Using Automation, Theory and Machine Learning to Gain Mechanistic Understanding of Chemical Glycosylation

Carbohydrates are one of the most abundant biomolecules on earth. These molecules range from single monomers such as glucose, measuring 180 Da, that serve as a basic energy source of plants and animals, to hundreds or even thousands of monomers joined together to form gigantic polymeric structures such as cellulose that are a staggering >15 kDa forming the structural backbones of plant cell walls. In addition to providing energy and structure, carbohydrates also serve fundamental biological functions such as cell-cell signaling, cell recognition, and signaling pathways. Extracting carbohydrates from nature is a tedious biochemical and enzymatic process often resulting in mixtures of compounds. The chemical synthesis of carbohydrates provides the opportunity to obtain defined chemical structures to aid in understanding the specific roles, their functional relationships, and advancing the field of carbohydrate research. However, the mechanism behind the formation of the glycosidic bond, and critically the control over the stereoselectivity, is one of the central challenges in organic chemistry dating back to the seminal paper of Fischer in 1893. This bond formation joins two monomers into a disaccharide. Many factors including the temperature, nature of solvent, water content, reaction time, and stoichiometry potentially influence the yield and stereochemical outcome of the reaction. To date no a systematic study of these factors has been pursued. Compounding the problem is the irreproducibility of the reaction, which stems from the sensitivity and lack of control over the reaction conditions. Flow chemistry and automation provides significant promise in control and reproducibility of chemical reactions. Hence, in this thesis, a fully automated flow chemical platform was built for the exhaustive study of glycosylation reactions, systematically interrogating the factors and reaction conditions influencing the yield and stereochemical outcome of glycosylation. The thesis, divided into six chapters, introduces the challenges in understanding the mechanism of glycosylation, before describing the tools utilized to address the challenges, an automated flow chemical platform for studying chemical glycosylation and the development of Random Forest based machine learning model for predicting the stereoselectivity of glycosylation reaction. Chapter 1 introduces the problem of understanding the glycosylation mechanism, the identity of the various factors affecting the selectivity of glycosylation, and the relevant flow chemical approach to obtain greater control over the reaction. Chapter 2 introduces methodologies details and the design of the automated flow platform for interrogating and controlling glycosylations. The detailed application of this machine, along with systematic interrogation of various factors influencing the stereochemical outcome, is described in Chapter 3. This systematic study led to a high degree of stereoselective control of a model glycosylation and allowed for our comprehensive empirical understanding of the glycosylation mechanism. Additionally, for the first time, more than 300 reproducible data points systematically populating the relevant chemical space were generated. This allowed for the application of Random Forest based machine learning algorithm for creating a model capable of predicting the stereoselectivity of glycosylations, described in detail in Chapter 4 of this thesis. The research concluded in Chapter 5 and an outlook on the immediate future work is suggested. All the experimental data described in this thesis is given in Chapter 6.Kohlenhydrate sind die am weitesten verbreiteten Biomoleküle auf der Erde. Diese Moleküle können von einem einzigen Monomer wie Glucose, welche als grundlegende Energiequelle für Pflanzen und Tiere dient, bis hin zu Hunderten oder Tausenden Monomeren reichen, welche riesige Polymerstrukturen wie Zellulose bilden, die das strukturelle Rückenrad der pflanzlichen Zellwand darstellen. Kohlenhydrate sind neben den Funktionen als Energielieferant und Strukturelement auch in grundlegende biologische Funktionen wie zelluläre Signale, Zellerkennung und Signalwege involviert. Die Gewinnung von Kohlenhydraten aus der Natur ist ein langwieriger, komplizierter biochemischer Prozess und führt sehr oft zu einer Mischung von Verbindungen. Die chemische Synthese von Kohlenhydraten bietet die Möglichkeit, eine definierte chemische Struktur von hoher Reinheit zu erhalten, was es ermöglicht, die einzelnen biologischen Funktionsbeziehungen zu verstehen und den Bereich der Kohlenhydratforschung weiter zu entwickeln. Das Kontrollieren der Glykosylierung, der Reaktion die zwei Zuckerbausteine unter Bildung einer glykosidischen Bindung verknüpft, und damit der Stereoselektivität ist eine der Herausforderungen in der modernen organischen Chemie, und basiert auf den bahnbrechenden Erkenntnissen von Emil Fischer im Jahr 1893. Viele Faktoren wie Temperatur, Lösungsmittel, Wassergehalt, Reaktionszeit und Stöchiometrie beeinflussen die Ausbeute der Reaktion und die stereochemische Zusammensetzung des Produkts. Bisher wurden keine umfassenden systematischen Untersuchungen aller dieser Faktoren durchgeführt. Eine große Herausforderung ist die Reproduzierbarkeit der Glykosylierung, die auf die Sensibilität der Reaktion und mangelnde Kontrolle über die Reaktionsbedingungen durch den Experimentator zurückzuführen ist. Durchflusschemie und Automatisierung bieten hier erhebliche Möglichkeiten die Kontrolle und damit die Reproduzierbarkeit chemischer Reaktionen zu optimieren. Daher wurde in dieser Dissertation eine vollautomatische durchflusschemische Plattform für die umfassende Untersuchung von Glykosylierungsreaktionen entwickelt, in der systematisch die Reaktionsbedingungen variiert und deren Einfluss auf Ausbeute und stereochemischen Zusammensetzung des Produkts untersucht werden können. In dieser sechs Kapitel umfassenden Arbeit werden die Herausforderungen beim Verständnis des Glykosylierungsmechanismus vorgestellt, und die zur Bewältigung verwendeten Werkzeuge beschrieben. Dazu gehören die automatisierte durchflusschemische Plattform zur Untersuchung der chemischen Glykosylierung und die Entwicklung eines zufälligen „Random Forest“ basierten Modells für maschinelles Lernen, das der Vorhersage der stereochemischen Zusammensetzung des Produkts dient. Kapitel 1 erörtert die Herausforderungen beim Verständnis des Glykosylierungs-mechanismus, und die verschiedenen Faktoren, die das Ergebnis der Glykosylierung beeinflussen, um damit im durchflusschemischen Ansatz eine größere Kontrolle über die Reaktion erhalten zu können. Kapitel 2 stellt die Methodik und das Design der automatisierten Flow-Plattform für Glykosylierungen vor. Die detaillierte Anwendung dieser Maschine wird in Kapitel 3 beschrieben, zusammen mit systematischen Fragen zu den verschiedenen Faktoren, die die stereochemische Zusammensetzung des Produkts beeinflussen. Durch diese systematische Studie konnte ein sehr hohes Maß an Kontrolle über die Modell-Glykosylierung und ein umfassendes empirisches Verständnis des Reaktionsmechanismus erworben werden. Außerdem wurden zum ersten Mal mehr als 300 reproduzierbare Datenpunkte systematisch im chemischen Raum erstellt. Dies ermöglichte es, mittels einem „Random Forest“ basierten maschinellen Lernalgorithmus ein Modell zu erstellen, das die stereochemische Zusammensetzung des Produkts vorhersagen kann, welches in Kapitel 4 dieser Arbeit detailliert beschrieben wird. Eine Zusammenfassung und ein Ausblick finden sich in Kapitel 5. Alle in dieser Arbeit beschriebenen experimentellen Daten sind in Kapitel 6 aufgeführt

