<p>The recent surge in shale gas production led to increases in alkane resources across the United States. One promising approach to convert the alkanes to higher value products is through dehydrogenation and oligomerization processes. This conversion to alkenes, if done in small modular units near the shale wells further aids in the ease of transportation and distribution of the final products. However, having highly selective processes is a major hindrance to improve the economic feasibility of the modular processes. Theoretical studies are of great significance to analyze detailed reaction mechanisms and identify the reaction pathways that leads to unselective product formations. These studies further enable the search for selective catalysts for any given chemistry based on descriptor analysis. Therefore, in this work Density Function Theory and Ab-initio Molecular Dynamics methods are used in conjunction with microkinetic modeling analyses to investigate the complex reaction networks involved in the shale gas conversion. Specifically, the work focuses on propane dehydrogenation (PDH) on alloy surfaces along with ethylene oligomerization on zeolite catalysts.</p><p> A major part of thesis is focused on finding selective and stable alloy catalysts for PDH chemistry. The initial work focused on understanding the selectivity, activity, and stability differences between 1:1 intermetallic alloys (PdIn) and the pure metal surfaces. This combined experimental and computational study shed light on the important role of step surfaces in understanding the activity trends across alloys. Through a detailed microkinetic analysis and simplified rate expression analysis, a novel selectivity descriptor in terms of effective barriers for propane C-H bond breaking and propyne C-C bond breaking was derived for propylene formation. This newly proposed descriptor showed greater fidelity for predicting the trends in experimental selectivities for a small set of Pd alloys than the previously proposed selectivity descriptors. Building upon these insights, a high throughput screening framework using graph-theory algorithms and python-based databasing has been developed to identify trends across a larger set of alloy combinations. The framework helped us identify a novel set of alloys that have not been explored until now for this chemistry. These alloy combinations were then experimentally tested and shown to have high selectivities for propylene formation and along with stabilities close to benchmark Pt-Sn catalysts. Detailed transition state analysis on terraces shows that the undesired C-C bond breaking pathways involves larger surface atom ensembles (4-5 atoms) while the C-H bond breaking involves smaller surface atom ensembles (1-2 atoms). This led to the conclusion that the site-isolation of active metal atoms is important to increase the selectivities for propylene formation. More importantly the combination of detailed mechanistic and screening studies using graph-theory methods shows a generalized framework towards finding new catalysts spaces for complex chemistries.</p><p>The work on ethylene oligomerization on the other hand is focused on understanding the role of mobility of active Ni species in the zeolites towards isomerization and deactivation reaction mechanisms. For this specific project, we have used state-of-the-art AIMD methods, including potential of mean force calculations, for accurate estimation of free energies for the reaction intermediates and transition states. The thermodynamic and kinetic analyses show that the reaction pathways involving mobile intermediates have the highest rates towards butene formations even under pressures lower than 1 bar. Further the isomerization step is found to be feasible on Ni-ethyl complex in agreement with experiments. Finally, the mobile complexes were shown to dimerize through alkyl bridged complexes and the generated complex has higher barriers for C-C bond formation than the isolated complex indicating that these are likely pathways for catalyst deactivation. This mechanistic understanding paves the way for fine-tuning the reaction conditions as well as ways in which the active site can be speciated inside the zeolitic frameworks to increase the selectivity towards 1-butene and reduce deactivation.</p>

Nowadays, the organoids structures has become more popular as suitable model systems for clinical research, particularly for development of new medication and drug screening. The standard study approaches include invazive biochemical or molecular-biology analysis as well as non-invasive optical approaches. Among optical methods, various microscopy techniques can give a very detailed information about the structure of organoids. However, the microscopy is time consuming as well as it puts a great demand on instrumentation. Therefore, the microscopy is not suitable for high content analysis of multiple samples. This work is focused on the development of the device and experimental technique for high-throughput screenings of organoids structures for biomedical applications based on microtitrate plates. Literatre search for non-invasive optical methods, suitable for analysis of organoid structures. The necessary adjustements of existing system for algae phenotypization are discussed. An experiment was made to test functionality of designed system. Practical use for clinical use is tested by the experiment of spheroids reaction to selected cytostatics. The results and findings are discussed in the conclusion.

