42 research outputs found

    Metal Cations in Protein Force Fields: From Data Set Creation and Benchmarks to Polarizable Force Field Implementation and Adjustment

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    Metal cations are essential to life. About one-third of all proteins require metal cofactors to accurately fold or to function. Computer simulations using empirical parameters and classical molecular mechanics models (force fields) are the standard tool to investigate proteins’ structural dynamics and functions in silico. Despite many successes, the accuracy of force fields is limited when cations are involved. The focus of this thesis is the development of tools and strategies to create system-specific force field parameters to accurately describe cation-protein interactions. The accuracy of a force field mainly relies on (i) the parameters derived from increasingly large quantum chemistry or experimental data and (ii) the physics behind the energy formula. The first part of this thesis presents a large and comprehensive quantum chemistry data set on a consistent computational footing that can be used for force field parameterization and benchmarking. The data set covers dipeptides of the 20 proteinogenic amino acids with different possible side chain protonation states, 3 divalent cations (Ca2+, Mg2+, and Ba2+), and a wide relative energy range. Crucial properties related to force field development, such as partial charges, interaction energies, etc., are also provided. To make the data available, the data set was uploaded to the NOMAD repository and its data structure was formalized in an ontology. Besides a proper data basis for parameterization, the physics covered by the terms of the additive force field formulation model impacts its applicability. The second part of this thesis benchmarks three popular non-polarizable force fields and the polarizable Drude model against a quantum chemistry data set. After some adjustments, the Drude model was found to reproduce the reference interaction energy substantially better than the non-polarizable force fields, which showed the importance of explicitly addressing polarization effects. Tweaking of the Drude model involved Boltzmann-weighted fitting to optimize Thole factors and Lennard-Jones parameters. The obtained parameters were validated by (i) their ability to reproduce reference interaction energies and (ii) molecular dynamics simulations of the N-lobe of calmodulin. This work facilitates the improvement of polarizable force fields for cation-protein interactions by quantum chemistry-driven parameterization combined with molecular dynamics simulations in the condensed phase. While the Drude model exhibits its potential simulating cation-protein interactions, it lacks description of charge transfer effects, which are significant between cation and protein. The CTPOL model extends the classical force field formulation by charge transfer (CT) and polarization (POL). Since the CTPOL model is not readily available in any of the popular molecular-dynamics packages, it was implemented in OpenMM. Furthermore, an open-source parameterization tool, called FFAFFURR, was implemented that enables the (system specific) parameterization of OPLS-AA and CTPOL models. Following the method established in the previous part, the performance of FFAFFURR was evaluated by its ability to reproduce quantum chemistry energies and molecular dynamics simulations of the zinc finger protein. In conclusion, this thesis steps towards the development of next-generation force fields to accurately describe cation-protein interactions by providing (i) reference data, (ii) a force field model that includes charge transfer and polarization, and (iii) a freely-available parameterization tool.Metallkationen sind für das Leben unerlässlich. Etwa ein Drittel aller Proteine benötigen Metall-Cofaktoren, um sich korrekt zu falten oder zu funktionieren. Computersimulationen unter Verwendung empirischer Parameter und klassischer Molekülmechanik-Modelle (Kraftfelder) sind ein Standardwerkzeug zur Untersuchung der strukturellen Dynamik und Funktionen von Proteinen in silico. Trotz vieler Erfolge ist die Genauigkeit der Kraftfelder begrenzt, wenn Kationen beteiligt sind. