This project will develop technologies to improve the integration of ligand and protein data for structure-based prediction of protein-ligand selectivity and polypharmacology.

The project will use KNIME Analytics Platform to integrate the different technologies and datasets.

To install 3D-e-Chem KNIME nodes use the community contributions software site.

• Project homepage
• Github organization
• News
• Team
• Repositories
• Publications
• Data sets
• Dissemination

3D-e-Chem partners and collaborators:

• VU Medicinal Chemistry
• CMBI Radboud University
• Netherlands eScience Center
• University of Copenhagen
• Heptares Therapeutics
• GPCR Consortium
• GPCRdb
• ONCORNET

Latest news

• Mar 9, 2018

  KNIME Spring summit 2018

read more

Repositories

• 3D-e-Chem-VM Shell

  Virtual machine with all software and sample data to run 3D-e-Chem KNIME workflows

• knime-gpcrdb Java

  GPCRDB nodes for KNIME

• knime-klifs Java

  KNIME plugin for retrieving data from KLIFS. KLIFS is a structural kinase-ligand interaction database.

• knime-kripodb Java

  KNIME nodes for KripoDB Python package

• knime-modified-tanimoto Java

  KNIME plugin for calculating distance of bitvector using Modifed Tanimoto similarity index

• knime-molviewer Java

  KNIME node which launches a web browser with a molecule viewer

• knime-pharmacophore Java

  KNIME nodes to align, read and write pharmacophores

• knime-plants Java

  KNIME nodes to configure, run and analyze PLANTS protein-ligand docking

• knime-python-node-archetype Java

  Maven archetype to generate KNIME workflow Python node skeleton repository with sample code.

• knime-python-wrapper Java

  Utilities for development of KNIME nodes calling Python scripts.

• knime-silicos-it Java

  KNIME nodes to run Silicos-it software like align-it and shape-it.

• knime-sstea Java

  KNIME node to calculate subfamily specific two entropy analysis (ss-TEA) score.

• knime-sygma Java

  SyGMa KNIME nodes for the Systematic Generation of potential Metabolites.

• knime-testflow Java

  Test KNIME workflows from a Junit test

• kripodb Python

  Generator of Kripo fingerprints from PDB files

• kripodb Python

  Library to interact with Kripo fragment, fingerprint and similarity data files.

• rdkit-react Python

  Script to perform reactions on molecules using RDKIT

• snooker-alignment Python

  Scripts to generate a GPCR multiple sequence alignment

• SyGMa Python

  SyGMa is a python library for the Systematic Generation of potential Metabolites.

• tycho-knime-node-archetype Java

  Maven archetype to generate KNIME workflow node skeleton repository with sample code.

• workflows KNIME

  KNIME workflows developed in project using nodes developed in project.

 Publications

• Vass, M., Kooistra, A. J., Yang, D., Stevens, R. C., Wang, M.-W., & de Graaf, C. (2018). Chemical Diversity in the G Protein-Coupled Receptor Superfamily. Trends in Pharmacological Sciences, 39(5), 494–512. doi:10.1016/j.tips.2018.02.004
• Kooistra, A. J., Vass, M., McGuire, R., Leurs, R., de Esch, I. J. P., Vriend, G., … de Graaf, C. (2018). 3D-e-Chem: Structural Cheminformatics Workflows for Computer-Aided Drug Discovery. ChemMedChem, 13(6), 614–626. doi:10.1002/cmdc.201700754
• Vass, M., Kooistra, A. J., Verhoeven, S., Gloriam, D., de Esch, I. J. P., & de Graaf, C. (2017). A Structural Framework for GPCR Chemogenomics: What’s In a Residue Number? Computational Methods for GPCR Drug Discovery, 73–113. doi:10.1007/978-1-4939-7465-8_4
• McGuire, R., Verhoeven, S., Vass, M., Vriend, G., de Esch, I. J. P., Lusher, S. J., … de Graaf, C. (2017). 3D-e-Chem-VM: Structural Cheminformatics Research Infrastructure in a Freely Available Virtual Machine. Journal of Chemical Information and Modeling, 57(2), 115–121. doi:10.1021/acs.jcim.6b00686
• Vass, M., Kooistra, A. J., Ritschel, T., Leurs, R., de Esch, I. J., & de Graaf, C. (2016). Molecular interaction fingerprint approaches for GPCR drug discovery. Current Opinion in Pharmacology, 30, 59–68. doi:10.1016/j.coph.2016.07.007
• Kooistra, A. J., Vischer, H. F., McNaught-Flores, D., Leurs, R., de Esch, I. J. P., & de Graaf, C. (2016). Function-specific virtual screening for GPCR ligands using a combined scoring method. Scientific Reports, 6(1). doi:10.1038/srep28288
• Kooistra, A. J., Kanev, G. K., van Linden, O. P. J., Leurs, R., de Esch, I. J. P., & de Graaf, C. (2015). KLIFS: a structural kinase-ligand interaction database. Nucleic Acids Research, 44(D1), D365–D371. doi:10.1093/nar/gkv1082

Data sets

• Vass, Marton, Podlewska, Sabina, Kooistra, Albert, Kuhne, Sebastiaan, Racz, Anita, Leurs, Rob, de Esch, Iwan, Bojarski, Andrzej, de Graaf, Chris. (2016). Aminergic G protein-coupled receptor (GPCR) mutation data set. Zenodo. http://doi.org/10.5281/zenodo.58104
• Arimont, Marta, Sun, Shanliang, Vass, Marton, Smit, Martine, Leurs, Rob, de Esch, Iwan, de Graaf, Chris. (2016). Chemokine G protein-coupled receptor (GPCR) mutation data set. Zenodo. http://doi.org/10.5281/zenodo.58160

Dissemination

Tutorials

• 3D-e-Chem KNIME Nodes for Integrated Structural Cheminformatics Analyses and Computer-Aided Drug Discovery

Posters

• Verhoeven, Stefan, Vass, Marton, de Esch, Iwan, Leurs, Rob, Lusher, Scott, Vriend, Gerrit, Ritschel, Tina, de Graaf, Chris, McGuire, Ross. (2016). 3D-e-Chem VM: Cheminformatics Research Infrastructure in a Downloadable Virtual Machine. Zenodo. http://doi.org/10.5281/zenodo.47208
• Vass, Marton, Verhoeven, Stefan, McGuire, Ross, Kooistra, Albert J., Ridder, Lars, Ritschel, Tina, de Esch, Iwan, Leurs, Rob, Vriend, Gerrit, de Graaf, Chris. (2016). 3D-e-Chem-VM: Cheminformatics Toolbox in a freely available Virtual Machine. Zenodo. http://doi.org/10.5281/zenodo.161567

Links

• Kinase-Ligand Interaction Fingerprint and Structures database
• PhosphoDiEsterase Structure and ligand Interaction Annotated database