42 research outputs found
Quantum/classical simulation of molecular excited state dynamics and spectroscopy
The ability of modern quantum chemistry to answer ever more complex questions rises steadily. In this thesis, a comprehensive exploration of molecular photochemistry using high-level electronic structure methods for quantum-classical dynamics is presented.
The first chapter introduces theoretical methods for simulating photodynamical processes, focussing on the relaxation of molecules in explicit atomistic environments. These approaches include nuclear wavepacket dynamics embedded within classical molecular dynamics. The presented Ehrenfest and multi-configurational Ehrenfest approaches are applied to small molecules surrounded by noble gas atoms. Furthermore, trajectory surface hopping is discussed, as, in later chapters, the program SHARC is used to perform such simulations. During this thesis, adaptive time-stepping and two new interfaces to electronic structure codes were implemented. These methods facilitate efficient and accurate dynamics calculations on a variety of photochemically relevant systems ranging from simulations in the gas phase with high-level XMS-CASPT2 electronic structure (including spin-orbit couplings) to QM/MM simulations in the condensed phase.
The second chapter focuses on the energy transfer between an infrared laser and solvated molecules, combining the traditional harmonic approximation to calculate infrared spectra with methods based on \textit{ab initio} molecular dynamics. This methodology is used to elucidate the coherent energy transfer dynamics from the field to the molecule in field-resolved spectroscopic measurements.
The third chapter of this thesis surveys the intricate world of 2-enone photochemistry. By exploring and reactivity using high-level electronic structure methods, insights are gained into the \textit{Z}/\textit{E} isomerization of cyclohept-2-enone and the photoinduced rearrangement of 5,5-dimethylcyclopent-2-enone to a ketene.
In the final chapter, mechanistic investigations are extended to Lewis acid\hyp coordinated enones, uncovering the impact of coordination on the electronic states, UV-Vis spectra, and reactivity. Trajectory surface hopping calculations are used in combination with ultrafast transient absorption spectroscopy to uncover the dynamics of the relaxation of cyclohex-2-enone-BF to the reactive triplet states and the photo-induced B\textendash Cl bond dissociation in benzaldehyde-BCl.
Collectively, this work exemplifies the potent synergy of computational and spectroscopic techniques in unraveling photochemical mechanisms. From explicit solvent relaxation to multi-step organic reactions and from spectroscopic signatures to intricate electronic transitions, this thesis advances our understanding of photochemical processes across a spectrum of molecular examples. The findings have implications for the design and understanding of photochemical reactions and spectroscopic studies in complex environments
Sublinear-Time Cellular Automata and Connections to Complexity Theory
Im Gebiet des verteilten Rechnens werden Modelle untersucht, in denen sich mehrere Berechnungseinheiten koordinieren, um zusammen ein gemeinsames Ziel zu erreichen, wobei sie aber nur über begrenzte Ressourcen verfügen — sei diese Zeit-, Platz- oder Kommunikationskapazitäten. Das Hauptuntersuchungsobjekt dieser Dissertation ist das wohl einfachste solche Modell überhaupt: (eindimensionale) Zellularautomaten. Unser Ziel ist es, einen besseren Überblick über die Fähigkeiten und Einschränkungen des Modells und ihrer Varianten zu erlangen in dem Fall, dass die gesamte Bearbeitungszeit deutlich kleiner als die Größe der Eingabe ist (d. h. Sublinear-Zeit). Wir führen unsere Analyse von dem Standpunkt der Komplexitätstheorie und stellen dabei auch Bezüge zwischen Zellularautomaten und anderen Gebieten wie verteiltes Rechnen und Streaming-Algorithmen her.
