Skip to main content

ChEMBL tissues: Increasing depth, breadth and accuracy of annotations

By


Our current tissue annotation efforts have been on increasing the breadth and depth of the tissue effort first started in ChEMBL 22. The figure above represents the increased depth and coverage from that initial point till now. 

We continue to use a suite of tissue ontologies namely: Uberon, Experimental Factor Ontology (http://www.ebi.ac.uk/ols/ontologies/efo), CALOHA (ftp://ftp.nextprot.org/pub/current_release/controlled_vocabularies/caloha.obo) and Brenda Tissue Ontology ((http://www.ebi.ac.uk/ols/ontologies/bto)  to identify assays where the tissue is the assay system. We have increased the detail of information we capture to reflect the more granular tissues mentioned in the assays such as 'Popliteal lymph node' and 'Substantia nigra' pars compacta where previously the higher level term ‘lymph node’ and ‘Substantia nigra’ might have been captured.

Plasma based assays

We have recently focused annotation efforts on plasma based assays  in response to end user interest in this assays as well as acknowledging the general prevalence of plasma as an assay system for many functional/ADME assays.

Assays with multiple tissue types
We have also increased tissue curation of bioassays whose measurements are recorded across multiple tissues in a single assay e.g ‘Kidney/Liver’, ‘Heart/Liver’. In these cases, bespoke entries are created in the Tissue Dictionary, representing the tissue combination.
 
Ongoing improvements to tissue curation

·      These newly created tissue targets and assays annotated with these will be available in the next ChEMBL release (ChEMBL 24).
·      Our future web interface tissue search functionality will also make use of hierarchies inherent in the tissue ontologies to retrieve the more granular tissue terms on searching with a higher level term. An example would be that a tissue search for a high level term would include child terms of the higher level term e.g  A search for assays annotated with the tissue ‘compound eye’ UBERON:0000018 should also ideally retrieve assays annotated with direct children of this higher level term e.g ommatidium (UBERON:0000971).
·      The nature of ontological terms is such that species differences may not always be abundantly clear where single tissue term is used across different taxonomic groups to describe tissues that perform the same function in the different species but have clear anatomical differences. An example being the term eye which refers to the ‘compound eye’ UBERON:0000018 found in insects vs ‘camera type eye’ UBERON:0000019 as found in humans. We plan to use taxonomic constraint information to disambiguate cases like these and improve the correctness of mappings.
 
For queries and questions on tissue annotation-related matters please contact our help desk chembl-help@ebi.ac.uk

Comments

Post a Comment

Popular posts from this blog

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

By
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...
Post a Comment
Read more

Improvements in SureChEMBL's chemistry search and adoption of RDKit

By Eloy
    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...
Post a Comment
Read more

ChEMBL 34 is out!

By
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 ...
Post a Comment
Read more

Improved querying for SureChEMBL

By
    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 ...
Post a Comment
Read more

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

By
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...
Post a Comment
Read more