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Chemistry and Nature

  As the Great Big Green Week (UK) draws to a close, so does EMBL-EBI’s own Sustainability week. The Wellcome Genome Campus held events in the areas of recycling, energy use, and biodiversity. The ChEMBL team was keen to get involved and we developed our own Nature Trail event highlighting some of the bioactive compounds from the flora and fauna found on-site, and elsewhere. Our favourite examples include the sensation of mint and chilli and the glorious smell of rain! The full Nature Trail can be made available for external Public Engagement events upon request . Databases, such as ChEMBL , are large stores of structured data, including genetic, biological, and chemistry data for life sciences research. Data on the natural world is often held by wildlife organisations; this can be used to research biodiversity and species decline. Various Citizen Science initiatives mean that everyone can get involved in submitting nature records. So why not join in with the Butterfly Conservation’s B
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Release of ChEMBL 33

We are pleased to announce the release of ChEMBL 33! This fresh release comes with a few new data soures and also some new features: we added bioactivity data for understudied SLC targets from the RESOLUTE project and included a flag for Natural Products and for Chemical Probes. An annotation for the ACTION_TYPE of a measurement was included for approx. 270 K bioactivities. We also time-stamped every document in ChEMBL with their CREATION_DATE! Have fun playing around with ChEMBL 33 over the summer and please send feedback via chembl-help@ebi.ac.uk .   ChEMBL database version ChEMBL 33 release notes ___________________________________________ # This version of the database, prepared on 31/05/2023 contains:      2,399,743 compounds (of which 2,372,674 have mol files)      3,051,613 compound records (non-unique compounds)        20,334,684 activities         1,610,596 assays      15,398 targets      88,630 documents BioAssay Data Sources:    Number Assays:    Number

Drug warning update: withdrawn drugs and drugs that carry a black box warning

The drug warning information in ChEMBL has been updated for version 32. In particular, the withdrawn drug data has been fully reviewed and, to assist the manual curation process, our rules have been updated, clarified and formally written.  In ChEMBL, a withdrawn drug is an approved drug (ie Phase 4) that has subsequently been withdrawn for toxicity reasons. For example, a drug is assigned as 'withdrawn' if: All doses are withdrawn (and not just the highest dose). The drug is withdrawn for all populations (and not just infants). The drugs is withdrawn for all indications.  Any drug withdrawn for a lack of evidence of efficacy is not included.  Any drug withdrawn for drug-drug interactions is included if it is a safety-related withdrawal. A regulatory body (e.g. EMA, FDA) is the preferred source of information for the withdrawn status. The withdrawn status is mapped to an individual drug form (e.g. a parent (salt-stripped) or salt drug form within a family of compound structures

Natural Product-likeness in ChEMBL

Recently, we included a Natural Product-likeness score for chemical compounds stored in ChEMBL. We made use of an algorithm published by Peter Ertl, Silvio Roggo and Ansgar Schuffenhauer in 2008 .  Whereas the original version of this algorithm used a commercial data set of Natural Product molecules for training the algorithm (the CRC Dictionary of Natural Products) and an in-house library of synthetic molecules as a negative set, we used Greg Landrum's  RDKit implementation  which is based on  ~50,000 natural products collected from various open databases and ~1 million drug-like molecules from ZINC as a "non-Natural Product background". After including the new score into ChEMBL, we were interested to see whether the results look meaningful. We had a handful of simple questions: How is Natural Product-likeness distributed in ChEMBL and how does this compare to Natural Product-likeness for "real" NPs? Can we observe any difference in Natural Product-likeness for