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Werkzeugen und Strategien zur Erstellung systemspezifischer Kraftfeldparameter zur genaueren Beschreibung von Kationen-Protein-Wechselwirkungen. Die Genauigkeit eines Kraftfelds hängt hauptsächlich von (i) den Parametern ab, die aus immer größeren quantenchemischen oder experimentellen Daten abgeleitet werden, und (ii) der Physik hinter der Kraftfeld-Formel. Im ersten Teil dieser Arbeit wird ein großer und umfassender quantenchemischer Datensatz auf einer konsistenten rechnerischen Grundlage vorgestellt, der für die Parametrisierung und das Benchmarking von Kraftfeldern verwendet werden kann. Der Datensatz umfasst Dipeptide der 20 proteinogenen Aminosäuren mit verschiedenen möglichen Seitenketten-Protonierungszuständen, 3 zweiwertige Kationen (Ca2+, Mg2+ und Ba2+) und einen breiten relativen Energiebereich. Wichtige Eigenschaften für die Entwicklung von Kraftfeldern, wie Wechselwirkungsenergien, Partialladungen usw., werden ebenfalls bereitgestellt. Um die Daten verfügbar zu machen, wurde der Datensatz in das NOMAD-Repository hochgeladen und seine Datenstruktur wurde in einer Ontologie formalisiert. Neben einer geeigneten Datenbasis für die Parametrisierung beeinflusst die Physik, die von den Termen des additiven Kraftfeld-Modells abgedeckt wird, dessen Anwendbarkeit. Der zweite Teil dieser Arbeit vergleicht drei populäre nichtpolarisierbare Kraftfelder und das polarisierbare Drude-Modell mit einem Datensatz aus der Quantenchemie. Nach einigen Anpassungen stellte sich heraus, dass das Drude-Modell die Referenzwechselwirkungsenergie wesentlich besser reproduziert als die nichtpolarisierbaren Kraftfelder, was zeigt, wie wichtig es ist, Polarisationseffekte explizit zu berücksichtigen. Die Anpassung des Drude-Modells umfasste eine Boltzmann-gewichtete Optimierung der Thole-Faktoren und Lennard-Jones-Parameter. Die erhaltenen Parameter wurden validiert durch (i) ihre Fähigkeit, Referenzwechselwirkungsenergien zu reproduzieren und (ii) Molekulardynamik-Simulationen des Calmodulin-N-Lobe. Diese Arbeit demonstriert die Verbesserung polarisierbarer Kraftfelder für Kationen-Protein-Wechselwirkungen durch quantenchemisch gesteuerte Parametrisierung in Kombination mit Molekulardynamiksimulationen in der kondensierten Phase. Während das Drude-Modell sein Potenzial bei der Simulation von Kation - Protein - Wechselwirkungen zeigt, fehlt ihm die Beschreibung von Ladungstransfereffekten, die zwischen Kation und Protein von Bedeutung sind. Das CTPOL-Modell erweitert die klassische Kraftfeldformulierung um den Ladungstransfer (CT) und die Polarisation (POL). Da das CTPOL-Modell in keinem der gängigen Molekulardynamik-Pakete verfügbar ist, wurde es in OpenMM implementiert. Außerdem wurde ein Open-Source-Parametrisierungswerkzeug namens FFAFFURR implementiert, welches die (systemspezifische) Parametrisierung von OPLS-AA und CTPOL-Modellen ermöglicht. In Anlehnung an die im vorangegangenen Teil etablierte Methode wurde die Leistung von FFAFFURR anhand seiner Fähigkeit, quantenchemische Energien und Molekulardynamiksimulationen des Zinkfingerproteins zu reproduzieren, bewertet. Zusammenfassend lässt sich sagen, dass diese Arbeit einen Schritt in Richtung der Entwicklung von Kraftfeldern der nächsten Generation zur genauen Beschreibung von Kationen-Protein-Wechselwirkungen darstellt, indem sie (i) Referenzdaten, (ii) ein Kraftfeldmodell, das Ladungstransfer und Polarisation einschließt, und (iii) ein frei verfügbares Parametrisierungswerkzeug bereitstellt

