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M5 Charge Matching
(v1)
Created: 03/06/10 @ 11:39:28
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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M4 Tautomer Matching
(v1)
Created: 03/06/10 @ 11:38:27
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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M3 Non-stereo Matching
(v1)
Created: 03/06/10 @ 11:35:03
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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M2 Similarity Matching
(v1)
Created: 03/06/10 @ 11:33:36
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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M1 Exact Matching
(v1)
Created: 03/06/10 @ 11:32:02
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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C1 Combined Workflow
(v1)
Created: 03/06/10 @ 11:26:48
| Last updated: 03/06/10 @ 11:30:10
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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CDK Example
(v1)
Created: 26/02/09 @ 16:31:21
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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.
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Wash and filter molecules
(v1)
Created: 20/01/09 @ 10:11:25
Credits:
Paul Dobson
License: Creative Commons Attribution-Share Alike 3.0 Unported License
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
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