Towards Efficient Novel Materials Discovery

Die Entdeckung von neuen Materialien mit speziellen funktionalen Eigenschaften ist eins der wichtigsten Ziele in den Materialwissenschaften. Das Screening des strukturellen und chemischen Phasenraums nach potentiellen neuen Materialkandidaten wird häufig durch den Einsatz von Hochdurchsatzmethoden erleichtert. Schnelle und genaue Berechnungen sind eins der Hauptwerkzeuge solcher Screenings, deren erster Schritt oft Geometrierelaxationen sind. In Teil I dieser Arbeit wird eine neue Methode der eingeschränkten Geometrierelaxation vorgestellt, welche die perfekte Symmetrie des Kristalls erhält, Resourcen spart sowie Relaxationen von metastabilen Phasen und Systemen mit lokalen Symmetrien und Verzerrungen erlaubt. Neben der Verbesserung solcher Berechnungen um den Materialraum schneller zu durchleuchten ist auch eine bessere Nutzung vorhandener Daten ein wichtiger Pfeiler zur Beschleunigung der Entdeckung neuer Materialien. Obwohl schon viele verschiedene Datenbanken für computerbasierte Materialdaten existieren ist die Nutzbarkeit abhängig von der Darstellung dieser Daten. Hier untersuchen wir inwiefern semantische Technologien und Graphdarstellungen die Annotation von Daten verbessern können. Verschiedene Ontologien und Wissensgraphen werden entwickelt anhand derer die semantische Darstellung von Kristallstrukturen, Materialeigenschaften sowie experimentellen Ergebenissen im Gebiet der heterogenen Katalyse ermöglicht werden. Wir diskutieren, wie der Ansatz Ontologien und Wissensgraphen zu separieren, zusammenbricht wenn neues Wissen mit künstlicher Intelligenz involviert ist. Eine Zwischenebene wird als Lösung vorgeschlagen. Die Ontologien bilden das Hintergrundwissen, welches als Grundlage von zukünftigen autonomen Agenten verwendet werden kann. Zusammenfassend ist es noch ein langer Weg bis Materialdaten für Maschinen verständlich gemacht werden können, so das der direkte Nutzen semantischer Technologien nach aktuellem Stand in den Materialwissenschaften sehr limitiert ist.The discovery of novel materials with specific functional properties is one of the highest goals in materials science. Screening the structural and chemical space for potential new material candidates is often facilitated by high-throughput methods. Fast and still precise computations are a main tool for such screenings and often start with a geometry relaxation to find the nearest low-energy configuration relative to the input structure. In part I of this work, a new constrained geometry relaxation is presented which maintains the perfect symmetry of a crystal, saves time and resources as well as enables relaxations of meta-stable phases and systems with local symmetries or distortions. Apart from improving such computations for a quicker screening of the materials space, better usage of existing data is another pillar that can accelerate novel materials discovery. While many different databases exists that make computational results accessible, their usability depends largely on how the data is presented. We here investigate how semantic technologies and graph representations can improve data annotation. A number of different ontologies and knowledge graphs are developed enabling the semantic representation of crystal structures, materials properties as well experimental results in the field of heterogeneous catalysis. We discuss the breakdown of the knowledge-graph approach when knowledge is created using artificial intelligence and propose an intermediate information layer. The underlying ontologies can provide background knowledge for possible autonomous intelligent agents in the future. We conclude that making materials science data understandable to machines is still a long way to go and the usefulness of semantic technologies in the domain of materials science is at the moment very limited

Structure, Electronic Structure and Electronic Spectra of Simple Materials at High Pressure

