Quantitative assessment of the expanding complementarity between public and commercial databases of bioactive compounds

<p>Abstract</p> <p>Background</p> <p>Since 2004 public cheminformatic databases and their collective functionality for exploring relationships between compounds, protein sequences, literature and assay data have advanced dramatically. In parallel, commercial sources that extract and curate such relationships from journals and patents have also been expanding. This work updates a previous comparative study of databases chosen because of their bioactive content, availability of downloads and facility to select informative subsets.</p> <p>Results</p> <p>Where they could be calculated, extracted compounds-per-journal article were in the range of 12 to 19 but compound-per-protein counts increased with document numbers. Chemical structure filtration to facilitate standardised comparisons typically reduced source counts by between 5% and 30%. The pair-wise overlaps between 23 databases and subsets were determined, as well as changes between 2006 and 2008. While all compound sets have increased, PubChem has doubled to 14.2 million. The 2008 comparison matrix shows not only overlap but also unique content across all sources. Many of the detailed differences could be attributed to individual strategies for data selection and extraction. While there was a big increase in patent-derived structures entering PubChem since 2006, GVKBIO contains over 0.8 million unique structures from this source. Venn diagrams showed extensive overlap between compounds extracted by independent expert curation from journals by GVKBIO, WOMBAT (both commercial) and BindingDB (public) but each included unique content. In contrast, the approved drug collections from GVKBIO, MDDR (commercial) and DrugBank (public) showed surprisingly low overlap. Aggregating all commercial sources established that while 1 million compounds overlapped with PubChem 1.2 million did not.</p> <p>Conclusion</p> <p>On the basis of chemical structure content <it>per se </it>public sources have covered an increasing proportion of commercial databases over the last two years. However, commercial products included in this study provide links between compounds and information from patents and journals at a larger scale than current public efforts. They also continue to capture a significant proportion of unique content. Our results thus demonstrate not only an encouraging overall expansion of data-supported bioactive chemical space but also that both commercial and public sources are complementary for its exploration.</p

Application of information extraction techniques to pharmacological domain : extracting drug-drug interactions