Combining radial and continuous flow synthesis to optimize and scale-up the production of medicines

Current drug production in batch cannot adapt rapidly to market demands, evidenced by recent shortages in many markets globally of essential medicines. Flow chemistry is a valuable tool for on-demand production of active pharmaceutical ingredients (APIs). Here, we reveal a new concept to develop and produce APIs, where an automated synthesizer that works with discrete volumes of solutions is employed at the discovery stage to identify the optimal synthetic route and conditions before a commercially available continuous flow system is used for scale-up. This concept is illustrated by the synthesis of nifedipine and paracetamol, in short supply in Germany during the COVID-19 pandemic, and the local anesthetic lidocaine

Road Dynamic Object Mapping System Based on Edge-Fog-Cloud Computing

Dynamic objects appearing on the road without notice can cause serious accidents. However, the detection ranges of roadside unit and CCTV that collect current road information are very limited. Moreover, there are a lack of systems for managing the collected information. In this study, a dynamic mapping system was implemented using a connected car that collected road environments data continuously. Additionally, edge-fog-cloud computing was applied to efficiently process large amounts of road data. For accurate dynamic mapping, the following steps are proposed: first, the classification and 3D position of road objects are estimated through a stereo camera and GPS data processing, and the coordinates of objects are mapped to a preset grid cell. Second, object information is transmitted in real time to a constructed big data processing platform. Subsequently, the collected information is compared with the grid information of an existing map, and the map is updated. As a result, an accurate dynamic map is created and maintained. In addition, this study verifies that maps can be shared in real time with IoT devices in various network environments, and this can support a safe driving milieu

The Influence of Mortality Focus on Guilt Advertising Effectiveness

The current research examines the influence of mortality focus on the effectiveness of guilt advertising via two experiments. Mortality focus and type of guilt advertising appeal interacted such that directing the focus of mortality on one\u27s own death (versus other) facilitated effectiveness of guilt-lessening (versus guilt-magnifying) appeals. The mediators of the influences were the motivation to boost self-confidence (versus manage impression). The findings offer practical implications for guilt advertising management and contribute to the literature on consumer guilt, mortality salience, and defensive processing

Simulation of A 90o Differential Phase Shifter for Korean VLBI Network 129 GHz Band Polarizer

