Hormone-Receptor Database
From DrugPedia: A Wikipedia for Drug discovery
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[http://pepbank.mgh.harvard.edu/]'''PepBank''' is a database of peptides based on sequence text mining and public peptide data sources. Only peptides that are 20 amino acids or shorter are stored. This will show a heat map for a paticular peptide that show their relative tendency in cancer, cardiovascular disease, diabetes related, Apoptosis related, Angiogenesis related,Molecular imaging related,binding data avialable. | [http://pepbank.mgh.harvard.edu/]'''PepBank''' is a database of peptides based on sequence text mining and public peptide data sources. Only peptides that are 20 amino acids or shorter are stored. This will show a heat map for a paticular peptide that show their relative tendency in cancer, cardiovascular disease, diabetes related, Apoptosis related, Angiogenesis related,Molecular imaging related,binding data avialable. | ||
| - | [http://biophysics.biol.uoa.gr/gpDB/]'''gpDB'''relational database of G-proteins and their interactions with GPCRs and effector molecules. The sequences are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature search. The main innovation besides the classification of both G-proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective alpha subunit of G-proteins and also the interaction between G-protein subfamilies and specific effector types, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, and the user may submit advanced queries for text search. Furthermore there is an interface for running BLAST against the database and a pattern search tool. The database will be very useful for the study of G-protein/GPCR and G-protein/effector interactions. | + | [http://biophysics.biol.uoa.gr/gpDB/]'''gpDB''' is a relational database of G-proteins and their interactions with GPCRs and effector molecules. The sequences are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature search. The main innovation besides the classification of both G-proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective alpha subunit of G-proteins and also the interaction between G-protein subfamilies and specific effector types, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, and the user may submit advanced queries for text search. Furthermore there is an interface for running BLAST against the database and a pattern search tool. The database will be very useful for the study of G-protein/GPCR and G-protein/effector interactions. |
[http://www.biomedcomp.com/GPCR.html]A database having lists the G protein coupled receptors expressed endogenously in various cell lines. | [http://www.biomedcomp.com/GPCR.html]A database having lists the G protein coupled receptors expressed endogenously in various cell lines. | ||
Revision as of 08:30, 19 September 2008
[1]GLIDA is a database thar have the information on both GPCRs and their known ligands.
- A complex information system covering biological information of GPCRs as well as chemical information of their known ligands.
- Two starting points : Enterable either by GPCR search or ligand search.
- Cross-searchable between GPCRs and their ligands.
This database use the GPCRDb classification system for classifying GPCR and Clustering Method for classifying Ligands.It has similarity search sytem for both ligand and GPCR.
[2]IUPHAR A Database of GPCR Protein
[3]EndoNet is a database that provides information about endocrine networks. Using information about hormones' donor and acceptor cells a network is built that represents hormonal signaling pathways as a bipartite graph comprising hormones and tissues as node classes. The involved components, the intercellular information flow and the inhibition or activation effects are displayed.
[4]LipidBank is an open, publicly free database of natural lipids including fatty acids, glycerolipids, sphingolipids, steroids, and various vitamins.The database contains more than 6000 unique molecular structures (ChemDraw cdx format, MDL MOL format), their lipid names (common name, IUPAC), spectral information (mass, UV, IR, NMR and others), and most importantly, literature information.
[5] The LIPID MAPS(LIPID Metabolites And Pathways Strategy) structure database now contains a total of 10,789 entries, including 2688 Fatty acyls (FA), 3009 Glycerolipids (GL), 1971 Glycerphospholipids (GP), 621 Sphingolipids (SP), 1745 Sterol lipids (ST), 609 Prenol lipids (PR), 10 Saccharolipids (SL), and 136 Polyketides (PK).
[6]PepBank is a database of peptides based on sequence text mining and public peptide data sources. Only peptides that are 20 amino acids or shorter are stored. This will show a heat map for a paticular peptide that show their relative tendency in cancer, cardiovascular disease, diabetes related, Apoptosis related, Angiogenesis related,Molecular imaging related,binding data avialable.
[7]gpDB is a relational database of G-proteins and their interactions with GPCRs and effector molecules. The sequences are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature search. The main innovation besides the classification of both G-proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective alpha subunit of G-proteins and also the interaction between G-protein subfamilies and specific effector types, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, and the user may submit advanced queries for text search. Furthermore there is an interface for running BLAST against the database and a pattern search tool. The database will be very useful for the study of G-protein/GPCR and G-protein/effector interactions.
[8]A database having lists the G protein coupled receptors expressed endogenously in various cell lines.