Una interacción farmacológica ocurre cuando los efectos de un fármaco se modifican por la presencia de otro. Las consecuencias pueden ser perjudiciales si la interacción causa un aumento de la toxicidad del fármaco o la disminución de su efecto, pudiendo provocar incluso la muerte del paciente en los peores casos. Las interacciones farmacológicas no sólo suponen un grave problema para la seguridad del paciente, sino que además también conllevan un importante incremento en el gasto médico. En la actualidad, el personal sanitario tiene a su disposición diversas bases de datos sobre interacciones que permiten evitar posibles interacciones a la hora de prescribir un determinado tratamiento, sin embargo, estas bases de datos no están completas. Por este motivo, médicos y farmacéuticos se ven obligados a revisar una gran cantidad de artículos científicos e informes sobre seguridad de medicamentos para estar al día de todo lo publicado en relación al tema. Desgraciadamente, el gran volumen de información al respecto hace que estos profesionales estén desbordados ante tal avalancha. El desarrollo de métodos automáticos que permitan recopilar, mantener e interpretar toda esta información es crucial a la hora de conseguir una mejora real en la detección temprana de las interacciones entre fármacos. Por tanto, la extracción de información podría reducir el tiempo empleado por el personal médico en la revisión de la literatura médica. Sin embargo, la extracción de interacciones farmacológicas a partir textos biomédicos no ha sido dirigida hasta el momento. Motivados por estos aspectos, en esta tesis hemos realizado un estudio detallado sobre diversas técnicas de extracción de información aplicadas al dominio farmacológico. Basándonos en este estudio, hemos propuesto dos aproximaciones distintas para la extracción de interacciones farmacológicas de los textos. Nuestra primera aproximación propone un enfoque híbrido, que combina análisis sintáctico superficial y la aplicación de patrones léxicos definidos por un farmacéutico. La segunda aproximación se aborda mediante aprendizaje supervisado, concretamente, el uso de métodos kernels. Además, se han desarrollado las siguientes tareas auxiliares: (1) el análisis de los textos utilizando la herramienta UMLS MetaMap Transfer (MMTx), que proporciona información sintáctica y semántica, (2) un proceso para identificar y clasificar los nombres de fármacos que ocurren en los textos, y (3) un proceso para reconoger las expresiones anafóricas que se refieren a fármacos. Un prototipo ha sido desarrollado para integrar y combinar las distintas técnicas propuestas en esta tesis. Para la evaluación de las dos propuestas, con la ayuda de un farmacéutico desarrollamos y anotamos un corpus con interacciones farmacológicas. El corpus DrugDDI es una de las principales aportaciones de la tesis, ya que es el primer corpus en el dominio biomédico anotado con este tipo de información y porque creemos que puede alentar la investigación sobre extracción de información en el dominio farmacológico. Los experimentos realizados demuestran que el enfoque basado en kernels consigue mejores resultados que los reportados por el enfoque que utiliza información sintáctica y patrones léxicos. Además, los kernels consiguen resultados comparables a los obtenidos en dominios similares como son las interacciones entre proteínas. Esta tesis se ha llevado a cabo en el marco del consorcio de investigación MAVIRCM (Mejorando el acceso y visibilidad de la información multilingüe en red para la Comunidad de Madrid, www.mavir.net) dentro del Programa de Actividades de I+D en Tecnologías 2005-2008 de la Comunidad de Madrid (S-0505/TIC-0267) así como en el proyecto de investigación BRAVO: ”Búsqueda de Respuestas Avanzada Multimodal y Multilingüe” (TIN2007-67407-C03-01).----------------------------------------------------------------------------------------A drug-drug interaction occurs when one drug influences the level or activity of another drug. The detection of drug interactions is an important research area in patient safety since these interactions can become very dangerous and increase health care costs. Although there are different databases supporting health care professionals in the detection of drug interactions, this kind of resource is rarely complete. Drug interactions are frequently reported in journals of clinical pharmacology, making medical literature the most effective source for the detection of drug interactions. However, the increasing volume of the literature overwhelms health care professionals trying to keep an up-to-date collection of all reported drug-drug interactions. The development of automatic methods for collecting, maintaining and interpreting this information is crucial for achieving a real improvement in their early detection. Information Extraction (IE) techniques can provide an interesting way of reducing the time spent by health care professionals on reviewing the literature. Nevertheless, no approach has been carried out to extract drug-drug interactions from biomedical texts. In this thesis, we have conducted a detailed study on various IE techniques applied to biomedical domain. Based on this study, we have proposed two different approximations for the extraction of drug-drug interactions from texts. The first approximation proposes a hybrid approach, which combines shallow parsing and pattern matching to extract relations between drugs from biomedical texts. The second approximation is based on a supervised machine learning approach, in particular, kernel methods. In addition, we have created and annotated the first corpus, DrugDDI, annotated with drug-drug interactions, which allow us to evaluate and compare both approximations. To the best of our knowledge, the DrugDDI corpus is the only available corpus annotated for drug-drug interactions and this thesis is the first work which addresses the problem of extracting drug-drug interactions from biomedical texts. We believe the DrugDDI corpus is an important contribution because it could encourage other research groups to research into this problem. We have also defined three auxiliary processes to provide crucial information, which will be used by the aforementioned approximations. These auxiliary tasks are as follows: (1) a process for text analysis based on the UMLS MetaMap Transfer tool (MMTx) to provide shallow syntactic and semantic information from texts, (2) a process for drug name recognition and classification, and (3) a process for drug anaphora resolution. Finally, we have developed a pipeline prototype which integrates the different auxiliary processes. The pipeline architecture allows us to easily integrate these modules with each of the approaches proposed in this thesis: pattern-matching or kernels. Several experiments were performed on the DrugDDI corpus. They show that while the first approximation based on pattern matching achieves low performance, the approach based on kernel-methods achieves a performance comparable to those obtained by approaches which carry out a similar task such as the extraction of protein-protein interactions. This work has been partially supported by the Spanish research projects: MAVIR consortium (S-0505/TIC-0267, www.mavir.net), a network of excellence funded by the Madrid Regional Government and TIN2007-67407-C03-01 (BRAVO: Advanced Multimodal and Multilingual Question Answering)

Cardiovascular effects, molecular docking and chemo informatics analysis of compounds isolated from leonotis leonurus

