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Cheminformatics
and cerebrospinal fluid samples. This is further listed above and from individual chemists.
supplemented with thousands of NMR and MS ChemSpider has also integrated the SureChem
spectra collected on purified, reference metabo- patent database collection (http://www.surechem.
lites. Each metabolite entry in the HMDB contains org/) of structures to facilitate structure-based link-
data fields including a comprehensive compound ing to patents between the two data collections.
description, names and synonyms, structural ChemSpider can be queried using struc-
information, physicochemical data, reference ture/substructure searching and alphanumeric text
NMR and MS spectra, biofluid concentrations, searching of both intrinsic as well as predicted
disease associations, pathway information, molecular properties. Unique capabilities relative
enzyme data, gene sequence data, SNP and muta- to other public chemistry databases include real
tion data as well as extensive links to images, ref- time curation of the data, association of analytical
erences and other public databases. Recent data with chemical structures, real-time deposition
Figure 2
improvements have included spectra and substruc- of single or batch chemical structures (including The ChEBI database offers a
ture searching. with activity data) and transaction-based predic-
detailed ontology including
tions of physicochemical data. A series of web serv-
subdivision into (1) Molecular
Structure, in which molecular
DrugBank (http://www.drugbank.ca/) is a manual- ices are provided to allow integration to the system
entities or parts thereof are
ly curated resource
7
assembled from a series of for the purpose of searching and linking with other
classified according to
other public domain databases (KEGG, PubChem, online databases from other groups (academia or composition and structure (2)
ChEBI, PDB, Swiss-Prot and GenBank) and industry). The integration can be with free or com-
Role, which classifies entities
enhanced with additional data generated within mercial resources. For example, Collaborative
either on the basis of their
role within a biological
the laboratories of the hosts. The database aggre- Drug Discovery, Inc (http://www.collaborative
context, eg antibiotic, antiviral
gates both bioinformatics and cheminformatics drug.com) recently provided links to ChemSpider
agent, coenzyme, hormone, or
data and combines detailed drug data with com- for molecules in its CDD database
12
thereby pro- on the basis of their intended
prehensive drug target (ie protein) information. viding an integration path between a commercial
use by humans, eg pesticide,
The database contains FDA approved small mole- resource and a public domain database. CDD is a
antirheumatic drug, fuel. The
structure shown is for
cule and biotech drugs as well as experimental highly secure, commercial collaborative drug dis-
chloroquine, identified as an
drugs, representing nearly 5,000 molecules
8
. The covery informatics platform and a new type of col-
antimalarial quinoline alkaloid
database supports extensive text, sequence, chemi- laborative system that handles a broad array of in the ChEBI ontology
cal structure and relational query searches of the
nearly 100 data fields. The data from DrugBank
has been used to show that the drug to drug-target
relationship is scale-free and several classes of pro-
teins are selectively enriched as drug targets for
FDA approved drugs
9
.
ZINC (http://zinc.docking.org/index.shtml) is a
free, searchable database of commercially avail-
able compounds for virtual screening
10,11
. The
library contains more than 20 million molecules,
each with a 3D structure and gathered from the
catalogues of compounds from vendors. All mole-
cules in the databases are assigned biologically-rel-
evant protonation states and annotated with
molecular properties.
ChemSpider (http://www.chemspider.com/)
1,2
is a
community resource for chemists provided by the
Royal Society of Chemistry (Figure 3). It offers a
number of facilities that distinguishes the service
from many of the other databases listed in this arti-
cle. At the time of writing it contains more than 23
million unique chemical entities aggregated from
more than 200 diverse data sources, including gov-
ernment databases, chemical vendors, commercial
database vendors, publishers, all of the databases
Drug Discovery World Winter 2009/10 35
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