Natural Product Database

Figure 10.2-7. Predictions oF h NMR cheinical shifts for a complex natural product by neural networks, a database-centered method (ACD), and an increment-based method (Upstream).

Figure 4.4 The general protocol for information extraction from an herbal text (A-E) is paired with case examples from our work with the Ambonese Herbal by Rumphius. (A) Text is digitized. (B) Through either manual reading or automated extraction the plant name(s), plant part(s), and symptoms or disorders are identified. (C) These extracted data are then updated (as necessary) to reflect current names of the plants, using the International Plant Names Index (IPNI), and the pharmacological function(s) of the described medicinal plants are extrapolated from the mentioned symptoms and disorders. (D) The current botanical names are queried against a natural products database such as the NAPRALERT database to determine whether the plant has been previously examined. (E) Differential tables are generated that separate the plants examined in the literature from plants that may warrant further examination for bioactivity. (Adapted from Trends in Pharmacological Sciences, with permission.) See color plate.

Incorporating the Kirtas system with the International Plant Names Index and SNOW-MED allows movement of the historic text into an electronic format, identihcation of current plant names, and identihcation of the symptoms treated with the plants. To complete the mining of historic herbal texts for novel drug leads we use the Natural Products Alert (NAPRALERT ) database to compare the information extracted from the historic herbal text to the reports of plant use in the current literature. The NAPRALERT database provides a summary of plants ethnopharmacological use, biochemical activities, and isolated compounds [27]. By querying each plant (with the current plant name) it is possible to identify any reports in the current literature regarding the plant. As an example, Table 4.1 shows the NAPRALERT output for Cycas rumphii. 

Na/K ATPase ICB natural product database (37 K), QSAR, Chemfinder similarity search based on ouabain 4 hits/10 tested [70]... 

Regarding the discovery of novel metabolites from fungal species previously investigated, it is of interest to point out that several fungal genome sequences currently available in public databases have revealed the existence of many orphan biosynthetic pathways for which the encoded natural products remain unknown [30]. Therefore, it is likely that further new metabolites and/or phytotoxins will be isolated from fungal species such as L. maculans and A. brassicicola when grown under different conditions such as culture medium or temperature. 

The DNP (Chapman HaU/CRC Dictionary of Natural Products) is a comprehensive literature database of around 170 000 isolated natural products from various sources and provides names, chemical structures, CAS registry numbers, extensive source data, uses and applications. 

CNPD (China Natural Products Database) provides for around 10 000 natural products isolated in China, 2D and 3D chemical structures, CAS registry numbers, integrated with related therapeutic uses in TMC (Traditional Chinese Medicine). 

The Dictionary of Natural Products database is available from Chapman HaU/CRC Press at http //www.chemnetbase.com... 

For this task, easily accessible properties of mixtures or pure metabolites are compared with literature data. This may be the biological activity spectrum against a variety of test organisms. Widely used also is the comparison of UV [90] or MS data and HPLC retention times with appropriate reference data collections, a method which needs only minimal amounts and affords reliable results. Finally, there are databases where substructures, NMR or UV data and a variety of other molecular descriptors can be searched using computers [91]. The most comprehensive data collection of natural compounds is the Dictionary of Natural Products (DNP) [92], which compiles metabolites from all natural sources, also from plants. More appropriate for dereplication of microbial products, however, is our own data collection (AntiBase [93]) that allows rapid identification using combined structural features and spectroscopic data, tools that are not available in the DNP. 

Bukingham J, Thompson S (1997) Dictionary of natural products and other information somces for natmal products scientists. In Phytochemical diversity - a somce of new industrial products. Royal Society of Chemistry, London, pp 53-67 (2001) Dictionary of Natmal Products on CD-ROM, Chapman and HaU/CRC Press Laatsch H (1994 and annual updates) AntiBase, A database for rapid structmal determination of microbial natmal products. Chemical Concepts, Weinheim, Germany Breheret S, Talou T, Rapior S, Bessiere JM (1997) J Agric Food Chem 45 831 Schulz S (2001) private commimication, Braunschweig, Germany Burkholder PR, Pfister RM, Leitz FH (1966) Appl Microbiol 14 649 Reid RT, Live DH, Faulkner DJ, Butler A (1993) Nature 366 455... 

In view of the abundance of natural products known to us, a collection such as this one must of course restrict itself to a few representatives from important classes of substances. At any rate, for a comprehensive collection of as much information as possible on as many natural products as possible, databases with their search possibilities are more suitable. However, one must bear in mind that data is often missing for products which were described some time ago this occurs, for example, because only the more recent publications have been included in databases. 

Farnsworth, N. R. 1999. NAPRALERT natural products alert database. Program for collaborative research in the Pharmaceutical Science Department of Medicinal Chem. Pharmacognosy, College Pharmacy, University of Illinois, Chicago. 

Use of an integrated system incorporating CCC separation, PDA detector, and LC-MS proved to be a valuable tool in the rapid identification of known compounds from microbial extracts.6 This collection of analytical data has enabled us to make exploratory use of advanced data analysis methods to enhance the identification process. For example, from the UV absorbance maxima and molecular weight for the active compound(s) present in a fraction, a list of potential structural matches from a natural products database (e.g., Berdy Bioactive Natural Products Database, Dictionary of Natural Products by Chapman and Hall, etc.) can be generated. Subsequently, the identity of metabolite(s) was ascertained by acquiring a proton nuclear magnetic resonance ( H-NMR) spectrum. 

Blunt, J.W. and Munro, M.H.G., University of Canterbury, Marinlit A Database of the Literature on Marine Natural Product, 1997. 

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