A simulation for the design of a 90o differential phase shifter aimed toward Korean VLBI Network (KVN) 129 GHz band polarizer is described in this paper. A dual-circular polarizer for KVN 129 GHz band consists of a 90o differential phase shifter and an orthomode transducer. The differential phase shifter is made up of a square waveguide with two opposite walls loaded with corrugations. Three-dimensional electromagnetic simulation has been performed to predict the 90o differential phase shifter’s characteristics. The simulation for the differential phase shifter shows that the phase shift is 90o ± 3.3o across 108-160 GHz and the return losses of two orthogonal modes are better than -30 dB within the design frequency band. According to the simulation results the calculated performance is quite encouraging for KVN 129 GHz band application

Eco-Friendly Photochemical Production of H2O2 through O2 Reduction over Carbon Nitride Frameworks Incorporated with Multiple Hetero-Elements

We report that in situ incorporation of both potassium and phosphate species into a polymeric carbon nitride (CN) framework highly enhanced the photoproduction of hydrogen peroxide (H2O2) without the use of any noble-metal cocatalysts. The incorporation of earth-abundant heteroelements (K, P, and O) (i) introduced the negative surface charge over the entire pH range through surface functionalization by phosphate species, (ii) increased the lifetime of the transient species to a picosecond time scale via the formation of charge separation states, (iii) facilitated the interfacial electron transfer to dioxygen, and (iv) inhibited the decomposition of in situ generated H2O2. As a result, the modified CN showed apparent quantum yields (Φ, for H2O2 production) that are enhanced by about 25 and 17 times (Φ420 = 8.0%; Φ320 = 26.2%) from those of bare CN (Φ420 = 0.32%; Φ320 = 1.55%) under monochromatic irradiation of 420 and 320 nm, respectively. This study clearly demonstrated a simple way to design multiple heteroelement-incorporated CN compounds that consist of earth-abundant elements only (C, N, K, P, O) for the development of practical and economical solar conversion photocatalytic materials.1134sciescopu

Whole-genome sequence of Clostridium lituseburense L74, isolated from the larval gut of the rhinoceros beetle, Trypoxylus dichotomus

Clostridium lituseburense L74 was isolated from the larval gut of the rhinoceros beetle, Trypoxylus dichotomus collected in Yeong-dong, Chuncheongbuk-do, South Korea and subjected to whole genome sequencing on HiSeq platform and annotated on RAST. The nucleotide sequence of this genome was deposited into DDBJ/EMBL/GenBank under the accession NZ_LITJ00000000. Keywords: Insect, Larval gut, Whole genome shot-gun sequencin

Click, Zoom, Explore: Interactive 3D (i-3D) Figures in Standard Manuscript PDFs

While chemistry exists in three-dimensions, it is published in two. This down-conversion results in a significant loss in information and often necessitates multiple images/figures to convey the complexity, intricacy, and beauty of a given structure. Outlined herein is a concise, straightforward method for incorporating interactive three-dimensional (i-3D) figures into manuscript pdfs. These figures can be generated from a variety of sources and allow for structures, molecular orbitals, unit cells and crystal lattices, as well as biopolymers to be published in the same information rich format as they are created and studied on our computers. These images can be seen and interacted with by anyone reading the manuscript in the standard pdf software (Adobe Reader) – and to fully appreciate this article, please read it using Adobe Reader. It is time for chemistry publications to take advantage of the digital age

Manipulation of Structural Colors in Liquid-Crystal Helical Structures Deformed by Surface Controls

Structural colors from cholesteric liquid crystals (CLCs) are manipulated by changing the only surface anchoring energy of an alignment layer. This behavior comes from the fact that weak surface energy of the perfluoropolymer induces the tilting of the cholesteric helix. Such deformed CLC structures with durability are successfully demonstrated without any external field applications and additional solidification processes. In addition, electrical tunings of structural colors from the deformed CLCs occur at very low operating voltages, compared to those of conventional CLC structures. On the basis of easy and simple fabrication, high durability, electrical tunability at low operating voltages, and the unique optical characteristics, the new deformed CLC structure could lead to extension in applications of CLCs, including multifunctional sensors, displays, and lasers

In vitro efficacy of Artemisia extracts against SARS-CoV-2

Background Traditional medicines based on herbal extracts have been proposed as affordable treatments for patients suffering from coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Teas and drinks containing extracts of Artemisia annua and Artemisia afra have been widely used in Africa in efforts to prevent SARS-CoV-2 infection and fight COVID-19. Methods The plant extracts and Covid-Organics drink produced in Madagascar were tested for plaque reduction using both feline coronavirus and SARS-CoV-2 in vitro. Their cytotoxicities were also investigated. Results Several extracts as well as Covid-Organics inhibited SARS-CoV-2 and FCoV infection at concentrations that did not affect cell viability. Conclusions Some plant extracts show inhibitory activity against FCoV and SARS-CoV-2. However, it remains unclear whether peak plasma concentrations in humans can reach levels needed to inhibit viral infection following consumption of teas or Covid-Organics. Clinical studies are required to evaluate the utility of these drinks for COVID-19 prevention or treatment of patients