Cargando…
Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME
Today’s large, public databases of protein–small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to custom scripting for informatics and data analysis. He...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4572361/ https://www.ncbi.nlm.nih.gov/pubmed/26384374 http://dx.doi.org/10.1093/database/bav087 |
_version_ | 1782390391679483904 |
---|---|
author | Nicola, George Berthold, Michael R. Hedrick, Michael P. Gilson, Michael K. |
author_facet | Nicola, George Berthold, Michael R. Hedrick, Michael P. Gilson, Michael K. |
author_sort | Nicola, George |
collection | PubMed |
description | Today’s large, public databases of protein–small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to custom scripting for informatics and data analysis. Here, we illustrate how the large protein-ligand database BindingDB may be incorporated into KNIME workflows as a step toward the integration of pharmacological data with broader biomolecular analyses. Thus, we describe a collection of KNIME workflows that access BindingDB data via RESTful webservices and, for more intensive queries, via a local distillation of the full BindingDB dataset. We focus in particular on the KNIME implementation of knowledge-based tools to generate informed hypotheses regarding protein targets of bioactive compounds, based on notions of chemical similarity. A number of variants of this basic approach are tested for seven existing drugs with relatively ill-defined therapeutic targets, leading to replication of some previously confirmed results and discovery of new, high-quality hits. Implications for future development are discussed. Database URL: www.bindingdb.org |
format | Online Article Text |
id | pubmed-4572361 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-45723612015-09-18 Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME Nicola, George Berthold, Michael R. Hedrick, Michael P. Gilson, Michael K. Database (Oxford) Original Article Today’s large, public databases of protein–small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to custom scripting for informatics and data analysis. Here, we illustrate how the large protein-ligand database BindingDB may be incorporated into KNIME workflows as a step toward the integration of pharmacological data with broader biomolecular analyses. Thus, we describe a collection of KNIME workflows that access BindingDB data via RESTful webservices and, for more intensive queries, via a local distillation of the full BindingDB dataset. We focus in particular on the KNIME implementation of knowledge-based tools to generate informed hypotheses regarding protein targets of bioactive compounds, based on notions of chemical similarity. A number of variants of this basic approach are tested for seven existing drugs with relatively ill-defined therapeutic targets, leading to replication of some previously confirmed results and discovery of new, high-quality hits. Implications for future development are discussed. Database URL: www.bindingdb.org Oxford University Press 2015-09-16 /pmc/articles/PMC4572361/ /pubmed/26384374 http://dx.doi.org/10.1093/database/bav087 Text en © The Author(s) 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Nicola, George Berthold, Michael R. Hedrick, Michael P. Gilson, Michael K. Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title | Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title_full | Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title_fullStr | Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title_full_unstemmed | Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title_short | Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME |
title_sort | connecting proteins with drug-like compounds: open source drug discovery workflows with bindingdb and knime |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4572361/ https://www.ncbi.nlm.nih.gov/pubmed/26384374 http://dx.doi.org/10.1093/database/bav087 |
work_keys_str_mv | AT nicolageorge connectingproteinswithdruglikecompoundsopensourcedrugdiscoveryworkflowswithbindingdbandknime AT bertholdmichaelr connectingproteinswithdruglikecompoundsopensourcedrugdiscoveryworkflowswithbindingdbandknime AT hedrickmichaelp connectingproteinswithdruglikecompoundsopensourcedrugdiscoveryworkflowswithbindingdbandknime AT gilsonmichaelk connectingproteinswithdruglikecompoundsopensourcedrugdiscoveryworkflowswithbindingdbandknime |