Under extreme conditions such as temperature and pressure, the chemical bonding, electronic structures and properties of materials undergo significant changes that leads to the discovery of new and unusual chemical species not obtainable at ambient conditions. Hence, chemical bonding plays a significant role in the description of systems in physics, solid state chemistry, material science etc. This makes the study and immense understanding of the structure and chemical bonding of solids significant and constitutes one of the main objectives of this thesis. The second part of this thesis employed state-of-the-art ab initio molecular dynamics simulation to reconstruct the phase transition in elemental Cs. Also, the Bethe-Salpeter Equation (BSE) was used to calculate the X-ray Absorption Spectra (XAS) and Non-Resonant Inelastic X-ray Scattering (NRIXS) spectra of crystalline ice Ih and compressed water. In the first project, the structure and bonding analysis of K2Ag and K3Ag intermetallics were studied at 4.0GPa and 6.4GPa respectively by employing all available bonding analysis methods. Analysis of the K2Ag reveal the K atom transfers electrons to the Ag atom and forms K-K, K-Ag and Ag-Ag closed shell interactions with the K-Ag being the strongest bond interaction present in the compound. Contrary to the K2Ag, topological analysis of the K3Ag yielded no Ag-Ag bond interaction. This is due to the very large bond length of the first nearest neighbour Ag-Ag interaction. All the plane wave and localized basis set dependent bond analysis methods employed gave consistent results. However, the projected density of state (PDOS) computed using the localized basis set method implemented in the LOBSTER code should always be checked against the PDOS calculated using a plane wave method before validating the crystal orbital overlap population (COOP) and crystal orbital Hamiltonian population (COHP) results from the LOBSTER code. In summary, the results from this study show that, all the bonding analysis techniques should be carefully applied when treating high pressure systems, due to the extensive modification of the electron density on application of pressure. Hence, a naive localized description is not appropriate and may lead to erroneous interpretation. The second project focused on the analysis of bonding in the three phases of Na-Au intermetallics following the benchmark established in the first project. Analysis of the phase I Na2Au structure at 0.83GPa revealed the presence of non-nuclear maximum (NNM) in the structure commonly known as electrides. The obtained NNMs were found to form off the Na atoms in agreement with the experimental maximum entropy method (MEM) analysis. The experimental structure of the Phase II Na3Au intermetallics was found to have either a trigonal Cu3As or hexagonal Cu3P-type structure. The two structures could not be distinguished from experiment and DFT equations of state. However, through topological analysis of both structures, only the tetragonal structure does satisfy the Morse sum and is thus said to be the accurate phase II structure as it is topologically stable. Further analysis of the topologically stable phase II structure at 2GPa and the phase III Na3Au at 51.7GPa yielded no NNMs. This implies the Na-Au intermetallics are stabilized by decreased localization of electrons at the interstitial sites at high pressure, contrary to elemental alkali metals that show increased localization of interstitial electrons at high pressure. Finally, Bader's quantum theory of atoms in molecule (QTAIM) revealed all the bond interactions present in the structures are closed shell interactions. The third project reconstructs the phase transition paths of elemental Cs around the complex Cs-III in other to define the transition mechanism. In addition, topological properties of the Cs-II, Cs-III and Cs-IV structures were examined and the result show electrides in the three phases. The molecular dynamics results reveal the transition in the Cs-III to Cs-IV and Cs-II to Cs-III transformations are typical crystalline solid-solid transitions with no evidence of melting in the transition states. In addition, the transformation mechanism observed in the Cs-III to Cs-IV is not martensitic ( i.e a transformation that occurs through a diffusionless cooperative motion of all the atoms in a transformation region) rather it occurs through nucleation and growth. The Cs-II to Cs-III transformation on the other hand was found to occur through a cooperative motion of all the atoms in the super cell. Also, the results suggest existence of a very large activation barrier for the reverse transformation to Cs-II from a backward (i.e Cs-III to Cs-II) transition. In the final project, BSE method was employed to calculate the XAS and NRIXS of crystalline ice Ih and compressed water at different momentum transfer values. Theoretical spectra computed using snapshots from the PICMD simulation performed here yield results in good agreement with experiment for both water and ice Ih. Further analysis of the trajectories revealed the water maintain approximate tetrahedral coordination and not dramatically different from crystalline ice. In addition, the results show dense water form interpenetrating hydrogen bonds by compressing the second nearest neighbour water molecules into the first coordination shell similar to the behaviour of high density ice

Improving Simulations of Aqueous Systems through Experimental Bias

In order to enhance the ab initio molecular dynamics treatment of aqueous systems, the Boltzmann inversion directed simulation method was developed that derives a corrective bias to the system pairwise potential using experimental data. The bias acts as an empirical correction that enables routine-level simulation of density functional theory water to achieve comparable liquid structure to experiment at ambient temperature without significantly increasing computational cost

Cell-free expression and molecular modeling of the γ-secretase complex and G-protein-coupled receptors

