Deskriptives Metadatenprofil für RADAR

Eine zentrale Aufgabe im RADAR-Projekt ist die Erstellung eines Metadatenprofils, das sowohl einen interdisziplinären, zentralen Nachweis der in RADAR archivierten und publizierten Forschungsdaten erlaubt als auch die fachspezifischen Anforderungen zur Suche und zur Nachnutzung dieser Daten erfüllt. Dazu wurden geeignete generische Metadatenparameter, die disziplinspezifisch angepasst werden können identifiziert und ausgewählt. Das nachfolgende Metadatenprofil umfasst 9 Pflichtfelder, welche zusammen den allgemeinen, deskriptiven Teil des Profils darstellen, sowie 12 optionale Felder, welche auch die fachspezifischen Beschreibungen der Datensätze abbilden. Die Pflichtfelder des entwickelten Metadatenprofils enthalten die Grundanforderungen für eine DOI-Registrierung nach dem DataCite-Metadatenschema v 3.11. Um die heterogenen Ansprüche verschiedener wissenschaftlicher Fachgebiete und die generische Ausrichtung von RADAR zusammenzubringen wurde bei der Definition der 12 optionalen Metadatenfelder mit einer Kombination von kontrollierten Listen und Freitextfeldern gearbeitet. Bei der Definition der kontrollierten Listen wurde auf weltweit anerkannte, verständliche Standards (z.B. ISONormen für die Sprache und das Entstehungsland der Forschungsdaten) zurückgegriffen. Dieses Metadatenprofil soll, in Verbindung mit exemplarischen Beispielen den Wissenschaftlern der jeweiligen Fachgebiete darlegen, wie eine detaillierte Beschreibung eines Datensatzes aussehen kann

Flavonoids and a neolignan glucoside from Guarea macrophylla (Meliaceae)

This work describes the phytochemical study of the methanol extract obtained from leaves of Guarea macrophylla, leading to the isolation and identification of three flavonoid glycosides (quercetin 3-O-β-D-glucopyranoside, quercetin 3-O-b-D-galactopyranoside, kaempferol 7-O-β-D-glucopyranoside) and a neolignan glucoside, dehydrodiconiferyl alcohol-4-β-D-glucoside. All compounds were identified by a combination of spectroscopic methods (¹H, 1D, 2D NMR, 13C and UV), ESI-MS and comparison with the literature data. This is the first report of flavonoids in the genus Guarea and of a neolignan glucoside in the Meliaceae family

Isolation of a New Natural Product and Cytotoxic and Antimicrobial Activities of Extracts from Fungi of Indonesian Marine Habitats

In the search for bioactive compounds, 11 fungal strains were isolated from Indonesian marine habitats. Ethyl acetate extracts of their culture broth were tested for cytotoxic activity against a urinary bladder carcinoma cell line and for antifungal and antibacterial activities against fish and human pathogenic bacteria as well as against plant and human pathogenic fungi. The crude extract of a sterile algicolous fungus (KT31), isolated from the red seaweed Kappaphycus alvarezii (Doty) Doty ex P.C. Silva exhibited potent cytotoxic activity with an IC50 value of 1.5 μg/mL. Another fungal strain (KT29) displayed fungicidal properties against the plant pathogenic fungus Cladosporium cucumerinum Ell. et Arth. at 50 μg/spot. 2-Carboxy-8-methoxy-naphthalene-1-ol (1) could be isolated as a new natural product

Elucidation of the biosynthesis of carnosic acid and its reconstitution in yeast

Rosemary extracts containing the phenolic diterpenes carnosic acid and its derivative carnosol are approved food additives used in an increasingly wide range of products to enhance shelf-life, thanks to their high anti-oxidant activity. We describe here the elucidation of the complete biosynthetic pathway of carnosic acid and its reconstitution in yeast cells. Cytochrome P450 oxygenases (CYP76AH22-24) from Rosmarinus officinalis and Salvia fruticosa already characterized as ferruginol synthases are also able to produce 11-hydroxyferruginol. Modelling-based mutagenesis of three amino acids in the related ferruginol synthase (CYP76AH1) from S. miltiorrhiza is sufficient to convert it to a 11-hydroxyferruginol synthase (HFS). The three sequential C20 oxidations for the conversion of 11-hydroxyferruginol to carnosic acid are catalysed by the related CYP76AK6-8. The availability of the genes for the biosynthesis of carnosic acid opens opportunities for the metabolic engineering of phenolic diterpenes, a class of compounds with potent anti-oxidant, anti-inflammatory and anti-tumour activities

