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.

Det blir allt viktigare att bygga energieffektivt och EU:s direktiv om energiprestanda har gjort att hårdare krav har införts i Boverkets byggregler (BBR). Detta har gjort att högre krav ställs på noggrannheten vid energiberäkningar i projekteringsfasen av ett byggprojekt. Vid en energiberäkning görs en rad inställningar och antaganden kring parametrar kopplade till byggnadens olika system, klimatskalet, samt det mänskliga beteendet i byggnaden. Det är vanligt att osäkerheter förekommer kring dessa parameterinställningar och detta kan i sin tur orsaka osäkerheter i beräkningsresultatet. För att undersöka hur stor inverkan osäkra parametrar har på beräkningsresultatet kan olika metoder av känslighetsanalys tillämpas. Syftet med detta arbete var att ta fram och tillämpa en metod för att genomföra en omfattande känslighetsanalys av osäkra parametrar vid energiberäkningar med simuleringsverktyget IDA ICE. Vidare gjordes en utvärdering över känslighetsanalysens roll i samband med energiberäkningar och hur resultaten kan användas för att förklara skillnader i projekterad och verklig energianvändning för en fastighetsägare. De inledande förberedelserna resulterade i en metod för global känslighetsanalys vid energiberäkningar i IDA ICE som låg till grund för större delen av detta arbete. Metoden använder sig av standardiserade regressionskoefficienter som känslighetsindikatorer och dessa beräknades genom att tillämpa Monte Carlo-simuleringar och multipel linjär regressionsanalys. Även en enklare metod för lokal känslighetsanalys vid energiberäkningar i IDA ICE undersöktes. Ett antal olika fall studerades i detta arbete och för samtliga fall undersöktes parametrarnas inverkan på den totala energianvändningen och primärenergitalet. En byggnadsmodell skapades över en byggnad i Umeå med fjärrvärme som uppvärmningskälla. För denna byggnadsmodell gjordes Monte Carlo-simuleringar och känslighetsanalys för basfallet, ett fall med bergvärme som uppvärmningskälla och ett fall där verksamheten förändrades. Klimatförutsättningarnas betydelse undersöktes genom att använda samma byggnadsmodell vid alternativa geografiska placeringar och genomföra känslighetsanalyser med den framtagna metoden. Förändringar i verksamheten, uppvärmningskällan och klimatet, visade sig alla påverka parametrarnas inverkan på beräkningsresultaten. En slutsats som gick att dra från resultaten var att osäkerheter i parametrar kopplade till byggnadsmodellernas värme- och ventilationssystem hade stor inverkan på beräkningsresultaten jämfört med de andra parametrarna. Även köldbryggornas specifika värmeförlustfaktor visade sig ha stor inverkan. Parametrar kopplade till mänskligt beteende hade även de relativt stor inverkan medan parametrarna kopplade till klimatskalets U-värden i de flesta fall visade sig ha mindre inverkan än de andra parametrar som undersöktes. / To build energy efficient buildings are becoming more important and as a response to the Energy Performance of Buildings Directive from the EU, harder requirements have been introduced into Boverket's building regulations (BBR). Higher demands are therefore placed on accuracy in energy calculations during the design phase of a building. When performing the energy calculations several parameter settings and assumptions are made that are linked to the building systems, envelope and the human behaviour inside the building. It is common that uncertainties occur around these parameter settings and this can often cause uncertainties in the calculation result. Different methods of sensitivity analysis can be applied to investigate which impact uncertain parameters have on the calculation results. The purpose of this master thesis was to develop and apply a method for computing a comprehensive sensitivity analysis of uncertain parameters in energy calculations with the simulation tool IDA ICE. Furthermore, an evaluation was made of the role of sensitivity analysis in combination with energy calculations and how the results can be used to explain differences in predicted and actual energy use for a property owner. The initial preparations resulted in a method for global sensitivity analysis for energy calculations in IDA ICE, which was the basis for the most part of this thesis. This method uses the standardized regression coefficients as sensitivity indices, which was calculated by applying Monte Carlo simulations and multiple linear regression. A simpler method for local sensitivity analysis was also investigated. In this thesis, a number of different cases were studied and for all of them, the influence of the parameters on the total energy use and the primary energy number was investigated. A building model was created for a building located in Umeå with district heating as heating source. For this building model, Monte Carlo simulations and sensitivity analysis were executed for the base case, a case with geothermal energy as heating source, and a case where the building was used as office spaces. The importance of climate conditions was investigated by using the same building model in alternative geographical locations and conduct sensitivity analysis with the developed method. Changes in operations, the heating source and the climate, all affected the influence of the parameters on the calculation results. One conclusion that could be made from the results was that uncertainties in parameters linked to the building models' heating and ventilation systems had a great impact on the calculation results compared to the other parameters. Also, the specific heat transfer coefficient of the thermal bridges was among the parameters with the greatest influence. The parameters linked to human behaviour also had a relatively large influence while parameters linked to the building envelope in most cases were found to have less influence than the other parameters examined.

