TY - JOUR
T1 - ChemDB update - Full-text search and virtual chemical space
AU - Chen, Jonathan H.
AU - Linstead, Erik
AU - Swamidass, S. Joshua
AU - Wang, Dennis
AU - Baldi, Pierre
N1 - Funding Information:
Work supported by an NIH Biomedical Informatics Training grant (LM-07443-01) and NSF grants EIA-0321390 and 0513376 to P.B. We acknowledge the OpenBabel project, OpenEye Scientific Software, Peter Ertl of Novartis (JME Editor) and the JMol project for academic software licenses. We thank the laboratory of Dr Tsai for the tuberculosis drug discovery collaboration.
PY - 2007/9/1
Y1 - 2007/9/1
N2 - ChemDB is a chemical database containing nearly 5M commercially available small molecules, important for use as synthetic building blocks, probes in systems biology and as leads for the discovery of drugs and other useful compounds. The data is publicly available over the web for download and for targeted searches using a variety of powerful methods. The chemical data includes predicted or experimentally determined physicochemical properties, such as 3D structure, melting temperature and solubility. Recent developments include optimization of chemical structure (and substructure) retrieval algorithms, enabling full database searches in less than a second. A text-based search engine allows efficient searching of compounds based on over 65M annotations from over 150 vendors. When searching for chemicals by name, fuzzy text matching capabilities yield productive results even when the correct spelling of a chemical name is unknown, taking advantage of both systematic and common names. Finally, built in reaction models enable searches through virtual chemical space, consisting of hypothetical products readily synthesizable from the building blocks in ChemDB.
AB - ChemDB is a chemical database containing nearly 5M commercially available small molecules, important for use as synthetic building blocks, probes in systems biology and as leads for the discovery of drugs and other useful compounds. The data is publicly available over the web for download and for targeted searches using a variety of powerful methods. The chemical data includes predicted or experimentally determined physicochemical properties, such as 3D structure, melting temperature and solubility. Recent developments include optimization of chemical structure (and substructure) retrieval algorithms, enabling full database searches in less than a second. A text-based search engine allows efficient searching of compounds based on over 65M annotations from over 150 vendors. When searching for chemicals by name, fuzzy text matching capabilities yield productive results even when the correct spelling of a chemical name is unknown, taking advantage of both systematic and common names. Finally, built in reaction models enable searches through virtual chemical space, consisting of hypothetical products readily synthesizable from the building blocks in ChemDB.
UR - http://www.scopus.com/inward/record.url?scp=34548742854&partnerID=8YFLogxK
U2 - 10.1093/bioinformatics/btm341
DO - 10.1093/bioinformatics/btm341
M3 - Article
C2 - 17599932
AN - SCOPUS:34548742854
SN - 1367-4803
VL - 23
SP - 2348
EP - 2351
JO - Bioinformatics
JF - Bioinformatics
IS - 17
ER -