Duplicate detection of 2D-NMR Spectra

2D-Nuclear magnetic resonance (NMR) spectra are used in the (structural) analysis of small molecules. In contrast to 1D-NMR spectra, 2D-NMR spectra correlate the chemical shifts of 1H and 13C at the same time. A spectrum consists of several peaks in a two--dimensional space. The most important information of a peak is the location of its center, which captures the bonding relationships of hydrogen and carbon atoms. A spectrum contains much information about the chemical structure of a product, but in most cases the structure cannot be read off in a simple and straightforward manner. Structure elucidation involves a considerable amount (manual) efforts

An Evaluation of Text Retrieval Methods for Similarity Search of multi-dimensional NMR-Spectra

Searching and mining nuclear magnetic resonance (NMR)-spectra of naturally occurring substances is an important task to investigate new potentially useful chemical compounds. Multidimensional NMR-spectra are relational objects like documents, but consists of continuous multi-dimensional points called peaks instead of words. We develop several mappings from continuous NMR-spectra to discrete text-like data. With the help of those mappings any text retrieval method can be applied. We evaluate the performance of two retrieval methods, namely the standard vector space model and probabilistic latent semantic indexing (PLSI). PLSI learns hidden topics in the data, which is in case of 2D-NMR data interesting in its owns rights. Additionally, we develop and evaluate a simple direct similarity function, which can detect duplicates of NMR-spectra. Our experiments show that the vector space model as well as PLSI, which are both designed for text data created by humans, can effectively handle the mapped NMRdata originating from natural products. Additionally, PLSI is able to find meaningful "topics" in the NMR-data

Similarity Search for multi-dimensional NMR-Spectra of Natural Products

Abstract. Searching and mining nuclear magnetic resonance (NMR)spectra of naturally occurring products is an important task to investigate new potentially useful chemical compounds. We develop a set-based similarity function, which, however, does not sufficiently capture more abstract aspects of similarity. NMR-spectra are like documents, but consists of continuous multi-dimensional points instead of words. Probabilistic semantic indexing (PLSI) is an retrieval method, which learns hidden topics. We develop several mappings from continuous NMR-spectra to discrete text-like data. The new mappings include redundancies into the discrete data, which proofs helpful for the PLSI-model used afterwards. Our experiments show that PLSI, which is designed for text data created by humans, can effectively handle the mapped NMR-data originating from natural products. Additionally, PLSI combined with the new mappings is able to find meaningful ”topics ” in the NMR-data.

Duplicate detection of 2d-nmr spectra

2D-Nuclear magnetic resonance (NMR) spectra are used in the (structural) analysis of small molecules. In contrast to 1D-NMR spectra, 2D-NMR spectra correlate the chemical shifts of 1 H and 13 C at the same time. A spectrum consists of several peaks in a twodimensional space. The most important information of a peak is the location of its center, which captures the bonding relationships of hydrogen and carbon atoms. A spectrum contains much information about the chemical structure of a product, but in most cases the structure cannot be read off in a simple and straightforward manner. Structure elucidation involves a considerable amount (manual) efforts. Using high-field NMR spectrometers, many 2D-NMR spectra can be recorded in short time. So the common situation is that a lab or company has a repository of 2D-NMR spectra, partially annotated with the structural information. For the remaining spectra the structure in unknown. In case two research labs are collaborating, the repositories will be merged and annotations shared. We reduce that problem to the task of finding duplicates in a given set of 2D-NMR spectra. Therefore, we propose a simple but robust definition of 2D-NMR duplicates, which allows for small measurement errors. We give a quadratic algorithm for the problem, which can be implemented in SQL. Further, we analyze a more abstract class of heuristics, which are based on selecting particular peaks. Such a heuristic works as a filter step on the pairs of possible duplicates and allows false positives. We compare all methods with respect to their run time. Finally we discuss the effectiveness of the duplicate definition on real data.