ChEMBL US Tour - an update

We've had a great response to our call for offers of venues to help us on a ChEMBL outreach tour, funded by the SMSDrug.net project. Things are shaping up pretty well, but we probably still have space for something in the Seattle area, and also space maybe for something in Philadelphia. We also will probably do both East and West coasts on the same trip, due to the very positive response.

Get in touch if you are in the north-west, or north-east!

jpo

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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...

Improved querying for SureChEMBL

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ChEMBL 34 is out!

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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...

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...

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