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Empowering pharmacoinformatics by linked life science data

With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or P...

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Detalles Bibliográficos
Autores principales: Goldmann, Daria, Zdrazil, Barbara, Digles, Daniela, Ecker, Gerhard F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385323/
https://www.ncbi.nlm.nih.gov/pubmed/27830428
http://dx.doi.org/10.1007/s10822-016-9990-4
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author Goldmann, Daria
Zdrazil, Barbara
Digles, Daniela
Ecker, Gerhard F.
author_facet Goldmann, Daria
Zdrazil, Barbara
Digles, Daniela
Ecker, Gerhard F.
author_sort Goldmann, Daria
collection PubMed
description With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-016-9990-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-53853232017-04-24 Empowering pharmacoinformatics by linked life science data Goldmann, Daria Zdrazil, Barbara Digles, Daniela Ecker, Gerhard F. J Comput Aided Mol Des Article With the public availability of large data sources such as ChEMBLdb and the Open PHACTS Discovery Platform, retrieval of data sets for certain protein targets of interest with consistent assay conditions is no longer a time consuming process. Especially the use of workflow engines such as KNIME or Pipeline Pilot allows complex queries and enables to simultaneously search for several targets. Data can then directly be used as input to various ligand- and structure-based studies. In this contribution, using in-house projects on P-gp inhibition, transporter selectivity, and TRPV1 modulation we outline how the incorporation of linked life science data in the daily execution of projects allowed to expand our approaches from conventional Hansch analysis to complex, integrated multilayer models. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10822-016-9990-4) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-11-09 2017 /pmc/articles/PMC5385323/ /pubmed/27830428 http://dx.doi.org/10.1007/s10822-016-9990-4 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Goldmann, Daria
Zdrazil, Barbara
Digles, Daniela
Ecker, Gerhard F.
Empowering pharmacoinformatics by linked life science data
title Empowering pharmacoinformatics by linked life science data
title_full Empowering pharmacoinformatics by linked life science data
title_fullStr Empowering pharmacoinformatics by linked life science data
title_full_unstemmed Empowering pharmacoinformatics by linked life science data
title_short Empowering pharmacoinformatics by linked life science data
title_sort empowering pharmacoinformatics by linked life science data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5385323/
https://www.ncbi.nlm.nih.gov/pubmed/27830428
http://dx.doi.org/10.1007/s10822-016-9990-4
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