Drug discovery is a process that takes many years and hundreds of millions of dollars to reveal a confident conclusion about a specific treatment. Part of this sophisticated process is based on preliminary investigations to suggest a set of chemical compounds as candidate drugs for the treatment. Computational resources have been playing a significant role in this part through a step known as virtual screening. From a data mining perspective, availability of rich data resources is key in training prediction models. Yet, the difficulties imposed by big expansion in data and its dimensionality are inevitable. In this thesis, I address the main challenges that come when data mining techniques are used for virtual screening. In order to achieve an efficient virtual screening using data mining, I start by addressing the problem of feature selection and provide analysis of best ways to describe a chemical compound for an enhanced screening performance. High-throughput screening (HTS) assays data used for virtual screening are characterized by a great class imbalance. To handle this problem of class imbalance, I suggest using a novel algorithm called DRAMOTE to narrow down promising candidate chemicals aimed at interaction with specific molecular targets before they are experimentally evaluated. Existing works are mostly proposed for small-scale virtual screening based on making use of few thousands of interactions. Thus, I propose enabling large-scale (or big) virtual screening through learning millions of interaction while exploiting any relevant dependency for a better accuracy. A novel solution called DRABAL that incorporates structure learning of a Bayesian Network as a step to model dependency between the HTS assays, is showed to achieve significant improvements over existing state-of-the-art approaches.

Indiana University-Purdue University Indianapolis (IUPUI) / Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects over 10 million people. Treatments for PD are limited to symptom mitigation with no means of stopping or slowing disease progression. Mutations within the protein leucine- rich repeat kinase 2 (LRRK2) are the most common cause of familial PD and are indistinguishable from the more common sporadic cases. Identifying molecules capable of modulating LRRK2 GTPase activity may serve as the foundation for future development of novel PD therapeutics. We recently discovered that the G-domain (ROC) of LRRK2 is capable of transitioning between monomer and dimer form in solution upon GTP/GDP binding. R1441C/G/H pathogenic mutations were demonstrated to alter this dynamic shifting toward a monomeric ROC conformation while decreasing GTPase activity. Using our ROC dimeric crystal structure, we strategically introduced disulfide bonds to generate locked monomer and locked dimer states. Monomeric ROC was shown to increase GTPase activity while the dimeric form decreased activity. Solvent mapping performed using the dimeric ROC crystal structure and a homology model of the ROC monomer revealed a binding hotspot at the ROC dimeric interface and adjacent to the R1441 residue in the monomeric model. In this study our goal was to identify more compounds capable of influencing GTPase activity. We performed high throughput screening of ROC against two compound libraries (LOPAC1280 and ChemBridge 50K) in a GTP binding assay. Twenty-three hits were identified and four compounds were further investigated in dose-response experiments. 3,4-Methylenedioxy-beta nitrostyrene (MNS) was demonstrated to decrease GTP binding and inhibit GTPase activity (IC50=23.92μM) while the compound N-phenylanthranilic acid increased GTP binding (EC50=4.969μM) and decreased GTPase activity. Identification of these compounds is the first step in the development of a novel PD therapeutic targeting the G-domain of LRRK2.

Immunotherapy is a promising tool in the fight against cancer and aims to recruit patients own immune systems to seek out and destroy malignant cells. Options such as oncolytic viruses (OVs), autologous tumour vaccines and chimeric antigen receptors have shown clinical success to date, yet there remain significant hurdles to overcome. Here, we demonstrate a novel vaccine combining irrCell priming and infected cell boosting dramatically improves the tumour-specific CTL response against CT26 tumours and can be further enhanced using additional immunogenic factors (armed OVs, adjuvants). We also developed a novel fluorescence-based high-throughput screening platform to identify compounds that sensitize resistant solid tumours to killing by CAR-T cells, which ultimately revealed cardiac glycosides as putative tumour sensitizers. Overall, this thesis identifies several novel enhancers of the anticancer immune response, including a heterologous irr:ICV vaccine regimen and the potential ability to identify molecules to overcome resistance to CAR-T therapy.