Sublinear-Zeit Zellularautomaten. Ein Zellularautomat (ZA) besteht aus identischen Zellen, die entlang einer Linie aneinandergereiht sind. Jede Zelle ist im Wesentlichen eine sehr primitive Berechnungseinheit (nämlich ein deterministischer endlicher Automat), die mit deren beiden Nachbarn interagieren kann. Die Berechnung entsteht durch die Aktualisierung der Zustände der Zellen gemäß derselben Zustandsüberführungsfunktion, die gleichzeitig überall im Automaten angewendet wird. Die von uns betrachteten Varianten sind unter anderem schrumpfende ZAs, die (gewissermaßen) dynamisch rekonfigurierbar sind, sowie eine probabilistische Variante, in der jede Zelle mit Zugriff auf eine faire Münze ausgestattet ist. Trotz überragendem Interesse an Linear- und Real-Zeit-ZAs scheint der Fall von Sublinear-Zeit im Großen und Ganzen von der wissenschaftlichen Gemeinschaft vernachlässigt worden zu sein. Wir arbeiten die überschaubare Anzahl an Vorarbeiten zu dem Thema auf, die vorhanden ist, und entwickeln die daraus stammenden Techniken weiter, sodass deren Spektrum an Anwendungsmöglichkeiten wesentlich breiter wird. Durch diese Bemühungen entsteht unter anderem ein Zeithierarchiesatz für das deterministische Modell. Außerdem übertragen wir Techniken zum Beweis unterer Schranken aus der Komplexitätstheorie auf das Modell der schrumpfenden ZAs und entwickeln neue Techniken, die auf probabilistische Sublinear-Zeit-ZAs zugeschnitten sind.
Ein Bezug zu Härte-Magnifizierung. Ein Bezug zu Komplexitätstheorie, die wir im Laufe unserer Untersuchungen herstellen, ist ein Satz über Härte-Magnifizierung (engl. hardness magnification) für schrumpfende ZAs. Hier bezieht sich Härte-Magnifizierung auf eine Reihe neuerer Arbeiten, die bezeugen, dass selbst geringfügig nicht-triviale untere Schranken sehr beeindruckende Konsequenzen in der Komplexitätstheorie haben können. Unser Satz ist eine Abwandlung eines neuen Ergebnisses von McKay, Murray und Williams (STOC, 2019) für Streaming-Algorithmen. Wie wir zeigen kann die Aussage dabei genauso in Bezug auf schrumpfende ZAs formuliert werden, was sie auch beweisbar verstärkt.
Eine Verbindung zu Sliding-Window Algorithmen. Wir verknüpfen das verteilte Zellularautomatenmodell mit dem sequenziellen Streaming-Algorithmen-Modell. Wie wir zeigen, können (gewisse Varianten von) ZAs von Streaming-Algorithmen simuliert werden, die bestimmten Lokalitätseinschränkungen unterliegen. Konkret ist der aktuelle Zustand des Algorithmus vollkommen bestimmt durch den Inhalt eines Fensters fester Größe, das wenige letzte Symbole enthält, die vom Algorithmus verarbeitet worden sind. Dementsprechend nennen wir diese eingeschränkte Form eines Streaming-Algorithmus einen Sliding-Window-Algorithmus. Wir zeigen, dass Sliding-Window-Algorithmen ZAs sehr effizient simulieren können und insbesondere in einer solchen Art und Weise, dass deren Platzkomplexität eng mit der Zeitkomplexität des simulierten ZA verbunden ist.
Derandomisierungsergebnisse. Wir zeigen Derandomisierungsergebnisse für das Modell von Sliding-Window-Algorithmen, die Zufall aus einer binären Zufallsquelle beziehen. Dazu stützen wir uns auf die robuste Maschinerie von Branching-Programmen, die den gängigen Ansatz zur Derandomisierung von Platz-beschränkten Maschinen in der Komplexitätstheorie darstellen. Als eine Anwendung stellen sich Derandomisierungsergebnisse für probabilistische Sublinear-Zeit-ZAs heraus, die durch die oben genannten Verknüpfung erlangt werden.
