Help us prioritise!

Over the years we've added many new features to ChEMBL and some of these have proved to be particularly valuable to our users. However, our resources are finite, and in order to continue to bring you exciting new improvements, we may sometimes need to re-evalutate features that are not well used and/or costly to maintain. To get the clearest possible view of which of our current data types, formats and access mechanisms are most important to you, we've put together a brief survey. If you're using ChEMBL (whether frequently or not), please help us by completing this - it should only take a couple of minutes!

https://www.surveymonkey.co.uk/r/DJ5HPF2

The survey is anonymous and will remain open until 31st October. Thanks in advance for your help.

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Here's a nice Christmas gift - ChEMBL 35 is out!

Use your well-deserved Christmas holidays to spend time with your loved ones and explore the new release of ChEMBL 35! This fresh release comes with a wealth of new data sets and some new data sources as well. Examples include a total of 14 datasets deposited by by the ASAP ( AI-driven Structure-enabled Antiviral Platform) project, a new NTD data se t by Aberystwyth University on anti-schistosome activity, nine new chemical probe data sets, and seven new data sets for the Chemogenomic library of the EUbOPEN project. We also inlcuded a few new fields that do impr ove the provenance and FAIRness of the data we host in ChEMBL: 1) A CONTACT field has been added to the DOCs table which should contain a contact profile of someone willing to be contacted about details of the dataset (ideally an ORCID ID; up to 3 contacts can be provided). 2) In an effort to provide more detailed information about the source of a deposited dat...

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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...

ChEMBL 34 is out!

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