>Magister Scientiae - MScLeonotis leonurus (L. Leonurus) has relatively abundant diterpenes and has been used as a traditional herbal medicine for treating several ailments including influenza, muscular cramps, skin related diseases, menstrual, antilipidemic, hyperglycaemia and hypertension. In this study, diterpenoid compounds such as; Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9 were isolated from L. Leonurus plant. The cardiovascular effects of these isolated compounds were investigated in order to determine the response of anaesthetised normotensive Wistar rats (in-vivo) to the compounds. Also, the druglikeness of the isolated diterpenoid compounds and their binding interaction with β1 adrenoceptor (PDB: 2Y04), angiotensin II receptor (Ang II) (PDB: 3R8A), Angiotensin converting enzyme (ACE) (PDB: 4XX3), and renin receptor (PDB: 2X8Z) by using molecular docking methods and Chemoinformatics analysis was performed (in-silico). Important molecular descriptors and molecular docking were used in our Chemoinformatics (in-silico) analysis to study the druglikeness and the binding affinity for of each molecule (Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9). The molecular descriptors and the binding energy were calculated by using the molecular operating environment software (MOE 2013). The lowest energy and highest cluster conformations of the molecules were further analysed. All the five (5) diterpenoids were predicted to have good oral bioavailability after oral administration and passed the BloodBrain Barrier (BBB) rules. Also, the compounds were predicted to have high probability of being good Druglike candidates, except for DC9, which is predicted to have lower possibilities of being Druglike candidate than the other diterpenoids. Furthermore, these compounds (Dubiin, SaponifiedDubiin, Hispanol, Marrubiin and DC9) were shown to interact with β1 adrenoceptors in-silico, an interaction that was confirmed in-vivo by increases in Blood pressure (SP, DP and MAP) and Heart rate (HR). In anaesthetized normotensive male Wistar rats (in-vivo), Dubiin (0.5 40mg/kg; IV), SaponifiedDubiin (0.5 60mg/kg; IV) Hispanol (0.5 40mg/kg; IV), DC9 (0.5 40mg/kg; IV) and Marrubiin (0.5 40mg/kg; IV) produced dose dependent increase in Systolic pressure (SP), Diastolic pressure (DP), and Mean arterial pressure (MAP) at all doses. Also, the compounds produced dose dependent increase in Heart rate (HR). From the in-vivo and in-silico studies it can be concluded that all the five (5) isolated diterpenoid compounds showed cardiovascular effects on Blood pressure (BP) and Heart rate (HR) by acting as β1 adrenoceptor agonists. Also, these diterpenoids compounds could be responsible for the cardiovascular effect observed in the methanol extracts from previous studies. These cardioactive compounds are prototype or ''lead compounds'' for designing and developing new nontoxic and effective drugs for cardiovascular disease (CVD) treatment

The desmoplastic response : mechanisms of tumour-induced fibrogenesis

The main concern of this thesis is with desmoplasia - a process in which excessive connective tissue is deposited in a neoplasm. This is a common phenomenon in neoplasia but one whose mechanisms are poorly understood. To study the process, I used a human malignant melanoma cell line (UCT-Mel 7) that was established in this laboratory and that, when injected into athymic mice, gave rise to tumours that showed a number of interesting features. Firstly, the tumour induced a marked desmoplastic response as evidenced by a high content of hydroxyproline in tumour lysates, intense staining for reticulin in sections of the tumour and infiltration of the tumour by host mesenchymal cells. Secondly, the desmoplasia was associated in UCT-Mel 7-derived tumours with an unusual phasic pattern of growth that was related to the in vitro passage number of the melanoma cells. On occasions, murine tumours developed at the site of inoculation of human tumour cells. I have identified 2 possible mechanisms by which UCT-Mel 7 cells could have induced the desmoplastic response: either the tumour cells could have exerted their effect indirectly, i.e. via macrophages, or they could have stimulated the host's stromal cells directly. UCT-Mel 7 cells were shown to be chemotactic for mouse macrophages and human foreskin fibroblasts were stimulated, in a dose-dependent manner, to synthesize increased amounts of collagen when co-cultured with mouse peritoneal exudate cells. Stimulation could only be effected by direct cell:cell contact; medium conditioned by macrophages was not effective. The amount of stimulation was not dependent on the state of activation of the peritoneal cells nor on the strain of mouse used. Tumour cells were also found to act directly. Co-culture of UCT-Mel 7 cells and fibroblasts resulted in increased collagen synthesis by the fibroblasts. Increased synthesis of the protein was reflected in an increase in the amount of collagen mRNA. UCT-Mel 7 cell stimulated in a dose-dependent manner with an absolute requirement for intimate cell:cell contact with the fibroblasts. DNA synthesis was not required. Dexamethasone, retinoic acid and the tumour promoter, phorbol myristate acetate, had significant primary effects on fibroblast collagen synthesis but did not modify the response to melanoma cells. Indomethacin, however, had a minimal primary effect upon the fibroblasts but significantly augmented the melanoma cell effect. The nature of the stimulatory cell:cell contact is still uncertain. The gap junction inhibitor, α-glycyrrhetinic acid, did not diminish the melanoma cell effect. Preliminary findings suggested that cell-surface proteoglycans may be important. Removal of the proteoglycans with the inhibitor of proteoglycan assembly, 4-methylumbelliferyl-β-D-xyloside, abrogated the melanoma cell:fibroblast interaction. Recombinant basic fibroblast growth factor did. not seem to be involved in the desmoplastic response. It was of incidental interest to note that this compound inhibited fibroblast collagen synthesis in a manner that was augmented by the concomitant addition of heparin. A surprising finding was the production of a potent inhibitor of collagen synthesis by superinduced cells of the mouse macrophage cell line, P388D₁. This inhibitor has not been fully characterised

