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

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

Fir filter design for area efficient implementation /

In this dissertation, a variable precision algorithm based on sensitivity analysis is proposed for reducing the wordlength of the coefficients and/or the number of nonzero bits of the coefficients to reduce the complexity required in the implementation. Further space savings is possible if the proposed algorithm is associated with our optimal structures and derived scaling algorithm. We also propose a structure to synthesize FIR filters using the improved prefilter equalizer structure with arbitrary bandwidth, and our proposed filter structure reduces the area required. Our improved design is targeted at improving the prefilters based on interpolated FIR filter and frequency masking design and aims to provide a sharp transition-band as well as increasing the stopband attenuation. We use an equalizer designed to compensate the prefilter performance. In this dissertation, we propose a systematic procedure for designing FIR filters implementations. Our method yields a good design with low coefficient sensitivity and small order while satisfying design specifications. The resulting hardware implementation is suitable for use in custom hardware such as VLSI and Field Programmable Gate Arrays (FPGAs).FIR filters are preferred for many Digital Signal Processing applications as they have several advantages over IIR filters such as the possibility of exact linear phase, shorter required wordlength and guaranteed stability. However, FIR filter applications impose several challenges on the implementations of the systems, especially in demanding considerably more arithmetic operations and hardware components. This dissertation focuses on the design and implementation of FIR filters in hardware to reduce the space required without loss of performance

Empirical Study of the Effects of Information Description on Crowdfunding Success — The Perspective of Information Communication

From the perspective of information communication, we identify four dimensions of information description, including information quantity (word number, picture number and video number), information attitude, information quality (as measured by readability) and information update. We then empirically exmain their effects on crowdfunding success using binary logistic regression. And data is collected from Kickstarter, a popular crowdfunding platform. The results reveal that word number, picture number, video number and update are positively associated with crowdfunding success. And readability is negatively associated with crowdfunding success. In addition, attitude positively moderates the relationship between picture number and crowdfunding success. These findings show the significance of information description on crowdfunding, providing theoretical and practical guidance for project creators

The Impact of Foreign Direct Investment on Economic Growth: A Case Study in Vietnam 1990 – 2015

Over the past 20 years, the role of FDI in the Vietnamese economy has been important. FDI is one of the essential factors for the domestic economic growth. FDI not only increases the supply of investment capital but also promotes technology transfer, human capital accumulation, which promotes long-term economic growth. This paper employs time series techniques to analyses the effect of the foreign direct investment on economic growth in Viet Nam. The study uses annual data over the period 1990 - 2015. The gross domestic product (GDP) is the dependent variable, and foreign direct investment (FDI), gross fixed capital formation, real exchange rate, real interest rate, and inflation rate are the explanatory variables. Keywords: Gross domestic product, foreign direct investment, gross fixed capital formation

Localization of Continuous Gas Leaks from a Flat-Surface Structure Using an Acoustic Emission Sensor Array

Leak localization is of great importance for pressurized vessels for reasons of safety and maintenance. This paper presents an experimental study using an Acoustic Emission sensor array coupled with a hyperbolic positioning algorithm for continuous leak localization. The study aims to detect continuous CO2 leak from an isotropic flat-surface structure on a pressurized vessel in the Carbon Capture and Storage system. The proposed approach consists of four main stages. In the first stage, empirical mode decomposition is deployed to extract the useful signal from the noise. The second step is concerned with the estimation of the time differences of the sensor array in conjunction with correlation signal processing. The third stage estimates the distance difference between the sensing elements from the measured time differences and wave speed. Finally, a hyperbolic positioning algorithm is used to locate the leak source on the flat-surface structure. Results obtained from experiments on a 100 cm ? 100 cm stainless plate demonstrate that the mean full-scale error in the leak localization is 4.9%