of the restraint and sampling protocols, production free energy simulations, and analysis that has facilitated the computation of absolute binding free energy predictions. Specifically highlighted is our ongoing effort to discover novel inhibitors of the main protease (Mpro) of SARS-CoV-2 as well as participation in the SAMPL9 Host-Guest Challenge. / Chemistry

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Orientador: Maurice de Koning / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Física Gleb Wataghin / Made available in DSpace on 2018-08-23T00:50:21Z (GMT). No. of bitstreams: 1 Freitas_RodrigoMoura_M.pdf: 11496259 bytes, checksum: 41c29f22d80da01064cf7a3b9681b05f (MD5) Previous issue date: 2013 / Resumo: Devido aos avanços conceptuais e técnicos feitos em física computacional e ciência dos materiais computacional nos estamos aptos a resolver problemas que eram inacessíveis a alguns anos atrás. Nessa dissertação estudamos a evolução de alguma destas técnicas, apresentando a teoria e técnicas de simulação computacional para estudar transições de fase de primeira ordem com ênfase nas técnicas mais avançadas de calculo de energia livre (Reversible Scaling) e métodos de simulação de eventos raros (Forward Flux Sampling) usando a técnica de simulação atomística da Dinâmica Molecular. A evolução e melhora da e ciência destas técnicas e apresentada junto com aplicações a sistemas simples que permitem solução exata e também ao caso mais complexo da transição de fase Martenstica. Também apresentamos a aplicação de métodos numéricos no estudo do modelo de Pauling para o gelo. Nos desenvolvemos e implementamos um novo algoritmo para a criação e ciente de estruturas de gelo desordenadas. Este algoritmo de geração de cristais de gelo nos permitiu criar células de gelo Ih de tamanhos que não eram possíveis antes. Usando este algoritmo abordamos o problema de efeitos de tamanho finito não estudados anteriormente / Abstract: Due to the conceptual and technical advances being made in computational physics and computational materials science we have been able to tackle problems that were inaccessible a few years ago. In this dissertation we study the evolution of some of these techniques, presenting the theory and simulation methods to study _rst order phase transitions with emphasis on state-of-the-art free-energy calculation (Reversible Scaling) and rare event (Forward Flux Sampling) methods using the atomistic simulation technique of Molecular Dynamics. The evolution and efficiency improvement of these techniques is presented together with applications to simple systems that allow exact solution as well as the more the complex case of Martensitic phase transitions. We also present the application of numerical methods to study Pauling\'s model of ice. We have developed and implemented a new algorithm for efficient generation of disordered ice structures. This ice generator algorithm allows us to create ice Ih cells of sizes not reported before. Using this algorithm we address finite size effects not studied before / Mestrado / Física / Mestre em Física