The classification of gene products in the molecular biology domain: Realism, objectivity, and the limitations of the Gene Ontology

Background: Controlled vocabularies in the molecular biology domain exist to facilitate data integration across database resources. One such tool is the Gene Ontology (GO), a classification designed to act as a universal index for gene products from any species. The Gene Ontology is used extensively in annotating gene products and analysing gene expression data, yet very little research exists from a library and information science perspective exploring the design principles, philosophy and social role of ontologies in biology. Aim: To explore how molecular biologists, in creating the Gene Ontology, devised guidelines and rules for determining which scientific concepts are included in the ontology, and the criteria for how these concepts are represented. Methods: A domain analysis approach was used to devise a mixed methodology to study the design of the Gene Ontology. Concept analysis of a GO term and a critical discourse analysis of GO developer mailing list texts were used to test whether ontological realism is a tenable basis for constructing objective ontologies. A comparison of the current GO vocabulary construction guidelines and a study of the reasons why GO terms are removed from the ontology further explored the justifications for the design of the Gene Ontology. Finally, a content analysis of published GO papers examined how authors use and cite GO data and terminology. Results: Gene Ontology terms can be presented according to different epistemologies for concepts, indicating that ontological realism is not the only way objective ontologies can be designed. Social roles and the exercise of power were found to play an important role in determining ontology content, and poor synonym control, a lack of clear warrant for deciding terminology and arbitrary decisions to delete and invent new terms undermine the objectivity and universal applicability of the Gene Ontology. Authors exhibited poor compliance with GO data citation policies, and in re-wording and misquoting GO terminology, risk exacerbating the semantic problems this controlled vocabulary was designed to solve. Conclusions: The failure of the Gene Ontology to define what is meant by a molecular function, the exercise of power by GO developers in clearing contentious concepts from the ontology, and the strict adherence to ontological realism, which marginalises social and subjective ways of classifying scientific concepts, limits the utility of the ontology as a tool to unify the molecular biology domain. These limitations to the Gene Ontology design could be overcome with the development of lighter, pluralistic, user-controlled ‘open ontologies’ for gene products that can work alongside more traditional, ‘top-down’ developed vocabularies

Phytochemical Investigation and Bioactivity Assessment of Medicinal Plant from Northern Nigeria