Indiana University-Purdue University Indianapolis (IUPUI) / The over-accumulation of glycogen appears as a hallmark in various glycogen storage diseases (GSDs), including Pompe, Cori, Andersen, and Lafora disease. Glycogen synthase (GS) is the rate-limiting enzyme for glycogen synthesis. Recent evidence suggests that suppression of glycogen accumulation represents a potential therapeutic approach for treating these diseases. Herein, we describe the discovery, characterization, and development of small molecule inhibitors of GS through a multicomponent study including biochemical, biophysical, and cellular assays. Adopting an affinity-based fluorescence polarization assay, we identified a substituted imidazole molecule (H23), as a first-in-class inhibitor of yeast glycogen synthase 2 (yGsy2) from the 50,000 ChemBridge DIVERSet library. Structural data derived from X-ray crystallography at 2.85 Å, and enzyme kinetic data, revealed that H23 bound within the uridine diphosphate glucose binding pocket of yGsy2. Medicinal chemistry efforts examining over 500 H23 analogs produced structure-activity relationship (SAR) profiles that led to the identification of potent pyrazole and isoflavone compounds with low micromolar potency against human glycogen synthase 1 (hGYS1). Notably, several of the isoflavones demonstrated cellular efficacy toward suppressing glycogen accumulation. In an alternative effort to screen inhibitors directly against human GS, an activity-based assay was designed using a two-step colorimetric approach. This assay led to the identification of compounds with submicromolar potency to hGYS1 from a chemical library comprised of 10,000 compounds. One of the hit molecules, hexachlorophene, was crystallized bound to the active site of yGsy2. The structure was determined to 3.15 Å. Additional kinetic, mutagenic, and SAR studies validated the binding of hexachlorophene in the catalytic pocket and its non-competitive mode of inhibition. In summary, these two novel assays provided feasible biochemical platforms for large-scale screening of small molecule modulators of GS. The newly-developed, potent analogs possess diverse promising scaffolds for drug development efforts targeting GS activity in GSDs associated with excess glycogen accumulation. / 2021-07-01

Myotonic dystrophy type 1 (DM1) is the most common form of adult muscular dystrophy (1:8000) and is caused by an abnormal expansion of CTG repeats in the 3’ untranslated region of the dystrophia myotonica protein kinase (DMPK) gene. The expanded repeats of the DMPK mRNA forms hairpin structures which sequester RNA-binding proteins (RBP) in intranuclear foci, such as the splicing regulator muscleblind-like 1 (MBNL1), which results in aberrant splicing of several mRNAs and underlie, at least in part, DM1 pathogenesis. It has been previously shown that disaggregating these RNA foci repletes free and thus functional MBNL1, rescuing DM1 spliceopathy and alleviating associated signs and symptoms such as myotonia. Importantly, the direct upregulation of MBNL1 has comparable beneficial outcomes. The focus of this thesis was to develop novel and practical therapeutic avenues for DM1 by employing high-throughput screening technology to identify key pathways and small molecule candidates which reduce CUG foci in patient cells, and ultimately correct DM1 spliceopathy and associated signs in vivo. First, a high-throughput kinome screen using an siRNA library targeting 692 kinase subunits identified PACT, HIPK4, and PKA2β as candidates for reducing CUG foci in patient fibroblasts. Knockdown of each gene resulted in a partial reduction in CUG foci, but ultimately did not correct aberrant splicing of insulin receptor (IR) or sarcoplasmic/endoplasmic reticulum Ca2+-ATPase (SERCA1), two genes which are typically misspliced in DM1. A second set of screens focused on testing small molecules, several of which are FDA-approved for clinical use, in an effort to expedite drug discovery. One approach was to data-mine from a previously completed chemical screen, which used system-wide RNA sequencing to establish drug-gene interactions in mouse neuronal cultures treated with blood brain barrier-penetrant drugs, and specifically look for compounds which downregulate DMPK mRNA or upregulate MBNL mRNA (MBNL1 and MBNL2). No compounds were found to downregulate DMPK mRNA. However, several compounds upregulated MBNL mRNAs; the activity of one of these, nilotinib, was validated in human DM1 fibroblasts and converted myoblasts, mediating a small correction in SERCA1 spliceopathy. Administration of nilotinib to unaffected mice did not result in in vivo MBNL gene upregulation in mouse skeletal muscle, as was seen in vitro. Further testing of nilotinib in DM1 in vivo models is required. A final set of chemical screens in patient myoblasts using an FDA-approved drug library and a chemogenomic drug library identified several HDAC inhibitors which reduced foci and rescued SERCA1 spliceopathy in vitro in DM1 differentiated myoblasts. Of these, vorinostat (SAHA) was further tested in a mouse model of DM1 (HSALR), proving safe and effective in correcting aberrant muscle pathology as well as splicing defects of RYR1, SERCA1, and CLCN1. Functional validation, such as myotonia, remains to be completed, but given the strong evidence for CUG foci reduction and splicing correction, vorinostat has emerged as a promising novel candidate for DM1 therapy.

