Blast from the past - 1000th blog post!

To celebrate the 1000th post, we've decided to take a journey back in time. So, what you see above is a timeline* showing the most important blog posts published on the ChEMBL blog. The posts delineate major events and milestones in the group’s 7-year history and highlight the contributions and impact to the community. Posts on ChEMBL updates, publications, innovative software applications and popular resources are all included there.

We hope you will enjoy skimming through it as much as we did. If you have any favourite blog post published here, let us know in the comments.

Just remember that this journey continues; here’s to the next chiliad of exciting blog posts!

The ChEMBL team.

* The timeline was prepared using the excellent timelineJS library by knightlab.com.

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

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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...

ChEMBL 34 is out!

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Improved querying for SureChEMBL

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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...

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