The ChEMBL bioactivity database: an update.

ChEMBL is an open large-scale bioactivity database (https://www.ebi.ac.uk/chembl), previously described in the 2012 Nucleic Acids Research Database Issue. Since then, a variety of new data sources and improvements in functionality have contributed to the growth and utility of the resource. In particular, more comprehensive tracking of compounds from research stages through clinical development to market is provided through the inclusion of data from United States Adopted Name applications; a new richer data model for representing drug targets has been developed; and a number of methods have been put in place to allow users to more easily identify reliable data. Finally, access to ChEMBL is now available via a new Resource Description Framework format, in addition to the web-based interface, data downloads and web services.

ChEMBL: a large-scale bioactivity database for drug discovery.

ChEMBL is an Open Data database containing binding, functional and ADMET information for a large number of drug-like bioactive compounds. These data are manually abstracted from the primary published literature on a regular basis, then further curated and standardized to maximize their quality and utility across a wide range of chemical biology and drug-discovery research problems. Currently, the database contains 5.4 million bioactivity measurements for more than 1 million compounds and 5200 protein targets. Access is available through a web-based interface, data downloads and web services at: https://www.ebi.ac.uk/chembldb.

Estimating error rates in bioactivity databases.

Bioactivity databases are routinely used in drug discovery to look-up and, using prediction tools, to predict potential targets for small molecules. These databases are typically manually curated from patents and scientific articles. Apart from errors in the source document, the human factor can cause errors during the extraction process. These errors can lead to wrong decisions in the early drug discovery process. In the current work, we have compared bioactivity data from three large databases (ChEMBL, Liceptor, and WOMBAT) who have curated data from the same source documents. As a result, we are able to report error rate estimates for individual activity parameters and individual bioactivity databases. Small molecule structures have the greatest estimated error rate followed by target, activity value, and activity type. This order is also reflected in supplier-specific error rate estimates. The results are also useful in identifying data points for recuration. We hope the results will lead to a more widespread awareness among scientists on the frequencies and types of errors in bioactivity data.

Collation and data-mining of literature bioactivity data for drug discovery.

The challenge of translating the huge amount of genomic and biochemical data into new drugs is a costly and challenging task. Historically, there has been comparatively little focus on linking the biochemical and chemical worlds. To address this need, we have developed ChEMBL, an online resource of small-molecule SAR (structure-activity relationship) data, which can be used to support chemical biology, lead discovery and target selection in drug discovery. The database contains the abstracted structures, properties and biological activities for over 700000 distinct compounds and in excess of more than 3 million bioactivity records abstracted from over 40000 publications. Additional public domain resources can be readily integrated into the same data model (e.g. PubChem BioAssay data). The compounds in ChEMBL are largely extracted from the primary medicinal chemistry literature, and are therefore usually 'drug-like' or 'lead-like' small molecules with full experimental context. The data cover a significant fraction of the discovery of modern drugs, and are useful in a wide range of drug design and discovery tasks. In addition to the compound data, ChEMBL also contains information for over 8000 protein, cell line and whole-organism 'targets', with over 4000 of those being proteins linked to their underlying genes. The database is searchable both chemically, using an interactive compound sketch tool, protein sequences, family hierarchies, SMILES strings, compound research codes and key words, and biologically, using a variety of gene identifiers, protein sequence similarity and protein families. The information retrieved can then be readily filtered and downloaded into various formats. ChEMBL can be accessed online at https://www.ebi.ac.uk/chembldb.

Cyclic AMP blocks cell growth through Raf-1-dependent and Raf-1-independent mechanisms.