Zusammenfassung Die menschliche Hautoberfläche enthält beträchtliche Mengen unterschiedlicher Lipide. Sie werden entweder in tieferen Hautschichten synthetisiert und wandern im Zuge der Hautdifferenzierung/Desquamation nach oben (stratum corneum lipide), oder entstehen im Inneren von Talgdrüsen und werden auf der Hautoberfläche ausgeschieden. Zusammen kann die Gesamtheit aller Hautoberflächenlipide als Hautlipidom bezeichnet werden. Ein besseres Verständnis der Variabilität von Hautoberflächenlipiden ist aus zweierlei Gründen das Ziel dieser Arbeit. Die erste Motivation ist ein besseres Verständnis der Hautbiologie an sich. Als wichtiger Bestandteil der Epidermis definieren Hautoberflächenlipide bestimmte Aspekte der Hautmikroanatomie und –physiologie und determinieren zentrale Hautparameter. Die zweite Motivation ist die Erlangung der Fähigkeit ein krankes Hautlipidom erkennen zu können. Dazu muss man wissen wie ein gesundes Hautlipidom variieren kann. Die Zusammensetzung des Hautlipidomes unterliegt erheblichen Schwankungen. Lipide sind das Produkt mehrerer komplexer, miteinander verbundener Synthesewege des Stoffwechesl. Als solche können ihre Mengen auf Prozesse im menschlichen Körper reagieren. Lipidschwankungen können besonders ausgeprägt sein, wenn sie im Zuge einer Hautkrankheit, als ethologischer Faktor oder als Folge auftreten, und damit Barriereeigenschaften der Haut beeinflussen. Aber mutmaßlich gibt es auch einen Schwankungsbereich, der als physiologisch einzuordnen wäre. Zur Vermessung der Hautlipidomzusammensetzung und –variabilität haben wir eine Technologie entwickelt und validiert, die der quantitativen, Hochdurchsatz-Shotgun-Massenspektrometire von Tape-stripping Oberhautproben basiert. Sie ermöglicht die Quantifizierung von 16 Lipidklassen bis runter auf Mengen individueller molekularer Lipidspezies, und ist dabei reproduzierbar und hochdurchsatzfähig. Mit dieser Technologie haben wir die bis heute umfangreichste Hautlipidom-Studie unter Einbeziehung von 268 menschlicher Oberhautproben durchgeführt. Wir haben den Zusammenhang zwischen Tiefe der Probenentnahme und der Zusammensetzung der Hautlipide, die Lipidomvariabilität an 14 unterschiedlichen anatomischen Loci, sowie die Populationsvariabilität des Hautlipidoms innerhalb von 104 Probanden untersucht.:The physiological lipidome of human epidermis Contents Abbreviations III Introduction 1 Architecture of the human shell 4 Measuring skin lipid composition 6 Skin sampling 6 Lipid extraction 9 Lipid identification 10 Lipid quantification 14 The design of this study 16 Material and methods 18 Method development and validation 18 Sampling development 18 Establishment of sample extraction and robotic handling 19 Establishment of mass spectrometric lipid identification 20 Establishment of lipid quantification 21 Skin lipidomic study 22 Sampling preparation 22 Standard sampling via tape stripping 23 Sampling via sequential tape-stripping 25 Lipid extraction 25 MS data acquisition 26 Lipid identification and data processing 27 Results 29 Method development and validation 29 Skin sampling via tape-stripping 29 Lipid extraction 31 Lipid identification 31 Lipid quantification 36 Skin lipidomic study results 38 Vertical skin surface lipid profile 38 Anatomical skin surface lipid variability 43 Inter-individual skin surface lipid variability 46 Discussion 50 Method development and validation 50 Skin sampling via tape-stripping 50 Lipid extraction 52 Lipid identification 53 Lipid quantification 55 Physiological lipid composition and variability 56 Lipidome variability vs sampling depth 56 Intra-individual lipidome variability 58 Inter-individual lipidome variability 59 General discussion 61 Conclusions 63 Abstract 66 Zusammenfassung 67 Literature 68 Acknowledgments 81 Anlage 1: Erklärungen zur Eröffnung des Promotionsverfahrens 83 Anlage 2: Gesetzliche Vorgaben 84 / The human skin surface contains considerable amounts of different lipids, both synthesized in deeper skin layers and migrating upwards (stratum corneum lipids), or generated in sebaceous glands and secreted on the skin surface (sebaceous lipids). Jointly the entirety of all skin surface lipids (SSLs) can be referred to as the skin lipidome. The composition of the skin lipidome is known to vary considerably. Lipids are product of several complex synthesis pathways, interconnected with the body’s metabolism. As such, lipid amounts may vary in response to what is happening inside of us. Lipid variations can be most pronounced when occurring in skin disorders, either as etiological cause or as effect, causing altered skin barrier properties. But certainly there is a range of variation in SSL amount which could be described as physiological. Attaining better knowledge of the physiological skin surface lipid variability is the purpose of this work for two main reasons. The first fundamental reason is to better understand skin biology. As major epidermis constituent, SSL composition and variability defines certain aspects of skin microanatomy, physiology and determines crucial skin properties. The second motivation is to acquire the ability to recognize what characterizes a sick skin lipidome. To this end, one must know how much a healthy skin lipidome can vary. To assess skin lipidome composition and variability, we developed and validated a quantitative high-throughput shotgun mass spectrometry-based platform for lipid analysis of tape-stripped stratum corneum (SC) skin samples. It features coverage of 16 lipid classes; total quantification to the level of individual lipid molecules; high reproducibility and high-throughput capabilities. With this method, we conducted the hitherto largest lipidomic survey of 268 human SC samples, where we investigated the relationship between sampling depth and lipid composition, lipidome variability in samples from 14 different sampling sites on the human body and finally, we assessed the impact of age and sex on lipidome variability in 104 healthy subjects.:The physiological lipidome of human epidermis Contents Abbreviations III Introduction 1 Architecture of the human shell 4 Measuring skin lipid composition 6 Skin sampling 6 Lipid extraction 9 Lipid identification 10 Lipid quantification 14 The design of this study 16 Material and methods 18 Method development and validation 18 Sampling development 18 Establishment of sample extraction and robotic handling 19 Establishment of mass spectrometric lipid identification 20 Establishment of lipid quantification 21 Skin lipidomic study 22 Sampling preparation 22 Standard sampling via tape stripping 23 Sampling via sequential tape-stripping 25 Lipid extraction 25 MS data acquisition 26 Lipid identification and data processing 27 Results 29 Method development and validation 29 Skin sampling via tape-stripping 29 Lipid extraction 31 Lipid identification 31 Lipid quantification 36 Skin lipidomic study results 38 Vertical skin surface lipid profile 38 Anatomical skin surface lipid variability 43 Inter-individual skin surface lipid variability 46 Discussion 50 Method development and validation 50 Skin sampling via tape-stripping 50 Lipid extraction 52 Lipid identification 53 Lipid quantification 55 Physiological lipid composition and variability 56 Lipidome variability vs sampling depth 56 Intra-individual lipidome variability 58 Inter-individual lipidome variability 59 General discussion 61 Conclusions 63 Abstract 66 Zusammenfassung 67 Literature 68 Acknowledgments 81 Anlage 1: Erklärungen zur Eröffnung des Promotionsverfahrens 83 Anlage 2: Gesetzliche Vorgaben 84

