2019 and ChEMBL – News, jobs and birthdays

Happy New Year from the ChEMBL Group to all our users and collaborators.

Firstly, do you want a new challenge in 2019? If so, we have a position for a bioinformatician in the ChEMBL Team to develop pipelines for identifying links between therapeutic targets, drugs and diseases. You will be based in the ChEMBL team but also work in collaboration with the exciting Open Targets initiative. More details can be found here (closing date 24^thJanuary).

In case you missed it, we published a paper at the end of last on the latest developments of the ChEMBL database “ChEMBL: towards direct deposition of bioassay data”. You can read it here. Highlights include bioactivity data from patents, human pharmacokinetic data from prescribing information, deposited data from neglected disease screening and data from the IMI funded K4DD project. We have also added a lot of new annotations on the therapeutic targets and indications for clinical candidates and marketed drugs to ChEMBL. Importantly we have also enhanced the data model so that we can capture information about assays and individual bioactivities in a more structured and detailed way. The top level view of the data is essentially the same but it also enhances the options for people wanting to deposit data in ChEMBL. So if you have experimental data that you would like to make publicly available through ChEMBL please contact us at chembl-help@ebi.ac.uk and we would be happy to discuss with you. Incidentally this is the same email address to use if you have any questions about using ChEMBL.

Have you tried our new ChEMBL interface yet? If not please give it a go here and let us know what you think. We are still working on refining it and so it’s not too late to influence its development. If you have suggestions now is the time to let us know by emailing chembl-help.

Last but not least this year it is 10 years since the first release of ChEMBL – watch this space for more details on how we plan to celebrate this milestone …….

Comments

Improvements in SureChEMBL's chemistry search and adoption of RDKit

Dear SureChEMBL users, If you frequently rely on our "chemistry search" feature, today brings great news! We’ve recently implemented a major update that makes your search experience faster than ever. What's New? Last week, we upgraded our structure search engine by aligning it with the core code base used in ChEMBL . This update allows SureChEMBL to leverage our FPSim2 Python package , returning results in approximately one second. The similarity search relies on 256-bit RDKit -calculated ECFP4 fingerprints, and a single instance requires approximately 1 GB of RAM to run. SureChEMBL’s FPSim2 file is not currently available for download, but we are considering generating it periodicaly and have created it once for you to try in Google Colab ! For substructure searches, we now also use an RDKit -based solution via SubstructLibrary , which returns results several times faster than our previous implementation. Additionally, structure search results are now sorted by

Improved querying for SureChEMBL

Dear SureChEMBL users, Earlier this year we ran a survey to identify what you, the users, would like to see next in SureChEMBL. Thank you for offering your feedback! This gave us the opportunity to have some interesting discussions both internally and externally. While we can't publicly reveal precisely our plans for the coming months (everything will be delivered at the right time), we can at least say that improving the compound structure extraction quality is a priority. Unfortunately, the change won't happen overnight as reprocessing 167 millions patents takes a while. However, the good news is that the new generation of optical chemical structure recognition shows good performance, even for patent images! We hope we can share our results with you soon. So in the meantime, what are we doing? You may have noticed a few changes on the SureChEMBL main page. No more "Beta" flag since we consider the system to be stable enough (it does not mean that you will never

ChEMBL brings drug bioactivity data to the Protein Data Bank in Europe

In the quest to develop new drugs, understanding the 3D structure of molecules is crucial. Resources like the Protein Data Bank in Europe (PDBe) and the Cambridge Structural Database (CSD) provide these 3D blueprints for many biological molecules. However, researchers also need to know how these molecules interact with their biological target – their bioactivity. ChEMBL is a treasure trove of bioactivity data for countless drug-like molecules. It tells us how strongly a molecule binds to a target, how it affects a biological process, and even how it might be metabolized. But here's the catch: while ChEMBL provides extensive information on a molecule's activity and cross references to other data sources, it doesn't always tell us if a 3D structure is available for a specific drug-target complex. This can be a roadblock for researchers who need that structural information to design effective drugs. Therefore, connecting ChEMBL data with resources like PDBe and CSD is essen

ChEMBL 34 is out!

We are delighted to announce the release of ChEMBL 34, which includes a full update to drug and clinical candidate drug data. This version of the database, prepared on 28/03/2024 contains: 2,431,025 compounds (of which 2,409,270 have mol files) 3,106,257 compound records (non-unique compounds) 20,772,701 activities 1,644,390 assays 15,598 targets 89,892 documents Data can be downloaded from the ChEMBL FTP site: https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/ Please see ChEMBL_34 release notes for full details of all changes in this release: https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_34/chembl_34_release_notes.txt New Data Sources European Medicines Agency (src_id = 66): European Medicines Agency's data correspond to EMA drugs prior to 20 January 2023 (excluding vaccines). 71 out of the 882 newly added EMA drugs are only authorised by EMA, rather than from other regulatory bodies e.g.

In search of the perfect assay description

Credit: Science biotech, CC BY-SA 4.0 Assays des cribe the experimental set-up when testing the activity of drug-like compounds against biological targets; they provide useful context for researchers interested in drug-target relationships. Ver sion 33 of ChEMBL contains 1.6 million diverse assays spanning ADMET, physicochemical, binding, functional and toxicity experiments. A set of well-defined and structured assay descriptions would be valuable for the drug discovery community, particularly for text mining and NLP projects. These would also support ChEMBL's ongoing efforts towards an in vitro assay classification. This Blog post will consider the features of the 'perfect' assay description and provide a guide for depositors on the submission of high quality data. ChEMBL's assays are typically structured with the overall aim, target, and method . The ideal assay description is succinct but contains all the necessary information for easy interpretation by database u

The ChEMBL-og

Search This Blog