Skip to main content

Citing ChEMBL, and Data DOIs


There are now multiple formats and ways to access the ChEMBL data, and we have recently assigned DOIs to all available versions of ChEMBL (and will archive these on the ftp server, permanently).

So when you publish use of ChEMBL, could you reference the following papers:

ChEMBL Database
A. Gaulton, L. Bellis, J. Chambers, M. Davies, A. Hersey, Y. Light, S. McGlinchey, R. Akhtar, A.P. Bento, B. Al-Lazikani, D. Michalovich, & J.P. Overington (2012) ‘ChEMBL: A Large-scale Bioactivity Database For Chemical Biology and Drug Discovery’ Nucleic Acids Res. Database Issue, 40 D1100-1107. DOI:10.1093/nar/gkr777 PMID:21948594

A.P. Bento, A. Gaulton, A. Hersey, L.J. Bellis, J. Chambers, M. Davies, F.A. Krüger, Y. Light, L. Mak, S. McGlinchey, M. Nowotka, G. Papadatos, R. Santos & J.P. Overington (2014) ‘The ChEMBL bioactivity database: an update’ Nucleic Acids Res. Database Issue, 42 1083-1090. DOI:10.1093/nar/gkt103 PMID: 24214965

myChEMBL
R. Ochoa, M. Davies, G. Papadatos, F. Atkinson and J.P. Overington (2014) 'myChEMBL: A virtual machine implementation of open data and cheminformatics tools' Bioinformatics. 30 298-300. DOI10.1093/bioinformatics/btt666 PMID: 24262214

ChEMBL RDF
S. Jupp, J. Malone, J. Bolleman, M. Brandizi, M. Davies, L. Garcia, A. Gaulton, S. Gehant, C. Laibe, N. Redaschi, S.M Wimalaratne, M. Martin, N. Le Novère, H. Parkinson, E. Birney and A.M Jenkinson (2014) 'The EBI RDF Platform: Linked Open Data for the Life Sciences' Bioinformatics 30 1338-1339 DOI:10.1093/bioinformatics/btt765 PMID:24413672

Also please reference the version of ChEMBL you may have used in any published analyses, using the following DOIs:

Dataset
DOI
ChEMBL

CHEMBL01
10.6019/CHEMBL.database.01
CHEMBL02
10.6019/CHEMBL.database.02
CHEMBL03
10.6019/CHEMBL.database.03
CHEMBL04
10.6019/CHEMBL.database.04
CHEMBL05
10.6019/CHEMBL.database.05
CHEMBL06
10.6019/CHEMBL.database.06
CHEMBL07
10.6019/CHEMBL.database.07
CHEMBL08
10.6019/CHEMBL.database.08
CHEMBL09
10.6019/CHEMBL.database.09
CHEMBL10
10.6019/CHEMBL.database.10
CHEMBL11
10.6019/CHEMBL.database.11
CHEMBL12
10.6019/CHEMBL.database.12
CHEMBL13
10.6019/CHEMBL.database.13
CHEMBL14
10.6019/CHEMBL.database.14
CHEMBL15
10.6019/CHEMBL.database.15
CHEMBL16
10.6019/CHEMBL.database.16
CHEMBL17
10.6019/CHEMBL.database.17
CHEMBL18
10.6019/CHEMBL.database.18
CHEMBL19
10.6019/CHEMBL.database.19


ChEMBL-RDF

ChEMBL-RDF/16.0
10.6019/CHEMBL.RDF.16.0
ChEMBL-RDF/17.0
10.6019/CHEMBL.RDF.17.0
ChEMBL-RDF/18.0
10.6019/CHEMBL.RDF.18.0
ChEMBL-RDF/18.1
10.6019/CHEMBL.RDF.19.0


myChEMBL

myChEMBL-17_0
10.6019/CHEMBL.myCHEMBL.17.0
myChEMBL-18_0
10.6019/CHEMBL.myCHEMBL.18.0

Future releases will adhere to the following patterns. We will be modifying the attribution part of the ChEMBL license to require reporting of these DOIs in publications that use ChEMBL. We hope this will contribute to reproducibility of analyses.

Comments

Popular posts from this blog

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

    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 ...

ChEMBL 34 is out!

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 ...

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...