Boswellia dalzielii (Burseraceae) has ethnopharmacological importance and is claimed to have anti-infection and immunomodulatory effects. In the Northern part of Nigeria, a region with a tropical dry climate, an aqueous infusion of this plant is used in the treatment of infections and tumours. The traditional formulation method was mimicked under laboratory conditions, and the effect of temperature and the impact of endophytic microbes present in aqueous infusion of B. dalzielii was also investigated. Activity-guided fractionation against Staphylococcus aureus and its methicillin-resistant strain resulted in the identification of two antibacterial compounds namely gallic acid and pyrogallol. The Minimum Inhibitory Concentration for pyrogallol and gallic acid against S. aureus growth are 508 and 753 μM, while against MRSA growth are 254 and 2032 μM, respectively. A growth Inhibition assay showed the activity of gallic acid as bacteriostatic, and pyrogallol as bacteriocidal against tested microorganisms. Interestingly, the bacteriocidal compound was found to arise by conversion of gallic acid by the endophyte Enterobacter cloacae. In addition, Pantoea spp was also isolated from the bark of B. Dalzielii. The sequences of both E. cloacae and Pantoea spp are deposited in the GenBank nucleotide database under the accession number MH764584 and MH764583, respectively. Similarly, activity-guided fractionation of B. Dalzielii bark against breast cancer cell line (MCF7) using MTT cytotoxicity assay resulted in the identification of a cytotoxic compound, catechol, and the half maximal effective concentration (EC50) observed was 86μM. The growth inhibition effect of catechol was observed to be time- and concentration- dependent. Endophytic Klebsiella pneumonia species (strain A and B) were shown to be responsible for bioconversion of protocatechuic acid to catechol. In addition, Pantoea agglomerans was also isolated from the bark of B. dalzielii. The sequences of Klebsiella pneumonia A, Klebsiella pneumonia B and Pantoea agglomerans are deposited in the GenBank nucleotide database under the accession number MH762022, MH762023 and MH762024, respectively. All isolated compounds were identified using HPLC, TLC, NMR, FTIR and HRMS.TETFUN

Network Pharmacology Approaches for Understanding Traditional Chinese Medicine

Traditional Chinese medicine (TCM) has obvious efficacy on disease treatments and is a valuable source for novel drug discovery. However, the underlying mechanism of the pharmacological effects of TCM remains unknown because TCM is a complex system with multiple herbs and ingredients coming together as a prescription. Therefore, it is urgent to apply computational tools to TCM to understand the underlying mechanism of TCM theories at the molecular level and use advanced network algorithms to explore potential effective ingredients and illustrate the principles of TCM in system biological aspects. In this thesis, we aim to understand the underlying mechanism of actions in complex TCM systems at the molecular level by bioinformatics and computational tools. In study Ⅰ, a machine learning framework was developed to predict the meridians of the herbs and ingredients. Finally, we achieved high accuracy of the meridians prediction for herbs and ingredients, suggesting an association between meridians and the molecular features of ingredients and herbs, especially the most important features for machine learning models. Secondly, we proposed a novel network approach to study the TCM formulae by quantifying the degree of interactions of pairwise herb pairs in study Ⅱ using five network distance methods, including the closest, shortest, central, kernel, as well as separation. We demonstrated that the distance of top herb pairs is shorter than that of random herb pairs, suggesting a strong interaction in the human interactome. In addition, center methods at the ingredient level outperformed the other methods. It hints to us that the central ingredients play an important role in the herbs. Thirdly, we explored the associations between herbs or ingredients and their important biological characteristics in study III, such as properties, meridians, structures, or targets via clusters from community analysis of the multipartite network. We found that herbal medicines among the same clusters tend to be more similar in the properties, meridians. Similarly, ingredients from the same cluster are more similar in structure and protein target. In summary, this thesis intends to build a bridge between the TCM system and modern medicinal systems using computational tools, including the machine learning model for meridian theory, network modelling for TCM formulae, as well as multipartite network analysis for herbal medicines and their ingredients. We demonstrated that applying novel computational approaches on the integrated high-throughput omics would provide insights for TCM and accelerate the novel drug discovery as well as repurposing from TCM.Perinteinen kiinalainen lääketiede (TCM) on ilmeinen tehokkuus taudin hoidoissa ja on arvokas lähde uuden lääkkeen löytämiseen. TCM: n farmakologisten vaikutusten taustalla oleva mekanismi pysyy kuitenkin tuntemattomassa, koska TCM on monimutkainen järjestelmä, jossa on useita yrttejä ja ainesosia, jotka tulevat yhteen reseptilääkkeeksi. Siksi on kiireellistä soveltaa Laskennallisia työkaluja TCM: lle ymmärtämään TCM-teorioiden taustalla oleva mekanismi molekyylitasolla ja käyttävät kehittyneitä verkkoalgoritmeja tutkimaan mahdollisia tehokkaita ainesosia ja havainnollistavat TCM: n periaatteita järjestelmän biologisissa näkökohdissa. Tässä opinnäytetyössä pyrimme ymmärtämään monimutkaisten TCM-järjestelmien toimintamekanismia molekyylitasolla bioinformaattilla ja laskennallisilla työkaluilla. Tutkimuksessa kehitettiin koneen oppimiskehystä yrttien ja ainesosien meridialaisista. Lopuksi saavutimme korkean tarkkuuden meridiaaneista yrtteistä ja ainesosista, mikä viittaa meridiaaneihin ja ainesosien ja yrtteihin liittyvien molekyylipiirin välillä, erityisesti koneen oppimismalleihin tärkeimmät ominaisuudet. Toiseksi ehdoimme uuden verkon lähestymistavan TCM-kaavojen tutkimiseksi kvantitoimisella vuorovaikutteisten yrttiparien vuorovaikutuksen tutkimuksessa ⅱ käyttämällä viisi verkkoetäisyyttä, mukaan lukien lähin, lyhyt, keskus, ydin sekä erottaminen. Osoitimme, että ylä-yrttiparien etäisyys on lyhyempi kuin satunnaisten yrttiparien, mikä viittaa voimakkaaseen vuorovaikutukseen ihmisellä vuorovaikutteisesti. Lisäksi Center-menetelmät ainesosan tasolla ylittivät muut menetelmät. Se vihjeitä meille, että keskeiset ainesosat ovat tärkeässä asemassa yrtteissä. Kolmanneksi tutkimme yrttien tai ainesosien välisiä yhdistyksiä ja niiden tärkeitä biologisia ominaisuuksia tutkimuksessa III, kuten ominaisuudet, meridiaanit, rakenteet tai tavoitteet klustereiden kautta moniparite-verkoston yhteisön analyysistä. Löysimme, että kasviperäiset lääkkeet samoilla klusterien keskuudessa ovat yleensä samankaltaisia ominaisuuksissa, meridiaaneissa. Samoin saman klusterin ainesosat ovat samankaltaisempia rakenteissa ja proteiinin tavoitteessa. Yhteenvetona tämä opinnäytetyö aikoo rakentaa silta TCM-järjestelmän ja nykyaikaisten lääkevalmisteiden välillä laskentatyökaluilla, mukaan lukien Meridian-teorian koneen oppimismalli, TCM-kaavojen verkkomallinnus sekä kasviperäiset lääkkeet ja niiden ainesosat Osoitimme, että uusien laskennallisten lähestymistapojen soveltaminen integroidulle korkean suorituskyvyttömiehille tarjosivat TCM: n näkemyksiä ja nopeuttaisivat romaanin huumeiden löytöä sekä toistuvat TCM: stä