Alzheimer’s disease (AD), which was first reported more than a century ago by Alhzeimer, is one of the commonest forms of dementia which affects >30 million people globally (>8 million in Europe). The origin and pathogenesis of AD is poorly understood and there is no cure available for the disease. AD is characterized by the accumulation of senile plaques composed of amyloid beta peptides (Ab 37-43) which is formed by the gamma secretase (GS) complex by cleaving amyloid precursor protein. Therefore GS can be an attractive drug target. Since GS processes several other substrates like Notch, CD44 and Cadherins, nonspecific inhibition of GS has many side effects. Due to the lack of crystal structure of GS, which is attributed to the extreme difficulties in purifying it, molecular modeling can be useful to understand its architecture. So far only low resolution cryoEM structures of the complex has been solved which only provides a rough structure of the complex at low 12-15 A resolution Furthermore the activity of GS in vitro can be achieved by means of cell-free (CF) expression. GS comprises catalytic subunits namely presenilins and supporting elements containing Pen-2, Aph-1 and Nicastrin. The origin of AD is hidden in the regulated intramembrnae proteolysis (RIP) which is involved in various physiological processes and also in leukemia. So far growth factors, cytokines, receptors, viral proteins, cell adhesion proteins, signal peptides and GS has been shown to undergo RIP. During RIP, the target proteins undergo extracellular shredding and intramembrane proteolysis. This thesis is based on molecular modeling, molecular dynamics (MD) simulations, cell-free (CF) expression, mass spectrometry, NMR, crystallization, activity assay etc of the components of GS complex and G-protein coupled receptors (GPCRs). First I validated the NMR structure of PS1 CTF in detergent micelles and lipid bilayers using coarse-grained MD simulations using MARTINI forcefield implemented in Gromacs. CTF was simulated in DPC micelles, DPPC and DLPC lipid bilayer. Starting from random configuration of detergent and lipids, micelle and lipid bilyer were formed respectively in presence of CTF and it was oriented properly to the micelle and bilyer during the simulation. Around DPC molecules formed micelle around CTF in agreement of the experimental results in which 80-85 DPC molecules are required to form micelles. The structure obtained in DPC was similar to that of NMR structure but differed in bilayer simulations showed the possibility of substrate docking in the conserved PAL motif. Simulations of CTF in implicit membrane (IMM1) in CHAMM yielded similar structure to that from coarse grained MD. I performed cell-free expression optimization, crystallization and NMR spectroscopy of Pen-2 in various detergent micelles. Additionally Pen-2 was modeled by a combination of rosetta membrane ab-initio method, HHPred distant homology modeling and incorporating NMR constraints. The models were validated by all atom and coarse grained MD simulations both in detergent micelles and POPC/DPPC lipid bilayers using MARTINI forcefield. GS operon consisting of all four subunits was co-expressed in CF and purified. The presence of of GS subunits after pull-down with Aph-1 was determined by western blotting (Pen-2) and mass spectrometry (Presenilin-1 and Aph-1). I also studied interactions of especially PS1 CTF, APP and NTF by docking and MD. I also made models and interfaces of Pen-2 with PS1 NTF and checked their stability by MD simulations and compared with experimental results. The goal is to model the interfaces between GS subunits using molecular modeling approaches based on available experimental data like cross-linking, mutations and NMR structure of C-terminal fragment of PS1 and transmembrane part of APP. The obtained interfaces of GS subunits may explain its catalysis mechanism which can be exploited for novel lead design. Due to lack of crystal/NMR structure of the GS subunits except the PS1 CTF, it is not possible to predict the effect of mutations in terms of APP cleavage. So I also developed a sequence based approach based on machine learning using support vector machine to predict the effect of PS1 CTF L383 mutations in terms of Aβ40/Aβ42 ratio with 88% accuracy. Mutational data derived from the Molgen database of Presenilin 1 mutations was using for training. GPCRs (also called 7TM receptors) form a large superfamily of membrane proteins, which can be activated by small molecules, lipids, hormones, peptides, light, pain, taste and smell etc. Although 50% of the drugs in market target GPCRs , only few are targeted therapeutically. Such wide range of targets is due to involvement of GPCRs in signaling pathways related to many diseases i.e. dementia (like Alzheimer's disease), metabolic (like diabetes) including endocrinological