It is widely accepted that cyclic AMP (cAMP) can block cell growth by phosphorylating Raf-1 on serine 43 and inhibiting signaling to extracellular signal-regulated protein kinase. We show that the suppression of Raf-1 by cAMP is considerably more complex than previously reported. When cellular cAMP is elevated, Raf-1 is phosphorylated on three residues (S43, S233, and S259), which work independently to block Raf-1. Both Ras-dependent and Ras-independent processes are disrupted. However, when cAMP-insensitive versions of Raf-1 are expressed in NIH 3T3 cells, their growth is still strongly suppressed when cAMP is elevated. Thus, although Raf-1 appears to be an important cAMP target, other pathways are also targeted by cAMP, providing alternative mechanisms that lead to suppression of cell growth.

14-3-3 antagonizes Ras-mediated Raf-1 recruitment to the plasma membrane to maintain signaling fidelity.

We have investigated the role that S259 phosphorylation, S621 phosphorylation, and 14-3-3 binding play in regulating Raf-1 activity. We show that 14-3-3 binding, rather than Raf-1 phosphorylation, is required for the correct regulation of kinase activity. Phosphorylation of S621 is not required for activity, but 14-3-3 binding is essential. When 14-3-3 binding to conserved region 2 (CR2) was disrupted, Raf-1 basal kinase activity was elevated and it could be further activated by (V12,G37)Ras, (V23)TC21, and (V38)R-Ras. Disruption of 14-3-3 binding at CR2 did not recover binding of Raf-1 to (V12,G37)Ras but allowed more efficient recruitment of Raf-1 to the plasma membrane and stimulated its phosphorylation on S338. Finally, (V12)Ras, but not (V12,G37)Ras, displaced 14-3-3 from full-length Raf-1 and the Raf-1 bound to Ras. GTP was still phosphorylated on S259. Our data suggest that stable association of Raf-1 with the plasma membrane requires Ras-mediated displacement of 14-3-3 from CR2. Small G proteins that cannot displace 14-3-3 fail to recruit Raf-1 to the membrane efficiently and so fail to stimulate kinase activity.

Activated B-RAF is an Hsp90 client protein that is targeted by the anticancer drug 17-allylamino-17-demethoxygeldanamycin.

Hsp90 is a ubiquitously expressed molecular chaperone that folds, stabilizes, and functionally regulates many cellular proteins. The benzoquinone ansamysin 17-allylamino-17-demethoxygeldanamycin (17-AAG) is an anticancer drug that disrupts Hsp90 binding to its clients, causing their degradation through the ubiquitin-dependent proteasomal pathway. The protein kinase B-RAF is mutated in approximately 7% of human cancers. The most common mutation (approximately 90%) is (V600E)B-RAF, which has constitutively elevated kinase activity, stimulates cancer cell proliferation, and promotes survival. Here, we show that (V600E)B-RAF is an Hsp90 client protein that requires Hsp90 for its folding and stability. (V600E)BRAF is more sensitive to degradation by 17-AAG treatment than (WT)B-RAF and we show that the majority of the other mutant forms of B-RAF are also sensitive to 17-AAG-mediated proteasomal degradation. Our data show that B-RAF is an important target for 17-AAG in human cancer.

Expression of kinase suppressor of Ras in the normal adult and embryonic mouse.

Recent studies indicate that kinase suppressor of Ras (KSR)is a scaffold protein for the Ras/Raf/MEK/ERK signaling cascade in mammals. To help determine the in vivo function of KSR, we have examined the tissue-specific distribution of this protein in the embryonic and adult mouse using a rat monoclonal antibody raised against the mouse protein. Western blot analysis indicates that the protein is expressed at highest levels in the adult brain. It is also expressed at low levels in bladder, ovary, testis, and lung, but the protein is not detectable in any other adult tissue. However, reverse transcription-PCR analysis shows that Ksr transcripts are detected in all adult tissues except the liver. A variant containing a differentially spliced exon in the CA4 domain is observed in brain, cerebellum, ovary, and intestine. The protein is also expressed throughout the E6.5 embryo and at high levels in the neuroepithelium of the E10.5 embryo. At this embryonic stage, expression is also detected at lower levels in the limb and tail buds as well as in the myocardium.