Paul Dobson's Workflows

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Workflow Wash and filter molecules (1)

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The Wash and Filter workflow performs some processing on incoming structures to filter out those wildcards or unspecified atom types, standardise stereo and charges, and various other adjustments. This is an advance on the filter used in the paper... Drug Discovery Today Volume 14, Issues 1-2, January 2009, Pages 31-40 ‘Metabolite-likeness’ as a criterion in the design and selection of pharmaceutical drug libraries  

Created: 2009-01-20

Credits: User Paul Dobson

Workflow CDK Example (1)

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This workflow reads a library from an SD file (change the default value of Read_MDL_SD_File) and identifies those structures that conform to Lipinski's Rule of Five. It then performs a substructure query, represented as SMILES (change the default value on Parse_SMILES), on the structures that pass Lipinski, and creates PNG images of those structures that contain the substructure. The image results will be found in your Taverna Data folder.

Created: 2009-02-26

Credits: User Paul Dobson

Workflow M5 Charge Matching (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithm M5 which ionises molecules at pH 7 prior to matching, restores original structures.

Created: 2010-06-03

Credits: User Paul Dobson

Workflow M4 Tautomer Matching (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithm M4 which generates canonical tautomers prior to matching, matches, then restores original structures.

Created: 2010-06-03

Credits: User Paul Dobson

Workflow M3 Non-stereo Matching (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithm M3 which strips stereochemical information from molecules, performs exact matching, and restores stereochemistry.

Created: 2010-06-03

Credits: User Paul Dobson

Workflow M2 Similarity Matching (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithm M2 which reads molecules from two sources and produces clusters of highly similar molecules.

Created: 2010-06-03

Credits: User Paul Dobson

Workflow M1 Exact Matching (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithm M1 which matches fully specified molecules on the basis of their canonical representations.

Created: 2010-06-03

Credits: User Paul Dobson

Workflow C1 Combined Workflow (1)

The process of metabolic network reconstructions typically begins with the task of collating existing information. For metabolites this poses a relatively straight forward set of cheminformatics problems. This workflow implements matching algorithms M1-M5 in one workflow, yielding a sparse matrix of matches annotated by match types.

Created: 2010-06-03 | Last updated: 2010-06-03

Credits: User Paul Dobson

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