The asymmetric synthesis of decalin synthons for use in flavour and fragrance compounds

In the pursuit of synthons for the preparation of the secondary metabolites geosmin and dehydrogeosmin, four synthetic strategies were evaluated. To support this study, the preparation of a chiral auxiliary and new surfactant media were also investigated: Techniques for the production of laboratory scale quantities of the enantiomeric forms of butan-2,3-diol were identified: The bacterial fermentation of sugars by Bacillus subtilis strains to access optically pure D-(-)-(2R,3R)-butandiol and the kinetic enzymatic resolution of a commercially available isomeric mixture of the diol to recover the L-(+)-(2S,3S)-isomer in optically pure form. Two optically pure amino acid derived surfactants were synthesised, characterised and a measurement of their critical micellar concentration undertaken. A novel strategy to construct the dehydrogeosmin skeleton was designed, employing a 'biomimetic' intramolecular polyene cyclisation as the key step. The preparation of the trans olefinic cyclisation precursor was investigated and metal facilitated carbonylation was used to generate a requisite aldehydic intermediate. The biomimetic cyclisation was tested and generated the predicted bicyclic octalin ether in a chemical yield and an enantiomeric excess of 22% and >99% respectively. The novel Diels-Alder disconnection of geosmin was investigated, through the preparation of several diene systems and testing their reactivity in the [4π+2π] cycloaddition reaction. A similar disconnection was applied to the dehydrogeosmin system and optically pure ketals of butan-2,3-diol used in lithium perchlorate solution to generate a precursor in 70% enantiomeric excess. A study of the Hajos-Parrish reaction - an amino acid catalysed intramolecular cyclisation - was undertaken to evaluate the effects of solvent and amino acid choice on enantioselectivity. Conditions were identified to form the target bicyclic ketone intermediate in a chemical yield of 72% and an enantiomeric excess of 74%. The formation of the cyclisation precursor, from the Michael addition of 2- methylcyclohexane-1,3-dione to ethyl vinyl ketone, was found to be greatly enhanced by performing the reaction in micellar media with a yield of >99% in surfactant solution compared to 55% in water. The use of surfactant solutions in studies of Robinson annelations was also undertaken. The enantioselective dehydration of a decalol, using an optically pure amino acid as a catalytic dehydrator, was carried out to prepare a key geosmin precursor in a chemical yield and an enantiomeric excess of >99% and 54% respectively. As part of the study into the effect of solvent and amino acid choice on selectivity, new insights into the mechanism of action of the Hajos-Parrish reaction were gained