Vorhersageproblem für Pilz-Sandhaufen. Ein letztes Problem, das wir behandeln und das auch einen Bezug zu Sublinear-Zeitkomplexität im Rahmen von Zellularautomaten hat (obwohl nicht zu Sublinear-Zeit-Zellularautomaten selber), ist das Vorhersageproblem für Sandhaufen-Zellularautomaten. Diese Automaten sind basierend auf zweidimensionalen ZAs definiert und modellieren einen deterministischen Prozess, in dem sich Partikel (in der Regel denkt man an Sandkörnern) durch den Raum verbreiten. Das Vorhersageproblem fragt ob, gegeben eine Zellennummer und eine initiale Konfiguration für den Sandhaufen, die Zelle mit Nummer irgendwann vor einer gewissen Zeitschranke einen von Null verschiedenen Zustand erreichen wird. Die Komplexität dieses mindestens zwei Jahrzehnte alten Vorhersageproblems ist für zweidimensionelle Sandhaufen bemerkenswerterweise nach wie vor offen. Wir lösen diese Frage im Wesentlichen für eine neue Variante von Sandhaufen namens Pilz-Sandhaufen, die von Goles u. a. (Phys. Lett. A, 2020) vorgeschlagen worden ist. Unser Ergebnis ist besonders relevant, weil es innovative Erkenntnisse und neue Techniken liefert, die für die Lösung des offenen Problems im allgemeinen Fall von hoher Relevanz sein könnten
Ionic Conductive Membranes for Fuel Cells
This book, titled “Ionic Conductive Membranes for Fuel Cells”, from the journal Membranes, discusses the state of the art and future developments in the field of polymer electrolyte membranes for fuel cells, an efficient and clean system for converting fuel into energy
Remanufacturing and Advanced Machining Processes for New Materials and Components
"Remanufacturing and Advanced Machining Processes for Materials and Components presents current and emerging techniques for machining of new materials and restoration of components, as well as surface engineering methods aimed at prolonging the life of industrial systems. It examines contemporary machining processes for new materials, methods of protection and restoration of components, and smart machining processes.
• Details a variety of advanced machining processes, new materials joining techniques, and methods to increase machining accuracy
• Presents innovative methods for protection and restoration of components primarily from the perspective of remanufacturing and protective surface engineering
• Discusses smart machining processes, including computer-integrated manufacturing and rapid prototyping, and smart materials
• Provides a comprehensive summary of state-of-the-art in every section and a description of manufacturing methods
• Describes the applications in recovery and enhancing purposes and identifies contemporary trends in industrial practice, emphasizing resource savings and performance prolongation for components and engineering systems
The book is aimed at a range of readers, including graduate-level students, researchers, and engineers in mechanical, materials, and manufacturing engineering, especially those focused on resource savings, renovation, and failure prevention of components in engineering systems.
Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics
This book is a collection of original research articles in the field of computer-aided drug design. It reports the use of current and validated computational approaches applied to drug discovery as well as the development of new computational tools to identify new and more potent drugs
In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs
Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies
Sanakielet ja lokaalisuus
In this master's thesis we study the generalization of word languages into multi-dimensional arrays of letters i.e picture languages. Our main interest is the class of recognizable picture languages which has many properties in common with the robust class of regular word languages. After surveying the basic properties of picture languages, we present a logical characterization of recognizable picture languages—a generalization of Büchi's theorem of word languages into pictures, namely that the class of recognizable picture languages is the one recognized by existential monadic second-order logic. The proof presented is a recent one that makes the relation between tilings and logic clear in the proof. By way of the proof we also study the locality of the model theory of picture structures through logical locality obtained by normalization of EMSO on those structures.
A continuing theme in the work is also to compare automata and recognizability between word and picture languages. In the fourth section we briefly look at topics related to computativity and computational complexity of recognizable picture languages
In silico identification and assessment of novel allosteric protein binding sites to expand the “druggable” human proteome
Ph. D. Thesis.Throughout the last years there has been a considerable number of drugs that
were discovered thanks to computer aided drug design (CADD) techniques.
Using the 3D information, such as protein structures obtained by X-ray
crystallography or nuclear magnetic resonance (NMR), it is possible to identify
the binding sites and to design molecules that may specifically target these sites.
