The ChEMBL-og

We are pleased to announce the release of ChEMBL 25 and our new web interface. This version of the database, prepared on 10/12/2018 contains: 2,335,417 compound records 1,879,206 compounds (of which 1,870,461 have mol files) 15,504,603 activities 1,125,387 assays 12,482 targets 72,271 documents Data can be downloaded from the ChEMBL ftp site: ftp://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_25 Please see ChEMBL_25 release notes for full details of all changes in this release: ftp://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_25/chembl_25_release_notes.txt DATA CHANGES SINCE THE LAST RELEASE # Deposited Data Sets: Kuster Lab Chemical Proteomics Drug Profiling (src_id = 48, Document ChEMBL_ID = CHEMBL3991601): Data have been included from the publication: The target landscape of clinical kinase drugs. Klaeger S, Heinzlmeir S and Wilhelm M et al (2017), Science, 358-6367 ( https://doi.org/10.1126/science.aan4368 ) # In Vivo Assay ...

In 2019 we celebrate the 10th anniversary of the first public release of the ChEMBL database. To recognise this important landmark we are organising a one-day symposium to celebrate the work achieved by ChEMBL during its first ten years, and look forward to its future. Save the date - Tuesday 8th October 2019 The symposium will be held on Tuesday 8th October in the Francis Crick Auditorium on the Wellcome Genome Campus, Hinxton, Cambridge, UK. A series of talks from invited speakers will be followed by a celebratory birthday cake and drinks reception. During the breaks, the poster session will be a great opportunity to catch up with other users of the ChEMBL database and chat to colleagues, co-workers and others to find how more about how the database is being used. For the programme of invited talks, and  more information on how to register,  see  https://www.ebi.ac.uk/about/events/10-years-of-chembl

  You know that in the ChEMBL group, we love to play with the data we collect!! Back in April 2014, we started to work on a  target prediction tool.   Wow! This was almost 5 years ago! Since then, we have continued to update the tool for each new ChEMBL release, providing you with the actual models and the result of the prediction on the ChEMBL website for the drug molecules. The good news is that these target predictions are not dead and a successor is on its way! First, we would like to introduce you some closely related work. You may have heard about conformal prediction (CP). If not, it is a machine learning framework developed to associate confidence to predictions. I personally consider this as a requirement for decision making. Basically, you train a model as you would do in QSAR but then you first predict a so-called calibration set, for which you know the actual values. For each of these observations you obtain two probabilities: one for the act...