    Modified Theories of Gravity and Cosmological Applications

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    This reprint focuses on recent aspects of gravitational theory and cosmology. It contains subjects of particular interest for modified gravity theories and applications to cosmology, special attention is given to Einstein–Gauss–Bonnet, f(R)-gravity, anisotropic inflation, extra dimension theories of gravity, black holes, dark energy, Palatini gravity, anisotropic spacetime, Einstein–Finsler gravity, off-diagonal cosmological solutions, Hawking-temperature and scalar-tensor-vector theories

    Numerical Simulations of Dusty Colliding Wind Binaries

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    Colliding Wind Binary (CWB) systems are relatively rare phenomena, but have a significant influence on galactic evolution in terms of dust production -- especially in the early universe. The mechanisms behind this dust production, however, are poorly understood. The strong winds from both partners in the binary system drive shocks that heat the dust forming region to temperatures in excess of 100 million Kelvin; whilst this region does rapidly cool, the initial shock temperatures would destroy any dust grains that formed outside the collision region. Furthermore, this collision region is difficult to observe and simulate, limiting our understanding of how grains form and evolve in this region. This thesis attempts to improve our understanding of the evolution of dust grains within these systems, particularly growth of these grains from small dust grain cores to micron-scale grains. A co-moving dust grain model was implemented that simulates growth through accretion of gas onto the dust grains, as well as destruction through gas-grain sputtering. The model also simulates cooling through collisional excitation and subsequent emission for both dust grains and gas. Overall, the goal of this model was to determine how dust growth was influenced by the wind and orbital characteristics of the system, and which of these characteristics were most important for dust growth. First, a parameter space exploration of dust producing CWB systems (WCd systems) was conducted, varying the orbital separation, the wind terminal velocity and the mass loss rate of each star. It was found that dust production is strongly influenced by the ratio of wind terminal velocities between each star, as well as the orbital separation. Following up on this, a limited simulation of the episodic dust forming system WR140 was conducted, in order to understand how variance in orbital separation through eccentricity changed dust production rates over the course of a periastron passage. Furthermore, it was determined that dust production occurs over a very short period immediately prior to periastron passage and a small period after, with an ``active'' phase of approximately 1 year, or an eighth of the systems orbital period Whilst there is much to be done in the future, and many more systems to be simulated (in particular the recently discovered WR+WR CWB systems WR48a and WR70-16) this model is a good first step towards shedding light on these elusive and dust-shrouded systems

    Review of Particle Physics

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    The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app.United States Department of Energy (DOE) DE-AC02-05CH11231government of Japan (Ministry of Education, Culture, Sports, Science and Technology)Istituto Nazionale di Fisica Nucleare (INFN)Physical Society of Japan (JPS)European Laboratory for Particle Physics (CERN)United States Department of Energy (DOE

    Elliptic partial differential equations from an elementary viewpoint

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    These notes are the outcome of some courses taught to undergraduate and graduate students from the University of Western Australia, the Pontif\'{\i}cia Universidade Cat\'olica do Rio de Janeiro, the Indian Institute of Technology Gandhinagar and the Ukrainian Catholic University in 2021 and 2022

    Review of Particle Physics

    Get PDF
    The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app

    Review of Particle Physics

    Get PDF
    The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings

    Medical Robotics

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    The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not

    Space-time residual minimization for parabolic partial differential equations

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    Many processes in nature and engineering are governed by partial differential equations (PDEs). We focus on parabolic PDEs, that describe time-dependent phenomena like heat conduction, chemical concentration, and fluid flow. Even if we know that a unique solution exists, we can express it in closed form only under very strict circumstances. So, to understand what it looks like, we turn to numerical approximation. Historically, parabolic PDEs are solved using time-stepping. One first discretizes the PDE in space as to obtain a system of coupled ordinary differential equations in time. This system is then solved using the vast theory for ODEs. While efficient in terms of memory and computational cost, time-stepping schemes take global time steps, which are independent of spatial position. As a result, these methods cannot efficiently resolve details in localized regions of space and time. Moreover, being inherently sequential, they have limited possibilities for parallel computation. In this thesis, we take a different approach and reformulate the parabolic evolution equation as an equation posed in space and time simultaneously. Space-time methods mitigate the aforementioned issues, and moreover produce approximations to the unknown solution that are uniformly quasi-optimal. The focal point of this thesis is the space-time minimal residual (MR) method introduced by R. Andreev, that finds the approximation that minimizes both PDE- and initial error. We discuss its theoretical properties, provide numerical algorithms for its computation, and discuss its applicability in data assimilation (the problem of fusing measured data to its underlying PDE)
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