disorders, immunological including viral infections, cardiovascular, inflammatory, senses disorders, pain and cancer. Cannabinoid and adrenergic receptors belong to the class A (similar to rhodopsin) GPCRs. Docking of agonists and antagonists to CB1 and CB2 cannabinoid receptors revealed the importance of a centrally located rotamer toggle switch, and its possible role in the mechanism of agonist/antagonist recognition. The switch is composed of two residues, F3.36 and W6.48, located on opposite transmembrane helices TM3 and TM6 in the central part of the membranous domain of cannabinoid receptors. The CB1 and CB2 receptor models were constructed based on the adenosine A2A receptor template. The two best scored conformations of each receptor were used for the docking procedure. In all poses (ligand-receptor conformations) characterized by the lowest ligand-receptor intermolecular energy and free energy of binding the ligand type matched the state of the rotamer toggle switch: antagonists maintained an inactive state of the switch, whereas agonists changed it. In case of agonists of β2AR, the (R,R) and (S,S) stereoisomers of fenoterol, the molecular dynamics simulations provided evidence of different binding modes while preserving the same average position of ligands in the binding site. The (S,S) isomer was much more labile in the binding site and only one stable hydrogen bond was created. Such dynamical binding modes may also be valid for ligands of cannabinoid receptors because of the hydrophobic nature of their ligand-receptor interactions. However, only very long molecular dynamics simulations could verify the validity of such binding modes and how they affect the process of activation. Human N-formyl peptide receptors (FPRs) are G protein-coupled receptors (GPCRs) involved in many physiological processes, including host defense against bacterial infection and resolving inflammation. The three human FPRs (FPR1, FPR2 and FPR3) share significant sequence homology and perform their action via coupling to Gi protein. Activation of FPRs induces a variety of responses, which are dependent on the agonist, cell type, receptor subtype, and also species involved. FPRs are expressed mainly by phagocytic leukocytes. Together, these receptors bind a large number of structurally diverse groups of agonistic ligands, including N-formyl and nonformyl peptides of different composition, that chemoattract and activate phagocytes. For example, N-formyl-Met-Leu-Phe (fMLF), an FPR1 agonist, activates human phagocyte inflammatory responses, such as intracellular calcium mobilization, production of cytokines, generation of reactive oxygen species, and chemotaxis. This ligand can efficiently activate the major bactericidal neutrophil functions and it was one of the first characterized bacterial chemotactic peptides. Whereas fMLF is by far the most frequently used chemotactic peptide in studies of neutrophil functions, atomistic descriptions for fMLF-FPR1 binding mode are still scarce mainly because of the absence of a crystal structure of this receptor. Elucidating the binding modes may contribute to designing novel and more efficient non-peptide FPR1 drug candidates. Molecular modeling of FPR1, on the other hand, can provide an efficient way to reveal details of ligand binding and activation of the receptor. However, recent modelings of FPRs were confined only to bovine rhodopsin as a template. To locate specific ligand-receptor interactions based on a more appropriate template than rhodopsin we generated the homology models of FPR1 using the crystal structure of the chemokine receptor CXCR4, which shares over 30% sequence identity with FPR1 and is located in the same γ branch of phylogenetic tree of GPCRs (rhodopsin is located in α branch). Docking and model refinement procedures were pursued afterward. Finally, 40 ns full-atom MD simulations were conducted for the Apo form as well as for complexes of fMLF (agonist) and tBocMLF (antagonist) with FPR1 in the membrane. Based on locations of the N- and C-termini of the ligand the FPR1 extracellular pocket can be divided into two zones, namely, the anchor and activation regions. The formylated M1 residue of fMLF bound to the activation region led to a series of conformational changes of conserved residues. Internal water molecules participating in extended hydrogen bond networks were found to play a crucial role in transmitting the agonist-receptor interactions. A mechanism of initial steps of the activation concurrent with ligand binding is proposed. I accurately predicted the structure and ligand binding pose of dopamine receptor 3 (RMSD to the crystal structure: 2.13 Å) and chemokine receptor 4 (CXCR4, RMSD to the crystal structure 3.21 Å) in GPCR-Dock 2010 competition. The homology model of the dopamine receptor 3 was 8 th best overall in the competition