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

I Sverige står bygg- och fastighetssektorn för nära en femtedel av koldioxidutsläppen och en tredjedel av energianvändningen varav en stor del kommer från uppvärmning av byggnader. Ett tillvägagångssätt för att minska energibehovet i bostäder är genom krav på energieffektivitet. Där spelar isoleringsmaterial stor roll för att minska värmeförlusterna i byggnaden. Ett problem med för tjock isolering är att isoleringsmaterialen i sig har viss kvantifierbar miljöpåverkan. I denna studie bestäms livscykelpåverkan från olika isoleringsmaterial med avseende på primärenergianvändning, växthuspotential, kostnad samt övrig miljöpåverkan. Studien undersöker även hur tjockleken av olika isoleringsmaterial påverkar driftenergin i byggnaden Backåkra 2, belägen i centrala Stockholm. Syftet är att bestämma den optimala tjockleken för varje isoleringsmaterial i byggnaden med avseende att minimera primärenergianvändningen, växthuspotentialen samt kostnaderna under en tidsperiod på 50 år. Övrig miljöpåverkan fastställs även. Materialen som utvärderats är glasull, cellulosaisolering, polyuretan/polyisocyanurat, vakuumisolering, aerogel, grafitcellplast, samt fenolbaserad isolering. Två olika avfallsscenarier implementeras varav ett scenario har hög materialåtervinning och ett annat har hög energiåtervinning. I en känslighetsanalys studeras inverkan av primärenergifaktorn, isoleringsmaterialens livslängd, koldioxidfaktorn, U-värden i byggnadens fönster samt andra värden för livscykelpåverkan. Resultaten visar att vald tjocklek av isoleringsmaterial i byggnaden i dag ligger nära den optimala tjockleken med avseende på minimal primärenergianvändning. Om isoleringsmaterialet har lägre koldioxidutsläpp under sin livscykel hamnar tjockleken i dagsläget nära den optimala tjockleken med avseende att minimera växthuspotentialen. Materialet aerogel har högst värden i alla påverkanskategorier i båda avfallsscenarierna. Lägst primärenergianvändning har vakuum- och cellulosaisolering vid optimala tjockleka på . Cellulosaisolering ger även upphov till lägst växthuspotential medan grafitcellplast har lägst kostnad för de optimala tjocklekarna i båda avfallsscenarier. Hög material-återvinningsgrad ger upphov till tjockare isolering och högre värden för påverkansfaktorerna. En hög energiåtervinningsgrad leder däremot till tunnare isolering och lägre värden. Att optimera isoleringsmaterialens tjocklek utifrån alla tre kriterier (primärenergianvändning, växthuspotential och kostnad) kan innebära svårigheter eftersom skillnaden mellan optimala tjocklekar är stor. Resultatet är känsligast för förändringar av livslängden och denna bör utvärderas noggrannare i framtida studier för att i högre utsträckning likna den verkliga byggnaden. Framtida studier kan även kretsa kring mer generell tillämpning av liknande analys för olika typer av byggnader i olika geografiska regioner. I vissa typer av byggnader är isoleringsmaterialens påverkan gällande primärenergianvändning och växthuspotential i förhållande till den totala byggnaden signifikant. I sådana fall har optimering av isoleringstjocklek stor betydelse för byggnadens totala prestanda och kan bidra till att minska byggnadens miljöpåverkan. Avslutningsvis kan denna studie bidra till en minskning av primärenergianvändningen, miljöpåverkan och kostnaderna i en energieffektiv byggnad. Därmed erhålls ett hållbarhetsperspektiv under hela livscykeln. / In Sweden, the construction and real estate sector accounts for approximately one fifth of the carbon dioxide emissions and one third of the total energy use, mainly due to heating. In order to reduce both energy requirement and environmental impact, energy efficient measures are of great importance. Insulation materials play a major role in reducing heat losses. However, manufacturing of insulation materials is an energy-intensive process with impact on the environment. In this study, the life cycle impact of seven different insulation materials was determined. The study considers the energy efficient building “Backåkra 2” in Sweden, planned to be completed next year, as a case study for evaluating lifecycle environmental and economic performances. It is investigated how the operating energy in “Backåkra 2” is affected by the choice of different insulation materials and their thicknesses. The optimal thickness of each insulation material in the building was determined in order to minimize primary energy use, global warming potential and cost over a period of 50 years. For the determined thicknesses, other environmental impacts were also investigated. The evaluated insulation materials are glass wool, cellulose insulation, polyuretan/polyisocyanurat, vacuum insulation, aerogel, graphite foam insulation, and phenolic based insulation. In the lifecycle analysis, two different waste scenarios are also implemented, of which one has high material recycling and the other has high energy recovery. A sensitivity analysis examines the impact of the primary energy factor, the lifespan of the insulation materials, the carbon dioxide factor, the U-values in the building's windows and other values for the life cycle impact. The results show that the selected thickness of insulation material in the building today of 19 cm is close to the optimal thickness with respect to minimal primary energy use. If the insulation material has lower carbon dioxide emissions during its lifecycle, the thickness is at present close to the optimal thickness in terms of minimizing the global warming potential. Aerogel has the highest values in all impact categories in both waste scenarios. Vacuum insulation will achieve the lowest primary energy use at its optimal thicknesses of 11,26 cm for waste scenario 0 while cellulose will achieve the lowest primary energy use of all materials at a thickness of 64,5 cm for waste scenario 50. Cellulose insulation also has the lowest global warming potential, while graphite foam insulation has the lowest cost for the optimal thicknesses in both waste scenarios. Higher material recovery rates give optimum at larger thicknesses, while high energy recovery rates lead to thinner insulation thickness. Optimizing the thickness of insulation materials based on all three criteria (primary energy use, global warming potential and cost) can cause difficulties due to a high difference in results. The result in the analysis is sensitive to changes in lifespan, and this should be more carefully evaluated in future studies to resemble the real building. Future studies can also revolve around more general application of similar analysis for different types of buildings in different geographic regions. In some types of buildings, the impact of insulation materials on primary energy use and global warming potential compared to the total building is significant. In such cases, optimization of insulation thickness has a significant impact on the overall performance and can reduce the environmental impact generated by the building. In conclusion, this study can contribute to a reduction of the primary energy use, the environmental impact and the costs in an energy efficient building throughout the whole life cycle.