Use Case C, Worflow 1

Created: 2014-05-26 13:29:17      Last updated: 2014-11-25 16:11:42

Workflow used to obtain data for the research paper ‘The application of the Open Pharmacological Concepts Triple Store (Open PHACTS) to support Drug Discovery Research’, currently submitted to PLOS ONE.  


This workflow can be used to get approved drugs from a pathway of interest using the Open PHACTS API

Requirements:
- Knime v2.9
- Open PHACTS Knime nodes 1.0.0 (DON'T use any later version!): https://github.com/openphacts/OPS-Knime

Installation:
- Download "org.openphacts.utils.json_1.0.0.zip" and unzip it in the plugins folder of your KNIME installation
- Download the workflow (Use Case C_Workflow1.zip)
- Start your Knime environment (you should see already a couple of new nodes at the ‘Node Repository’, like OPS_KNIME)
- Import the workflow (file>>import-workflow...>>select archive file)

Running:
- Double click on the desired workflow
- Reset the OPS nodes (in orange)
- Execute the nodes. Because of a bug found, the OPS nodes have to be run one by one to avoid the retrieved columns of the metanodes get mixed up.

Description of the Workflow:
This workflow starts with a Wikipathway URI. The URI of the pathway has been copied from Wikipathways (http://wikipathways.org/index.php/Pathway:WP1531) after choosing the pathway of interest.
Using the above URI as input:
1. We use ‘Pathway Information’ API call to get information about the pathway such as the version of the data, the title and its description.
 2. A list of proteins and genes in the pathway can be retrieved directly with Pathway Information: Get Targets. We use those targets as input for ‘Target Pharmacology: List’ (2.1) and ‘Target Information’ API calls (2.2).
2.1 The Target Pharmacology: List API call is used to retrieve pharmacology data from ChEMBL. In this case we return the data using ‘_pageSize=250’ in combination with a loop overall result sets with the ‘_page’ parameter. Also the parameter/value ‘target_type = protein_complex’ has been used to retrieve only protein complexes. Then we apply filters (2.1.1) to remove: Unspecified Activity value, Activity comment = inactive, inconclusive, Not determined and/or Not active and Potential data errors (values larger than 1E08 are removed) using ‘Row filter’ and ‘Row Splitter’ nodes. 2.1.2 From compounds retrieved above, we use ‘Compound Information API’ call to get information about the compounds. To get approved drugs, we use the ‘Row Filter’ node (Drug type = approved).
2.2 With the list of proteins/genes from step 2, we use Target Information API to get target information and the approved drugs are filtered as before (2.1.2). We again use Target Information to retrieve target names.  
The outputs from 2.1 and 2.2 are concatenated to get the final Table.  
3. Other Pathways where a certain target is present are retrieved using ‘Pathways for Target: List’ API call. After that, we remove the initial pathway using the ‘row filter’ node and we group them by ‘target name’.

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