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ChEMBL 26 Released



We are pleased to announce the release of ChEMBL_26

This version of the database, prepared on 10/01/2020 contains:

  • 2,425,876 compound records
  • 1,950,765 compounds (of which 1,940,733 have mol files)
  • 15,996,368 activities
  • 1,221,311 assays
  • 13,377 targets
  • 76,076 documents
You can query the ChEMBL 26 data online via the ChEMBL Interface and you can also download the data from the ChEMBL FTP site. Please see ChEMBL_26 release notes for full details of all changes in this release.

Changes since the last release:

* Deposited Data Sets:

CO-ADD antimicrobial screening data:
Two new data sets have been included from the Community for Open Access Drug Discovery (CO-ADD). These data sets are screening of the NIH NCI Natural Product Set III in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296183, DOI = 10.6019/CHEMBL4296183) and screening of the NIH NCI Diversity Set V in the CO-ADD assays (src_id = 40, Document ChEMBL_ID = CHEMBL4296182, DOI = 10.6019/CHEMBL4296182).

HESI - Evaluation of the utility of stem-cell derived cardiomyocytes for drug proarrhythmic potential (src_id = 49, Document ChEMBL_ID = CHEMBL4295262 , DOI = 10.6019/CHEMBL4295262). Summary assay results for this data set have been included in ChEMBL_26 and further supplementary data will be added in ChEMBL_27.

* Changes to structure-processing and compound properties:
We are now using RDKit for almost all of our compound-related processing. For the first time in ChEMBL_26, this will include compound standardization, salt-stripping, generation of canonical smiles, structural alerts, image depiction, substructure searches and similarity searches (via FPSim2: https://github.com/chembl/FPSim2). Therefore, all molecules have been reprocessed and you may notice some differences in molfiles, smiles and structure search results compared with previous releases. The ChEMBL structure curation pipeline has been released as an open source package: https://github.com/chembl/ChEMBL_Structure_Pipeline, and incorporated into our Beaker web services (see below). More information can be found here: http://chembl.blogspot.com/2020/02/chembl-compound-curation-pipeline.html.

We are also now using ChemAxon tools to calculate most acidic and basic pKa, logP and logD (pH 7.4) predictions, rather than ACDLabs software. These properties have therefore been recalculated and renamed in the database.

* Target Predictions:
Target predictions in ChEMBL are now generated by a new method, using conformal prediction (https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0325-4). A docker image is available for those wishing to use the models locally: https://hub.docker.com/repository/docker/chembl/mcp (see https://chembl.blogspot.com/2020/01/new-chembl-ligand-based-target.html for more information). We also plan to provide a new target prediction web service in the future. The current target prediction web service (https://www.ebi.ac.uk/chembl/api/data/target_prediction/) has now been deprecated.

* Updated Data Sets:
Scientific Literature
Patent Bioactivity Data
Orange Book
USP Dictionary of USAN and International Drug Names
Clinical Candidates
WHO Anatomical Therapeutic Chemical Classification
British National Formulary
Manually Added Drugs

Database changes:

# Columns Added:

CELL_DICTIONARY
CELL_ONTOLOGY_ID VARCHAR2(10) ID for the corresponding cell type in the Cell Ontology

VARIANT_SEQUENCES
TAX_ID   NUMBER(11,0) NCBI Tax ID for the organism from which the sequence was obtained

COMPOUND_PROPERTIES
CX_MOST_APKA NUMBER(9,2) The most acidic pKa calculated using ChemAxon v17.29.0
CX_MOST_BPKA NUMBER(9,2) The most basic pKa calculated using ChemAxon v17.29.0
CX_LOGP NUMBER(9,2) The calculated octanol/water partition coefficient using ChemAxon v17.29.0
CX_LOGD NUMBER(9,2) The calculated octanol/water distribution coefficient at pH7.4 using ChemAxon v17.29.0

# Columns Removed:

COMPOUND_PROPERTIES
ACD_MOST_APKA Replaced by CX_MOST_APKA
ACD_MOST Replaced by CX_MOST_BPKA
ACD_LOGP Replaced by CX_LOGP
ACD_LOGD Replaced by CX_LOGD


Funding acknowledgements:

Work contributing to ChEMBL26 was funded by the Wellcome Trust, EMBL Member States, Open Targets, National Institutes of Health (NIH), EU Innovative Medicines Initiative 2 (IMI2) and EU Horizon 2020 programmes. Please see https://chembl.gitbook.io/chembl-interface-documentation/acknowledgments for more details.


If you require further information about ChEMBL, please contact us: chembl-help@ebi.ac.uk

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