This approach saves a lot of time and money, as the lead search is more
accurate: less compounds need to be synthesised and tested. Although a great
number of proteins have been successfully targeted with this structure-based
approach, there are a lot of disease-linked proteins that have been considered
“undruggable” by conventional structure-based techniques. This is mainly due to
failure in detection of potential binding sites, which precludes the structure-guided
design of suitable ligands.
There is the presumption that the “druggable” human proteome may be larger
than previously expected. Protein structures may present multiple binding sites
(allosteric and/or cryptic) that cannot be targeted by the means of conventional
CADD techniques. In the past years, several novel methods have been
developed to identify and/or unveil these binding hotspots. Amongst them
cosolvent Molecular Dynamics (MD) simulations are increasingly popular
techniques developed for prediction and characterisation of allosteric and cryptic
binding sites, which can be rendered “druggable” by small molecule ligands.
Despite their conceptual simplicity and effectiveness, the analysis of cosolvent
MD trajectories relies on pocket volume data, which requires a high level of
manual investigation and may introduce a bias. The present study focused on the
development of the novel cosolvent analysis toolkit (denoted as CAT), as an
open-source, freely accessible analytical tool, suitable for automated analysis of
cosolvent MD trajectories. CAT is compatible with popular molecular graphics
software packages such as UCSF Chimera and VMD. Using a novel hybrid
empirical force field scoring function, CAT accurately ranked the dynamic
interactions between the macromolecular target and cosolvent molecular probes.
Alongside the development of CAT, this work investigated the signal transducer
activator of transcription 3 (STAT3) as the case study. STAT3 is among the most
investigated oncogenic transcription factors, as it is highly associated with cancer
initiation, progression, metastasis, chemoresistance, and immune evasion.
Constitutive activation of STAT3 by mutations occurs frequently in tumour cells,
and directly contributes to many malignant phenotypes. The evidence from both
preclinical and clinical studies have demonstrated that STAT3 plays a critical role
in several malignancies associated with poor prognosis such as glioblastoma and
triple-negative breast cancer (TNBC), and STAT3 inhibitors have shown efficacy
in inhibiting cancer growth and metastasis. Unfortunately, detailed structural
biology studies on STAT3 as well as target-based drug discovery efforts have
been hampered by difficulties in the expression and purification of the full length
STAT3 and a lack of ligand-bound crystal structures. Considering these,
computational methods offer an attractive strategy for the assessment of
“druggability” of STAT3 dimers and allow investigations of reported activating and
inhibiting STAT3 mutants at the atomistic level of detail. This work studied effects
exerted by reported STAT3 mutations on the protein structure, dynamics, DNA
binding and dimerisation, thus linking structure, dynamics, energetics, and the
biological function. By employing a combination of equilibrium molecular
dynamics (MD) and umbrella sampling (US) simulations to a series of human
STAT3 dimers, which comprised wild-type protein and four mutations; the work
presented herein explains the modulation of STAT3 activity by these mutations.
The binding sites were mapped by the combination of MD simulations, molecular
docking, and CAT analysis, and the binding mode of a clinical candidate
napabucasin/BBI-608 at STAT3, which resembles the effect of D570K mutation,
has been characterised.
Collectively the results of this study demonstrate the robustness of the newly
developed CAT methodology and its applicability in computational studies aiming
at identification of protein “hotspots” in a wide range of protein targets, including
the challenging ones. This work contributes to understanding the
activation/inhibition mechanism of STAT3, and it explains the molecular
mechanism of STAT3 inhibition by BBI-608. Alongside the characterisation of the
BBI-608 binding mode, a novel binding site amenable to bind small molecule
v
ligands has been discovered in this work, which may pave the way to design
novel STAT3 inhibitors and to suggest new strategies for pharmacological
intervention to combat cancers associated with poor prognosis. It is expected that
the results presented in this dissertation will contribute to an increase of the size
of the potentially “druggable” human proteome