Property screening of porous organic molecules

Porous organic molecules have internal pores readily occupied by gases, solvent or other guests. These molecules can form porous molecular materials with possible application in storage and separation. In this thesis, the properties of isolated porous organic molecules are used as a proxy to the bulk or in-solution applications. As a result, software was first developed for the automated and precise structural characterisation of porous organic molecules. This allows one to easily calculate window diameters to study the thermal window size fluctuations and predict guest diffusion in the bulk. A screening of previously reported porous organic molecules for the application of Xe/Kr separation allowed the most promising material, Noria, to be identified. This was possible with a combination of molecular modelling, electronic structure calculations and structural analysis using the developed software. The experimental Xe/Kr selectivity of Noria, not previously considered for this application, was shown to be comparable with the best performing porous materials. Next, eight synthetically realised porous organic cages were studied as possible C60 fullerene encapsulants. The relative orientation of the C60 fullerene in the pore was shown to have little to no effect on the binding energy and the encapsulation of the C60 during cage formation was determined as the likely mechanism of encapsulation. Lastly, a function-led material design approach was developed. An evolutionary algorithm was used to generate possible C60 encapsulants from a database of precursors. The resulting porous organic cages are structurally similar to some recently synthetically realised cages and some found in the literature. In summary, presented in this thesis is software, a methodology and results that can further advance the computational function-led materials discovery for specific applications.Open Acces

Intelligent based Packet Scheduling Scheme using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Technology for 5G. Design and Investigation of Bandwidth Management Technique for Service-Aware Traffic Engineering using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) for 5G

Multi-Protocol Label Switching (MPLS) makes use of traffic engineering (TE) techniques and a variety of protocols to establish pre-determined highly efficient routes in Wide Area Network (WAN). Unlike IP networks in which routing decision has to be made through header analysis on a hop-by-hop basis, MPLS makes use of a short bit sequence that indicates the forwarding equivalence class (FEC) of a packet and utilises a predefined routing table to handle packets of a specific FEC type. Thus header analysis of packets is not required, resulting in lower latency. In addition, packets of similar characteristics can be routed in a consistent manner. For example, packets carrying real-time information can be routed to low latency paths across the networks. Thus the key success to MPLS is to efficiently control and distribute the bandwidth available between applications across the networks. A lot of research effort on bandwidth management in MPLS networks has already been devoted in the past. However, with the imminent roll out of 5G, MPLS is seen as a key technology for mobile backhaul. To cope with the 5G demands of rich, context aware and multimedia-based user applications, more efficient bandwidth management solutions need to be derived. This thesis focuses on the design of bandwidth management algorithms, more specifically QoS scheduling, in MPLS network for 5G mobile backhaul. The aim is to ensure the reliability and the speed of packet transfer across the network. As 5G is expected to greatly improve the user experience with innovative and high quality services, users’ perceived quality of service (QoS) needs to be taken into account when deriving such bandwidth management solutions. QoS expectation from users are often subjective and vague. Thus this thesis proposes the use of fuzzy logic based solution to provide service aware and user-centric bandwidth management in order to satisfy requirements imposed by the network and users. Unfortunately, the disadvantage of fuzzy logic is scalability since dependable fuzzy rules and membership functions increase when the complexity of being modelled increases. To resolve this issue, this thesis proposes the use of neuro-fuzzy to solicit interpretable IF-THEN rules.The algorithms are implemented and tested through NS2 and Matlab simulations. The performance of the algorithms are evaluated and compared with other conventional algorithms in terms of average throughput, delay, reliability, cost, packet loss ratio, and utilization rate. Simulation results show that the neuro-fuzzy based algorithm perform better than fuzzy and other conventional packet scheduling algorithms using IP and IP over MPLS technologies.Tertiary Education Trust Fund (TETFUND

La dynamique structurale de l'acétylcholinestérase: étude réalisée par cristallographie aux rayons X et une méthode spectroscopique complémentaire.