Cancer immunotherapy is emerging as a powerful tool in the treatment of cancer. Multiple clinical trials have established that infusion of tumour-specific T cells can cause regression of advanced tumours and prevent tumour relapse. While tumour-specific T cells are typically rare, engineering methods have been developed to introduce tumour-specific receptors into T cells and engender peripheral blood T cells with the ability to kill tumour cells. These engineering successes notwithstanding, tumour cells demonstrate variable sensitivity to T cell attack. Therefore, to maximize the impact of the engineered T cells, it is necessary to develop therapeutic strategies that render tumour cells sensitive to immune attack. For my thesis research, I sought to develop a high throughput screening assay that would allow me to screen chemical libraries for agents that sensitize tumour cells to T cell attack. My ultimate goal is to define chemical agents that effectively sensitize tumour cells to T cell attack but display a better toxicity profile than existing chemotherapies. To this end, I developed a screen where resistant tumour cells were exposed to T cells engineered with chimeric antigen receptors and positive hits were defined as agents that could enhance killing of the tumour cells. My work explored both murine and human systems and I ultimately decided to use human cells for my screen. Multiple methods for measuring tumour cell killing were evaluated, many tumour lines were screened and I optimized the conditions for generating large numbers of engineered T cells for the screen. The net result of my thesis work is a miniaturized assay that is ready for high throughput screening. / Thesis / Master of Science in Medical Sciences (MSMS)

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