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TeachOpenCADD with modification

TeachOpenCADD - a teaching platform for computer-aided drug design using KNIME

The TeachOpenCADD KNIME (v1.0.5) pipeline consists of eight inter-connected workflows (W1-8) , each containing one topic in computer-aided drug design.
The pipeline is illustrated using the epidermal growth factor receptor (EGFR), but can easily be applied to other targets of interest. Topics include how to fetch, filter and analyze compound data associated with a query targe.

URL: Zenodo DOI https://doi.org/10.5281/zenodo.3475085

[W2 W3 W4 W5 W6]
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W2
W6
W7
W8
W4
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W5
W3
W2
W1
W3
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[W2 W3 W4 W7]
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[W2 W3 W4 W5 W6]TeachOpenCADD: A teaching platform for computer-aided drug design using KNIME
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[genuine]TeachOpenCADD: A teaching platform for computer-aided drug design using KNIME
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[W2 W3 W4 W7]TeachOpenCADD: A teaching platform for computer-aided drug design using KNIME
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Dominique Sydow, Michele Wichmann, Jaime Rodríguez-Guerra, Daria Goldmann, Gregory Landrum, andAndrea Volkamer
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W5
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Dominique Sydow, Michele Wichmann, Jaime Rodríguez-Guerra, Daria Goldmann, Gregory Landrum, andAndrea Volkamer
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[W2 W3 W4 W5 W6]TeachOpenCADD: A teaching platform for computer-aided drug design using KNIME
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Compound set
Table View (JavaScript) (legacy)
Similarity to query
Scatter plot
Score view
Evaluate model
Filtered compound set
Table View (JavaScript) (legacy)
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Dataset clustered byFingerprint similarity Note: Clustering takes time!
5. Compound clustering
Similarity to query
Scatter plot
Keep only top 2000 mols
Row Filter (deprecated)
ROC curve
Evaluate model
Temsirolimus & Rapamisin
Query compound
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Input target ChEMBL ID
Keep only top 2000 mols
Row Filter (deprecated)
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
Temsirolimus & Rapamisin
Query compound
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
Filtered compound set
Table View (JavaScript) (legacy)
Highlighted MCS
Table View (JavaScript) (legacy)
Input target ChEMBL ID
Keep only top 2000 mols
Row Filter (deprecated)
Compound set
Table View (JavaScript) (legacy)
Score view
Evaluate model
Similarity to query
Scatter plot
Filtered compound set
Table View (JavaScript) (legacy)
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
Input target ChEMBL ID
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
Similarity to query
Scatter plot
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Compound set
Table View (JavaScript) (legacy)
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Get MCS for largest cluster in dataset
6. Maximum common substructures
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Dataset clustered byFingerprint similarity Note: Clustering takes time!
5. Compound clustering
ROC curve
Evaluate model
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Tanimoto similarity
Enrichment Plotter (legacy)
Line Plot (JavaScript) (legacy)
Tanimoto similarity
Enrichment Plotter (legacy)
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
Temsirolimus & Rapamisin
Query compound
Diverse subset from clusters
Table View (JavaScript) (legacy)
Score view
Evaluate model
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Tanimoto similarity
Enrichment Plotter (legacy)
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Score view
Evaluate model
Filtered compound set
Table View (JavaScript) (legacy)
Input target ChEMBL ID
Compound set
Table View (JavaScript) (legacy)
Similarity to query
Scatter plot
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
Keep only top 2000 mols
Row Filter (deprecated)
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
ROC curve
Evaluate model
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
Input target ChEMBL ID
Temsirolimus & Rapamisin
Query compound
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Score view
Evaluate model
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
ROC curve
Evaluate model
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Filtered compound set
Table View (JavaScript) (legacy)
Compound set
Table View (JavaScript) (legacy)
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Similarity to query
Scatter plot
Keep only top 2000 mols
Row Filter (deprecated)
Tanimoto similarity
Enrichment Plotter (legacy)
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Highlighted MCS
Table View (JavaScript) (legacy)
Input target ChEMBL ID
Temsirolimus & Rapamisin
Query compound
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Dataset filtered & formatted bybioactivity and SMILES
1. Data acquisition from ChEMBL
Tanimoto similarity
Enrichment Plotter (legacy)
ML classifier(applicable to new compounds)
7. Ligand-based screening: machine learning
Dataset filtered byunwanted substructures
3. Molecular filtering: unwanted substructures
Dataset filtered by X-ray,resolution & presence of ligand Note: Target ChEMBL ID can only be changed inside the metanode
8. Protein data acquisition: Protein Data Bank (PDB)
ROC curve
Evaluate model
Compounds with PAINS/Brenk
Table View (JavaScript) (legacy)
Filtered compound set
Table View (JavaScript) (legacy)
Compound set
Table View (JavaScript) (legacy)
Temsirolimus & Rapamisin
Query compound
Score view
Evaluate model
Line Plot (JavaScript) (legacy)
Diverse subset from clusters
Table View (JavaScript) (legacy)
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Dataset filtered by Lipinski's rule of five
2. Molecular filtering: ADME and lead-likeness criteria
ROC curve
Evaluate model
Compounds without PAINS/Brenk
Table View (JavaScript) (legacy)
Keep only top 2000 mols
Row Filter (deprecated)
Dataset ranked bysimilarity to query compound
4. Ligand-based screening: compound similarity
Phys. chem. properties
Box Plot (JavaScript) (legacy)
Get MCS for largest cluster in dataset
6. Maximum common substructures
Tanimoto similarity
Enrichment Plotter (legacy)

Nodes

Extensions

Links

Download

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

Download Workflow
Created by: michele
Created at: 2019-01-10
On NodePit since: 2025-12-25
Last update: 2025-12-25
Created with KNIME version: v5.8.0
Tags: ChEMBL queryPDB queryMolecular filteringUnwanted substructuresLipinski's rule of fiveSimilarity searchCompound clusteringMaximum common substructureMachine learning

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