This work aimed at watching acetylcholinesterase (AChE) 'at work'. AChE is a very rapid enzyme and terminates the transmission of the nervous influx at cholinergic synapses. Conformational substates of Torpedo californica (Tc) AChE were trapped in x-ray crystallography structures of the enzyme in complex with putative anti-Alzheimer drugs. Structures of both nonaged and aged conjugates of TcAChE and soman were solved, which allowed to shed light on the mechanism of aging in organophosphate (OP) - inhibited AChE. The structure of the ternary complex of the nonaged conjugate and a reactivator was solved. All those structures will help designing new AChE-targeted drugs (anti-Alzheimer drugs or antidotes against OP poisoning) by taking into account flexibility and minor conformations of the enzyme. The structure of TcAChE in complex with the peripheral site (PAS) inhibitor aflatoxin B1 was solved in two crystal forms. This work revealed crystallography artifacts that should be avoided for correct biological interpretation. Measurement of the phosphorescence lifetime of AB1 allowed probing PAS dynamics on the timescale of seconds, thereby highlighting differential flexibility in two distinct crystal packing environments of TcAChE. This spectroscopic method is proposed as a complementary tool for kinetic crystallography experiments. An optimal cryogenic temperature range was identified, which could help exploring the reaction mechanisms of AChE by slowing down the enzyme motions without freezing them.L'objectif de la thèse était de regarder l'acétylcholinestérase (AChE) en mouvement. L'AChE est une enzyme très rapide qui met fin à la transmission de l'influx nerveux au sein des synapses cholinergiques. À l'aide de la cristallographie aux rayons X, des sous-états conformationnels de l'AChE de Torpedo californica (Tc) ont été piégés par sa liaison à des drogues anti-Alzheimer putatives. Les formes, non vieillie et vieillie, de la TcAChE conjuguée au soman ont été caractérisées structuralement, éclairant ainsi le mécanisme de vieillissement de la TcAChE inhibée par les organophosphorés (OP). La structure du complexe ternaire du conjugué vieilli avec un réactivateur a également été résolue. Toutes ces structures guideront l'élaboration de médicaments (drogues anti-Alzheimer ou antidotes contre l'empoisonnement par des OP) en prenant en compte la flexibilité de l'enzyme et ses conformations minoritaires. La structure du complexe de la TcAChE avec un inhibiteur de son site périphérique (PAS), l'aflatoxine B1 (AB1), a été résolue dans deux formes cristallines. Ce travail a mis en évidence des artefacts de la cristallographie nuisibles à l'interprétation biologique des structures. La mesure du temps de vie de phosphorescence de l'AB1 a permis de sonder les mouvements du PAS à l'échelle de la seconde et de révéler des différences de flexibilité liées à l'empilement cristallin de la TcAChE. Cette méthode spectroscopique est complémentaire à la cristallographie cinétique. La gamme de températures cryogéniques identifiée pourrait en effet faciliter l'exploration du mécanisme réactionnel de l'AChE, en ralentissant l'enzyme sans pour autant la figer

Functionally Relevant Macromolecular Interactions of Disordered Proteins

Disordered proteins are relatively recent newcomers in protein science. They were first described in detail by Wright and Dyson, in their J. Mol. Biol. paper in 1999. First, it was generally thought for more than a decade that disordered proteins or disordered parts of proteins have different amino acid compositions than folded proteins, and various prediction methods were developed based on this principle. These methods were suitable for distinguishing between the disordered (unstructured) and structured proteins known at that time. In addition, they could predict the site where a folded protein binds to the disordered part of a protein, shaping the latter into a well-defined 3D structure. Recently, however, evidence has emerged for a new type of disordered protein family whose members can undergo coupled folding and binding without the involvement of any folded proteins. Instead, they interact with each other, stabilizing their structure via “mutual synergistic folding” and, surprisingly, they exhibit the same residue composition as the folded protein. Increasingly more examples have been found where disordered proteins interact with non-protein macromolecules, adding to the already large variety of protein–protein interactions. There is also a very new phenomenon when proteins are involved in phase separation, which can represent a weak but functionally important macromolecular interaction. These phenomena are presented and discussed in the chapters of this book

Natural variation in heat tolerance of corals on the Great Barrier Reef

Josephine Nielsen investigated patterns of acute heat tolerance in corals along the Great Barrier Reef. She found that differential acute heat tolerance was driven by coral host transcriptomics, symbiont community, and thermal disturbance history. Her thesis has direct implications for conservation management of corals under continued climate change