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EUbOPEN CGL GPCR Ligand Selector

This workflow was designed as part of WP1 'Collection of available candidate compounds from academia and industry' within the IMI-2-funded EUbOPEN project (https://www.eubopen.org/). The workflow specifically identifies commercially available candidate GPCR ligands within the criteria set by the EUbOPEN consortium. Commercial vendors have been limited to Sigma-Aldrich, Cayman and Tocris. However, due to legal constraints the full set of commercial ligands considered cannot be shared, and a mock Vendor Compounds table containing the final set of 2443 candidate ligands is used here instead, so that the final results can be reproduced.

The workflow collects structure-activity relationship (SAR) data for GPCR ligands from ChEMBLdb and from this generates a target matrix, a table with primary and off-targets, a table with selectivity scores, and a table with structural similarities of the ligand set. These are then joined and a Pareto ranking is performed, favouring ligands with high potency on their primary target, high selectivity, and low structural similarity. For each target the ligands are then ranked by Pareto score, allowing for selection of the most interesting ligands per target.

To reproduce the results you need to download a local copy of the ChEMBLdb in SQLite format from https://ftp.ebi.ac.uk/pub/databases/chembl/ChEMBLdb/releases/chembl_32/ and connect to the chembl_32.db file using the SQLite Connector node. You also need Community Contribution nodes from RDKit, Vernalis, Erlwood and ChemAxon/InfoCOM.

This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No 875510. The JU receives support from the European Union’s Horizon 2020 research and innovation programme the European Federation of Pharmaceutical Industries and Associations (EFPIA), the Ontario Institute for Cancer Research, the Royal Institution for the Advancement of Learning McGill University, Kungliga Tekniska Hoegskolan, and Diamond Light Source Limited. This communication reflects the views of the authors and the JU is not liable for any use that may be made of the information contained herein.

Node 952Node 961Node 964Node 966Node 969Node 971Node 976Node 985Node 987Node 988Ligands per targetNode 994Node 995Vendor CompoundsSelectivity Entropy Target Matrix Pareto Ranking RowID SQLite Connector StructuralSimilarity Joiner Joiner Structure-ActivityData Joiner Sorter Primary &Off-Targets ReferenceRow Filter Joiner MolConverter SDF Writer GroupBy Column Resorter Sorter Table Reader Node 952Node 961Node 964Node 966Node 969Node 971Node 976Node 985Node 987Node 988Ligands per targetNode 994Node 995Vendor CompoundsSelectivity Entropy Target Matrix Pareto Ranking RowID SQLite Connector StructuralSimilarity Joiner Joiner Structure-ActivityData Joiner Sorter Primary &Off-Targets ReferenceRow Filter Joiner MolConverter SDF Writer GroupBy Column Resorter Sorter Table Reader

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: evert.homan
Created at: 2020-05-26
On NodePit since: 2025-10-20
Last update: 2025-10-20
Created with KNIME version: v5.2.6

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