Design, synthesis and structural characterisation of inhibitors of 1-Deoxy-D-xylulose-5-phosphate Synthase

Due to the emergence of pathogenic organisms with resistance to classical antibiotics, the developmemt of new drugs is needed. The enzyme 1-deoxy-D-xylulose-5-phosphate synthase (DXPS) is a potential target for such a new antibiotic. DXPS is the first enzyme of the methylerythritol phosphate (MEP) pathway, one of two known pathways for the biosynthesis of essential terpene building-blocks. It is found in many bacteria and plants, whereas most other organisms, especially mammals, use the mevalonate pathway. Inhibition of the MEP pathway is therefore one way to impare the growth and survival of microorganisms. The focus of this thesis is the protein structure of DXPS and the identification and development of DXPS inhibitors. In Chapter 1.2 an overview of the enzyme and the metabolic pathway is given, Chapter 1.3 updates on developments since 2017. Chapter 1.4 introduces our general workflow for protein-templated dynamic combinatorial chemistry (ptDCC). The main part describes in Chapters 2.1 and 2.2 protein crystallographic work to improve the resolution of D. radiodurans DXPS and structural elucidation of DXPS homologous from pathogenic species. In parallel, the hit-identification strategies ligandbased virtual screening (Chapter 2.3) and ptDCC (Chapter 2.4) were applied to find DXPS inhibitors. Finally, Chapter 2.5 describes the development and crystallographic validation of bioisosters for acylhydrazone-based ptDCC hits.Aufgrund der Zunahme von antibiotika-resistenten Pathogenen ist die Entwicklung neuer Antibiotika erforderlich. Das Enzym 1-Desoxy-D-xylulose-5-phosphat-Synthase (DXPS) ist ein potenzielles Ziel für eine solche Neuentwicklung. DXPS ist das erste Enzym des Methylerythritolphosphat (MEP)-Weges, einer von zwei Stoffwechselwegen für die Biosynthese der essentiellen Terpen bausteine. Er kommt in vielen Bakterien und Pflanzen vor, wohingegen die meisten anderen Organismen, insbesondere Säugetiere, den Mevalonatweg nutzen. Die Hemmung des MEP-Weges ist daher eine Möglichkeit, das Wachstum und Überleben von Mikroorganismen gezielt zu beeinträchtigen. Der Schwerpunkt dieser Arbeit liegt auf der Proteinstruktur von DXPS sowie der Identifizierung und Entwicklung von DXPS-Inhibitoren. Zunächst wird ein Überblick über das Enzym, den MEP-Weg und den aktuellen Forschungsstand seit 2017 gegeben (Kapitel 1.2 und 1.3). Das Protokoll unserer Arbeitsgruppe für protein-templierte dynamische kombinatorische Chemie (ptDCC) wird anschließend in Kapitel 1.4 vorgestellt. Der Hauptteil beschriebt in den Kapiteln 2.1 und 2.2 proteinkristallographische Arbeiten zur Verbesserung der Auflösung von D. radiodurans DXPS sowie zur Strukturaufklärung von DXPS-homologen von Pathogenen. Parallel dazu wurden die Hit-identifikations- Strategien ligandenbasiertes virtuelles Screening (Kapitel 2.3) und ptDCC (Kapitel 2.4) angewandt, um DXPS-Inhibitoren zu finden. Abschließend wird in Kapitel 2.5 die Entwicklung und kristallographische Validierung von Bioisosteren für Acylhydrazon-basierte ptDCC-Hits beschrieben.LIFT gran